The document outlines research topics at the Systems Biomedical Informatics National Core Research Center (SBI-NCRC) in South Korea, including:
1. Activity recognition for personalized healthcare using sensors to monitor patients and detect risky situations.
2. A healthcare service framework for continuous context monitoring using smartphones to track things like diet, activity levels, and vital signs for conditions like obesity, elderly care, and cardiac issues.
3. Text mining of web content and personalized analysis of biological and medical data.
The SBI-NCRC conducts interdisciplinary research with various universities and organizations to develop digital health avatars and personalized medicine through integration of clinical and biological information using information technology.
This document provides a vita for Nicos Maglaveras, including his personal information, education history, professional appointments, teaching experience, research experience, EU projects involvement, publications, and awards. It details that he is a Professor of Computing & Medical Informatics at Aristotle University of Thessaloniki in Greece. Over the past 25+ years, he has led over 40 EU-funded projects totaling over 12 million euros, published over 95 journal papers cited over 3,000 times, and received several awards for excellence in research.
Biomedical Signal Processing / Biomedical Signals/ Bio-signals/ Bio-signals C...Mehak Azeem
These amazing and highly informative slides presented to the IEEE Signal Processing Society of IEEE MESCE Student Branch. These slides aim to provide basic knowledge about biosignals, their classification, examples and their working.
For more information, please contact:
[mehakazeem@ieee.org]
Development of a Home-based Wrist Rehabilitation System IJECEIAES
There are several factors that may result to wrist injuries such as athlete injuries and stroke. Most of the patients are unable to undergo rehabilitation at healthcare providers due to cost and logistic constraint. To solve this problem, this project proposes a home-based wrist rehabilitation system. The goal is to create a wrist rehabilitation device that incorporates an interactive computer game so that patients can use it at home without assistance. The main structure of the device is developed using 3D printer. The device is connected to a computer, where the device provides exercises for the wrist, as the user completes a computer game which requires moving a ball to four target positions. Data from an InvenSense MPU-6050 accelerometer is used to measure wrist movements. The accelerometer values are read and used to control a mouse cursor for the computer game. The pattern of wrist movements can be recorded periodically and displayed back as sample run for analysis purposes. In this paper, the usefulness of the proposed system is demonstrated through preliminary experiment of a subject using the device to complete a wrist exercise task based on the developed computer game. The result shows the usefulness of the proposed system.
Design and Implementation of Smart Monitoring Systems in Hospital Wagon using...ijtsrd
Nowadays, many researchers are contributing their research in the field of Internet of things IOT , since it is important and attractive technology. IOT means communication between human to device or device to device, anywhere in real time. This communication takes place with the help of different smart sensors which are connected via internet. In the IOT infrastructure different sensors can sense, analyse, transmit and store all the datas on cloud. This paper presents a wearable sensor network system for Internet of Things IoT connected safety and health applications. The wearable sensors on different subjects can communicate with each other and transmit the data to a gateway via a Local Area Network which forms a heterogeneous IoT platform with wifi based medical signal sensing network. It consists of two sections the basic information and condition of patient is collected in the wagon by the means IoT Internet of Things and make it available to hospital before the emergency vehicle reaches the hospital. On the base of such data, the system is able to detect anomalous situations and provide information about the status directly and exclusively to the hospital. The second path is control of traffic lights from the wagon and makes free for its path automatically. This project is to save the time of major late time aspects in more efficient manner and save the life. Mrs. S. Kirthica | Mrs. S. Priyadharsini "Design and Implementation of Smart Monitoring Systems in Hospital Wagon using IoT Technology: A Case Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31731.pdf Paper Url :https://www.ijtsrd.com/mathemetics/other/31731/design-and-implementation-of-smart-monitoring-systems-in-hospital-wagon-using-iot-technology-a-case-study/mrs-s-kirthica
This document discusses how robotics and machine intelligence could impact the future of hospitals. It notes that rising healthcare costs are driving a need to reduce costs and increase reliability through new technologies. The document outlines current and emerging technologies like disinfection robots, transport robots, surgical robots, telemedicine, sensors, and more advanced machine intelligence. It envisions future hospitals becoming more specialized facilities using robotics and AI to replace many routine functions and help diagnose and treat patients more efficiently. The hospital of the future is predicted to have autonomous machines, multi-functional patient rooms, and machine intelligence constantly optimizing resource use.
Special Report: Medical Robotics
Self-propelled nanobots that deliver drugs inside the human body...novel sensors that improve the safety and precision of industrial robots...a dynamic hydrogel material that makes building soft robotic devices as simple as assembling a LEGO set. These are just a few of the medical robotics innovations you'll read about in this compendium of recent articles from the editors of Medical Design Briefs and Tech Briefs magazines.
Design of an internet of things based real-time monitoring system for retired...journalBEEI
The main aim of this article is to design a monitoring center for collecting and evaluating the physiological function of retired patients in nursing homes. The system should be able to collect the information of body heat, heart rate, blood oxygen, orientation, and sleep time in the form of the little bracelet. The evaluating part of the system with the program can be placed into personal computer (PC) which can provide a user-friendly interface and easy managing. The program can display all needed information of the patient from previous days or months in the form of the graphs and the nursing person can have the view of the patient´s physiological health. The evaluation and the collection of the data from each patient are done only on the card and the computer is only a device for live-view and managing. In case of the power failure, the monitoring system will be still operating normally due to the uninterruptible power supply (UPS) in the form of the battery. It means that the system will operate even if the PC is powered off. The system also has several external communication interfaces like wireless fidelity (Wi-Fi), ethernet, and general packet radio service (GPRS) which provides an external connection.
The worldwide network of internet of things (IOT) combined with advancements in sensor networks, FID and software platform connects objects of various application fields and technology. IOT is most commonly described as an ecosystem of technologies but it requires necessary components to enable communication between devices and objects. Components being RFID and sensors. Many organization have already implemented IOT. Healthcare industry too have adopted IOT and can be extensively used in the future for the benefit of patients, elderly people and caregivers. A new concept named 'Health Internet of Things (HIOT)' was proposed to exploit sensor technologies and wireless networks in monitoring medical conditions. Also advancements in E textile technologies make the textile multifunctional, adaptive and responsive system which combined with IOT performs functions such as communication, computation and health care benefits. Cloud is used to store, control and retrieve or transform or classify information. The use of cloud based application in healthcare industries is constantly growing to benefit patients so that they can monitor their health, store and share records. This paper aims at developing a dependable, productive, high performance and assured smart healthcare system to deliver service to patients avoiding health risks using e textile technologies
This document provides a vita for Nicos Maglaveras, including his personal information, education history, professional appointments, teaching experience, research experience, EU projects involvement, publications, and awards. It details that he is a Professor of Computing & Medical Informatics at Aristotle University of Thessaloniki in Greece. Over the past 25+ years, he has led over 40 EU-funded projects totaling over 12 million euros, published over 95 journal papers cited over 3,000 times, and received several awards for excellence in research.
Biomedical Signal Processing / Biomedical Signals/ Bio-signals/ Bio-signals C...Mehak Azeem
These amazing and highly informative slides presented to the IEEE Signal Processing Society of IEEE MESCE Student Branch. These slides aim to provide basic knowledge about biosignals, their classification, examples and their working.
For more information, please contact:
[mehakazeem@ieee.org]
Development of a Home-based Wrist Rehabilitation System IJECEIAES
There are several factors that may result to wrist injuries such as athlete injuries and stroke. Most of the patients are unable to undergo rehabilitation at healthcare providers due to cost and logistic constraint. To solve this problem, this project proposes a home-based wrist rehabilitation system. The goal is to create a wrist rehabilitation device that incorporates an interactive computer game so that patients can use it at home without assistance. The main structure of the device is developed using 3D printer. The device is connected to a computer, where the device provides exercises for the wrist, as the user completes a computer game which requires moving a ball to four target positions. Data from an InvenSense MPU-6050 accelerometer is used to measure wrist movements. The accelerometer values are read and used to control a mouse cursor for the computer game. The pattern of wrist movements can be recorded periodically and displayed back as sample run for analysis purposes. In this paper, the usefulness of the proposed system is demonstrated through preliminary experiment of a subject using the device to complete a wrist exercise task based on the developed computer game. The result shows the usefulness of the proposed system.
Design and Implementation of Smart Monitoring Systems in Hospital Wagon using...ijtsrd
Nowadays, many researchers are contributing their research in the field of Internet of things IOT , since it is important and attractive technology. IOT means communication between human to device or device to device, anywhere in real time. This communication takes place with the help of different smart sensors which are connected via internet. In the IOT infrastructure different sensors can sense, analyse, transmit and store all the datas on cloud. This paper presents a wearable sensor network system for Internet of Things IoT connected safety and health applications. The wearable sensors on different subjects can communicate with each other and transmit the data to a gateway via a Local Area Network which forms a heterogeneous IoT platform with wifi based medical signal sensing network. It consists of two sections the basic information and condition of patient is collected in the wagon by the means IoT Internet of Things and make it available to hospital before the emergency vehicle reaches the hospital. On the base of such data, the system is able to detect anomalous situations and provide information about the status directly and exclusively to the hospital. The second path is control of traffic lights from the wagon and makes free for its path automatically. This project is to save the time of major late time aspects in more efficient manner and save the life. Mrs. S. Kirthica | Mrs. S. Priyadharsini "Design and Implementation of Smart Monitoring Systems in Hospital Wagon using IoT Technology: A Case Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31731.pdf Paper Url :https://www.ijtsrd.com/mathemetics/other/31731/design-and-implementation-of-smart-monitoring-systems-in-hospital-wagon-using-iot-technology-a-case-study/mrs-s-kirthica
This document discusses how robotics and machine intelligence could impact the future of hospitals. It notes that rising healthcare costs are driving a need to reduce costs and increase reliability through new technologies. The document outlines current and emerging technologies like disinfection robots, transport robots, surgical robots, telemedicine, sensors, and more advanced machine intelligence. It envisions future hospitals becoming more specialized facilities using robotics and AI to replace many routine functions and help diagnose and treat patients more efficiently. The hospital of the future is predicted to have autonomous machines, multi-functional patient rooms, and machine intelligence constantly optimizing resource use.
Special Report: Medical Robotics
Self-propelled nanobots that deliver drugs inside the human body...novel sensors that improve the safety and precision of industrial robots...a dynamic hydrogel material that makes building soft robotic devices as simple as assembling a LEGO set. These are just a few of the medical robotics innovations you'll read about in this compendium of recent articles from the editors of Medical Design Briefs and Tech Briefs magazines.
Design of an internet of things based real-time monitoring system for retired...journalBEEI
The main aim of this article is to design a monitoring center for collecting and evaluating the physiological function of retired patients in nursing homes. The system should be able to collect the information of body heat, heart rate, blood oxygen, orientation, and sleep time in the form of the little bracelet. The evaluating part of the system with the program can be placed into personal computer (PC) which can provide a user-friendly interface and easy managing. The program can display all needed information of the patient from previous days or months in the form of the graphs and the nursing person can have the view of the patient´s physiological health. The evaluation and the collection of the data from each patient are done only on the card and the computer is only a device for live-view and managing. In case of the power failure, the monitoring system will be still operating normally due to the uninterruptible power supply (UPS) in the form of the battery. It means that the system will operate even if the PC is powered off. The system also has several external communication interfaces like wireless fidelity (Wi-Fi), ethernet, and general packet radio service (GPRS) which provides an external connection.
The worldwide network of internet of things (IOT) combined with advancements in sensor networks, FID and software platform connects objects of various application fields and technology. IOT is most commonly described as an ecosystem of technologies but it requires necessary components to enable communication between devices and objects. Components being RFID and sensors. Many organization have already implemented IOT. Healthcare industry too have adopted IOT and can be extensively used in the future for the benefit of patients, elderly people and caregivers. A new concept named 'Health Internet of Things (HIOT)' was proposed to exploit sensor technologies and wireless networks in monitoring medical conditions. Also advancements in E textile technologies make the textile multifunctional, adaptive and responsive system which combined with IOT performs functions such as communication, computation and health care benefits. Cloud is used to store, control and retrieve or transform or classify information. The use of cloud based application in healthcare industries is constantly growing to benefit patients so that they can monitor their health, store and share records. This paper aims at developing a dependable, productive, high performance and assured smart healthcare system to deliver service to patients avoiding health risks using e textile technologies
This document summarizes a study that evaluated the performance of a wearable sensor called the BioHarness 3.0 (BH3) in measuring heart rate (HR) and breathing rate (BR). Twenty participants had their HR measured at rest using the BH3 and an ECG (the gold standard method). Four participants also did a walking test on a treadmill. For BR, five participants breathed at controlled rates while wearing the BH3 and a respiratory belt. The study found that the BH3 provided accurate HR values during rest (±2.1 bpm) and movement (±2.8 bpm), without needing additional processing. However, additional processing of the BH3's raw breathing waveform data improved the
This document discusses the various applications of information technology in veterinary science. It begins by introducing veterinary informatics and some key areas where IT is applied, including disease surveillance using geo-informatics, disease diagnosis using various imaging technologies, artificial intelligence in health management, and data analysis. It then discusses veterinary hospital management software and its features and advantages. Next, it covers dairy herd management software and its benefits. Finally, it briefly mentions telemedicine and its role in veterinary care.
Biomedical engineering is an interdisciplinary field that applies engineering principles to medicine. It involves developing medical devices, imaging systems, prosthetics, and more to improve healthcare. In India, biomedical engineering degrees are offered at institutions like IITs, NITs, and private colleges. Masters and PhD programs are available mainly at IITs. Research areas include tissue engineering, biomechanics, imaging, and more. Biomedical engineers work in companies developing medical technologies and at research centers. The field has opportunities both in India and abroad.
Effective use of personal health records to support emergency servicesAlba Morales
This document describes a methodology for using personal health records to support emergency services while protecting privacy. The researchers aim to identify individuals needing special assistance during emergencies and determine why assistance is needed. Their approach classifies health record attributes, filters sensitive data, and uses a knowledge base to categorize conditions and derive disability types. In a fire evacuation scenario case study, their system correctly identified 91% of individuals needing assistance and determined assistance types with high precision. The researchers conclude their approach can help emergency services while avoiding disclosure of private health information.
WBSN based safe lifestyle: a case study of heartrate monitoring system IJECEIAES
A Heart is the vital organ of the body. According to the “world health statistics 2017” by WHO, about 460,000 people die due to fatal heart attacks every year. To reduce the death rate due to fatal heart attacks and malfunctioning of the cardiovascular system, this paper proposed a Wireless Body Sensor Network (WBSN) based, portable, easily affordable, miniatured, accurate “Heartrate Monitoring System (HMS)”. HMS can be used to regularly examine the cardiac condition at home or hospital to avoid or early detection of any serious condition. Heartrate Monitoring Algorithm (HMA) was designed to observe the spread heartbeat spectrum and worked at the backend of HMS. A case study was performed for forty healthy young subjects. Each subject data was computed for 푠푢푏 ̅̅̅̅̅ − 3푆 푑 < 푠푢푏 < 푠푢푏 ̅̅̅̅̅ + 3푆 . All subjects’ 99% data lie in the custom range. The result produced by HMS was the same as the previous medical record of subjects.
IRJET- The Essence of the Surgical Navigation System using Artificial Int...IRJET Journal
The document discusses the potential for a surgical navigation system that uses artificial intelligence and augmented reality to help doctors perform surgeries. Such a system would use image processing and tracking of surgical instruments to overlay virtual images onto the real world view of the surgery. The authors argue that AI could help diagnose diseases, plan optimal surgical procedures, and provide navigation assistance during operations to improve precision and outcomes.
An Intelligent Sensing System for Sleep Motion and Stage Analysistoukaigi
This document describes an intelligent sensing system developed to analyze sleep motion and stages. The system uses a thermal infrared camera to detect body movement, a 3-electrode EEG device to determine sleep stages, and analysis algorithms. It provides 3 main types of results: (1) descriptions of sleep stages using Markov models and state duration statistics, (2) movement graphs over time, and (3) relationships between detected stages and motion, such as more movement occurring during transitions between stages. An empirical study with 2 subjects captured sensory recordings over multiple nights, demonstrating the system's ability to provide these results and its potential for in-home sleep monitoring.
Implementation of electronic stethoscope for online remote monitoring with mo...journalBEEI
The document describes the implementation of an electronic stethoscope integrated with a mobile application for online remote patient monitoring. Key points:
1. The system includes an electronic stethoscope that converts heart and lung sounds to electrical signals, and a mobile app called "Steder" that records the signals, converts them to MP3 format, and sends them to a cloud server.
2. The stethoscope hardware uses a condenser mic, amplifier, and filter to capture sounds from 20-1000Hz. The app allows sounds to be stored, played back, and sent to doctors for analysis.
3. Testing showed the hardware and app worked as intended, with sounds accurately recorded and transmitted to the cloud server
A Review Paper on Design of GPS and GSM Based Intelligent Ambulance MonitoringIJERA Editor
Proposed paper presents design of such a monitoring system for emergency patient transportation employing ARM 7 processor module. The system will be useful for monitoring ambulance location using Google map. It also include biomedical sensors to monitor heart bit rate and temperature of patient through SMS. The front end application at the monitoring system is developed using visual basic software in Personal Computers. It can display location of ambulance and status of heart bit rate and temperature of patient. After receiving SMS hospital can prepare their staff for proper treatment of coming patient.
Artificial intelligence in orthopaedicsSaswata Datta
This document discusses the history and applications of artificial intelligence in orthopaedics. It begins with definitions of AI and provides examples of early AI pioneers. It then outlines the current and potential future uses of AI in orthopaedics, including for analyzing medical images, assisting with surgical navigation and procedures, and evaluating treatments. While AI may replace some tasks, the document argues that AI will likely change and enhance the role of orthopaedic surgeons rather than replace them entirely. It closes by acknowledging challenges with AI and calling for maintaining the important doctor-patient relationship.
This document discusses the growing use of wearable sensor technology in sports medicine. It describes various types of movement sensors like pedometers, accelerometers, gyroscopes, and GPS that can track athlete movements, workloads, and positions. It also discusses physiologic sensors like heart rate monitors and temperature sensors. The document concludes that wearable sensors provide a method to monitor real-time physiology and movement to optimize performance, detect injury risks, and design efficient training programs.
introduction to biomedical engineering, Applications of biomedical engineeringJayachandran T
Bio-medical engineering applies engineering principles and design concepts to medicine and biology. It combines engineering and medical sciences to advance healthcare, including through developing diagnostic and therapeutic medical equipment, devices, and technologies. Some examples include designing artificial organs and prosthetics, maintaining medical equipment, and researching the engineering of biological systems. Bio-medical engineers also evaluate medical technology, train clinicians on equipment use, and publish research findings.
Computer systems and the internet have greatly improved healthcare in several ways:
1. Electronic medical records allow doctors to access complete patient histories instantly and share information between hospitals. Computerized prescriptions reduce errors.
2. Diagnostic tools like CT scans, MRIs, and ultrasounds can identify medical issues much faster and more accurately than before. Monitoring equipment keeps close tabs on patients' vital signs.
3. Treatments are also enhanced through robotics in surgery, pacemakers, ventilators, and prosthetics that can mimic natural limb movement. Online support groups and research databases help patients.
4. However, self-diagnosis online risks missing issues, and purchasing medications without a prescription
The information technology played an important role in information
and knowledge dissemination in the last decade. The usage of IT to
transfer information and knowledge in the animal health care domain
using expert systems is one of the areas investigated by many
institutions. The current era is witnessing a vast development in all
fields of animal health care. Therefore there is a need for an
unconventional method to transfer the knowledge of experts in this
domain to the general public of livestock holders, especially that the
number of experts in new technologies is lesser than their demand in a
certain domain. The transfer of knowledge from veterinary consultants
& scientists to livestock holders represents a bottleneck for the
development of animal health care in any country. Expert systems are
simply computer software programs that mimic the behaviour of human
experts. They are one of the successful applications of the Artificial
Intelligence field, a branch in Computer Science that investigates how
to make the machine think like human or do tasks that humans do.
Expert Systems are very helpful to ensure an effective and nationally
coordinated approach in response to emergency incidents and in routine
bio-security activities. Such systems enable better management of the
information and resources used to manage animal’s diseases and
emergency responses to incursions.
The heart is a vital organ that serves to pump blood to the whole body. A heart rate can be used as a healthy body parameter conditions. Growing evidence suggests that IT-based health records play essential role to drive medical revolution especially on data storage and processing. The heart rate measurement (HRM) process usually involves wearable sensor devices to record patient’s data. This data is recorded to help the doctors to analyze and provide a better diagnose in order to determine the best treatment for the patients. Connecting the sensor system through a wireless network to a cloud server will enable the doctor to monitor remotely. This paper presents fit-NES wearable bracelet, an alternative method for integrating a HR measurement device using optical based pulse sensor and Bluetooth-based communication module. This paper is also present the benchmarking of proposed system with several various commercial HR measurement devices.
There are a number of scopes for IoT in order to make a difference in lives of patients. The devices can capture as well as monitor related data regarding patient and allows the providers to obtain the insights without bringing the patients visiting. The procedure can assist the patient results as well as preventing the possible communications for the process that involves risk. However, lack of electronic health record (EHR) system integration is one of the major issues faced while using IoT in healthcare. Some of the EHR systems allow the patients importing data into the record. However, it remains limited to a few dominant where the EHR players as well as leaves providers unspecific of the processing data that can be helpful for the organization to use the process. The challenges for interoperability in order to keep data in distinctive medical devices depend on the purpose and ordering physician. by Vishal Dineshkumar Soni 2018. An IoT Based Patient Health Monitoring System. International Journal on Integrated Education. 1, 1 (Dec. 2018), 43-48. DOI:https://doi.org/10.31149/ijie.v1i1.481. https://journals.researchparks.org/index.php/IJIE/article/view/481/458 https://journals.researchparks.org/index.php/IJIE/article/view/481
In nuclear medicine, molecular imaging is applied. It employs various methods to picture biological processes that are reacting in the cells. Radiopharmaceuticals are used in molecular imaging. It is used in small quantities called radioactive markers. It offers detailed information about the biological processes that are occurring in the body especially at molecular and cellular levels. It can show the disease in the early stages. Other kinds of medical imaging are ultrasound imaging, CT and magnetic resonance imaging. The best feature of all these imaging systems is they function without ionizing radiation. Visit here https://www.alliedbusiness.co.in/ to know more about the medical imaging systems.
Advanced watermarking technique to improve medical images’ securityTELKOMNIKA JOURNAL
Advances in imaging technology have made medical images become one of the important
sources for information in supporting accurate diagnoses and treatment decisions by doctors for their
patients. However, the vulnerability of medical images’ security is high. The images can be easily
‘attacked’, which altered their information that can lead to incorrect diagnoses or treatment. In order to
make the images less vulnerable from outside attacks, this study proposes to secure them by advancing
the watermarking using dual-layer fragile technique. It is expected that this dual-layer fragile watermarking
will guarantee the integrity, authenticity, and confidentiality of patient’s and any other important information
and also the pixel data of the medical images. The work in this study implements two LSBs of image where
the role of the first LSB is as a tamper detector, and the second LSB is used to store patient’s and any
other important information. Medical images of four deadliest diseases in Indonesia were used to test
the proposed watermarking technique. Results from the conducted tests show that the proposed technique
able to generate a watermarked image that has no noticeable changes compared to its original image, with
PSNR value more than 44 dB and SSIM value of almost 1, where the tamper detector can correctly detect
and localize any tampering on the watermarked image. Furthermore, the proposed technique has shown to
have a higher level of security on medical images, compared to DICOM standard and standard
watermarking method.
This document provides an overview of medical devices, including definitions, classifications, examples of different types of devices used for diagnosis, treatment and monitoring, and the theoretical principles underlying their functions. It discusses the purpose of medical biophysics education which is to ensure safe and effective use of devices through understanding their physics and applying protocols to minimize risks to patients and users. Competencies for medical device users are outlined, such as understanding device functions, limitations, quality control, and adhering to relevant regulations.
Robotics is the Engineering science and technology of robots, and their design, manufacture, application, and Structural disposition.
Robotics is related to Electronics, Mechanics, and Software.
The term “Robotics” was coined by Isaac Asimov in his 1941 science fiction Short story “Liar”.
The document summarizes a presentation on semantic web activities in Russia. It discusses key players working in semantics and linked open data in Russia, including the W3C Russian office hosted by HSE. Products and projects presented include Eventos, OntosLive, OntoQUAD, and RIA Novosti's use of linked open data. Current activities focus on transforming data sources into linked open data, text understanding through NLP, and the RDFace editor. The presentation envisions expanding linked open data in Russia through applications on smart devices, collective intelligence, and improving the visibility of Russian universities and science.
Most research in Russian universities is performed by small groups of software enthusiasts, though interest has grown since 2013. Popular areas include natural language processing, ontology engineering, and linked data. Many projects are run by students and young researchers. Examples from NRU ITMO include linked learning projects, an ontology visualization tool, IoT projects, and open government data integration. Potential future areas include open government data, linked data in education, and digital libraries. The annual Russian Conference on Knowledge Engineering and Semantic Web grows each year and aims to include more international participation.
This document summarizes a study that evaluated the performance of a wearable sensor called the BioHarness 3.0 (BH3) in measuring heart rate (HR) and breathing rate (BR). Twenty participants had their HR measured at rest using the BH3 and an ECG (the gold standard method). Four participants also did a walking test on a treadmill. For BR, five participants breathed at controlled rates while wearing the BH3 and a respiratory belt. The study found that the BH3 provided accurate HR values during rest (±2.1 bpm) and movement (±2.8 bpm), without needing additional processing. However, additional processing of the BH3's raw breathing waveform data improved the
This document discusses the various applications of information technology in veterinary science. It begins by introducing veterinary informatics and some key areas where IT is applied, including disease surveillance using geo-informatics, disease diagnosis using various imaging technologies, artificial intelligence in health management, and data analysis. It then discusses veterinary hospital management software and its features and advantages. Next, it covers dairy herd management software and its benefits. Finally, it briefly mentions telemedicine and its role in veterinary care.
Biomedical engineering is an interdisciplinary field that applies engineering principles to medicine. It involves developing medical devices, imaging systems, prosthetics, and more to improve healthcare. In India, biomedical engineering degrees are offered at institutions like IITs, NITs, and private colleges. Masters and PhD programs are available mainly at IITs. Research areas include tissue engineering, biomechanics, imaging, and more. Biomedical engineers work in companies developing medical technologies and at research centers. The field has opportunities both in India and abroad.
Effective use of personal health records to support emergency servicesAlba Morales
This document describes a methodology for using personal health records to support emergency services while protecting privacy. The researchers aim to identify individuals needing special assistance during emergencies and determine why assistance is needed. Their approach classifies health record attributes, filters sensitive data, and uses a knowledge base to categorize conditions and derive disability types. In a fire evacuation scenario case study, their system correctly identified 91% of individuals needing assistance and determined assistance types with high precision. The researchers conclude their approach can help emergency services while avoiding disclosure of private health information.
WBSN based safe lifestyle: a case study of heartrate monitoring system IJECEIAES
A Heart is the vital organ of the body. According to the “world health statistics 2017” by WHO, about 460,000 people die due to fatal heart attacks every year. To reduce the death rate due to fatal heart attacks and malfunctioning of the cardiovascular system, this paper proposed a Wireless Body Sensor Network (WBSN) based, portable, easily affordable, miniatured, accurate “Heartrate Monitoring System (HMS)”. HMS can be used to regularly examine the cardiac condition at home or hospital to avoid or early detection of any serious condition. Heartrate Monitoring Algorithm (HMA) was designed to observe the spread heartbeat spectrum and worked at the backend of HMS. A case study was performed for forty healthy young subjects. Each subject data was computed for 푠푢푏 ̅̅̅̅̅ − 3푆 푑 < 푠푢푏 < 푠푢푏 ̅̅̅̅̅ + 3푆 . All subjects’ 99% data lie in the custom range. The result produced by HMS was the same as the previous medical record of subjects.
IRJET- The Essence of the Surgical Navigation System using Artificial Int...IRJET Journal
The document discusses the potential for a surgical navigation system that uses artificial intelligence and augmented reality to help doctors perform surgeries. Such a system would use image processing and tracking of surgical instruments to overlay virtual images onto the real world view of the surgery. The authors argue that AI could help diagnose diseases, plan optimal surgical procedures, and provide navigation assistance during operations to improve precision and outcomes.
An Intelligent Sensing System for Sleep Motion and Stage Analysistoukaigi
This document describes an intelligent sensing system developed to analyze sleep motion and stages. The system uses a thermal infrared camera to detect body movement, a 3-electrode EEG device to determine sleep stages, and analysis algorithms. It provides 3 main types of results: (1) descriptions of sleep stages using Markov models and state duration statistics, (2) movement graphs over time, and (3) relationships between detected stages and motion, such as more movement occurring during transitions between stages. An empirical study with 2 subjects captured sensory recordings over multiple nights, demonstrating the system's ability to provide these results and its potential for in-home sleep monitoring.
Implementation of electronic stethoscope for online remote monitoring with mo...journalBEEI
The document describes the implementation of an electronic stethoscope integrated with a mobile application for online remote patient monitoring. Key points:
1. The system includes an electronic stethoscope that converts heart and lung sounds to electrical signals, and a mobile app called "Steder" that records the signals, converts them to MP3 format, and sends them to a cloud server.
2. The stethoscope hardware uses a condenser mic, amplifier, and filter to capture sounds from 20-1000Hz. The app allows sounds to be stored, played back, and sent to doctors for analysis.
3. Testing showed the hardware and app worked as intended, with sounds accurately recorded and transmitted to the cloud server
A Review Paper on Design of GPS and GSM Based Intelligent Ambulance MonitoringIJERA Editor
Proposed paper presents design of such a monitoring system for emergency patient transportation employing ARM 7 processor module. The system will be useful for monitoring ambulance location using Google map. It also include biomedical sensors to monitor heart bit rate and temperature of patient through SMS. The front end application at the monitoring system is developed using visual basic software in Personal Computers. It can display location of ambulance and status of heart bit rate and temperature of patient. After receiving SMS hospital can prepare their staff for proper treatment of coming patient.
Artificial intelligence in orthopaedicsSaswata Datta
This document discusses the history and applications of artificial intelligence in orthopaedics. It begins with definitions of AI and provides examples of early AI pioneers. It then outlines the current and potential future uses of AI in orthopaedics, including for analyzing medical images, assisting with surgical navigation and procedures, and evaluating treatments. While AI may replace some tasks, the document argues that AI will likely change and enhance the role of orthopaedic surgeons rather than replace them entirely. It closes by acknowledging challenges with AI and calling for maintaining the important doctor-patient relationship.
This document discusses the growing use of wearable sensor technology in sports medicine. It describes various types of movement sensors like pedometers, accelerometers, gyroscopes, and GPS that can track athlete movements, workloads, and positions. It also discusses physiologic sensors like heart rate monitors and temperature sensors. The document concludes that wearable sensors provide a method to monitor real-time physiology and movement to optimize performance, detect injury risks, and design efficient training programs.
introduction to biomedical engineering, Applications of biomedical engineeringJayachandran T
Bio-medical engineering applies engineering principles and design concepts to medicine and biology. It combines engineering and medical sciences to advance healthcare, including through developing diagnostic and therapeutic medical equipment, devices, and technologies. Some examples include designing artificial organs and prosthetics, maintaining medical equipment, and researching the engineering of biological systems. Bio-medical engineers also evaluate medical technology, train clinicians on equipment use, and publish research findings.
Computer systems and the internet have greatly improved healthcare in several ways:
1. Electronic medical records allow doctors to access complete patient histories instantly and share information between hospitals. Computerized prescriptions reduce errors.
2. Diagnostic tools like CT scans, MRIs, and ultrasounds can identify medical issues much faster and more accurately than before. Monitoring equipment keeps close tabs on patients' vital signs.
3. Treatments are also enhanced through robotics in surgery, pacemakers, ventilators, and prosthetics that can mimic natural limb movement. Online support groups and research databases help patients.
4. However, self-diagnosis online risks missing issues, and purchasing medications without a prescription
The information technology played an important role in information
and knowledge dissemination in the last decade. The usage of IT to
transfer information and knowledge in the animal health care domain
using expert systems is one of the areas investigated by many
institutions. The current era is witnessing a vast development in all
fields of animal health care. Therefore there is a need for an
unconventional method to transfer the knowledge of experts in this
domain to the general public of livestock holders, especially that the
number of experts in new technologies is lesser than their demand in a
certain domain. The transfer of knowledge from veterinary consultants
& scientists to livestock holders represents a bottleneck for the
development of animal health care in any country. Expert systems are
simply computer software programs that mimic the behaviour of human
experts. They are one of the successful applications of the Artificial
Intelligence field, a branch in Computer Science that investigates how
to make the machine think like human or do tasks that humans do.
Expert Systems are very helpful to ensure an effective and nationally
coordinated approach in response to emergency incidents and in routine
bio-security activities. Such systems enable better management of the
information and resources used to manage animal’s diseases and
emergency responses to incursions.
The heart is a vital organ that serves to pump blood to the whole body. A heart rate can be used as a healthy body parameter conditions. Growing evidence suggests that IT-based health records play essential role to drive medical revolution especially on data storage and processing. The heart rate measurement (HRM) process usually involves wearable sensor devices to record patient’s data. This data is recorded to help the doctors to analyze and provide a better diagnose in order to determine the best treatment for the patients. Connecting the sensor system through a wireless network to a cloud server will enable the doctor to monitor remotely. This paper presents fit-NES wearable bracelet, an alternative method for integrating a HR measurement device using optical based pulse sensor and Bluetooth-based communication module. This paper is also present the benchmarking of proposed system with several various commercial HR measurement devices.
There are a number of scopes for IoT in order to make a difference in lives of patients. The devices can capture as well as monitor related data regarding patient and allows the providers to obtain the insights without bringing the patients visiting. The procedure can assist the patient results as well as preventing the possible communications for the process that involves risk. However, lack of electronic health record (EHR) system integration is one of the major issues faced while using IoT in healthcare. Some of the EHR systems allow the patients importing data into the record. However, it remains limited to a few dominant where the EHR players as well as leaves providers unspecific of the processing data that can be helpful for the organization to use the process. The challenges for interoperability in order to keep data in distinctive medical devices depend on the purpose and ordering physician. by Vishal Dineshkumar Soni 2018. An IoT Based Patient Health Monitoring System. International Journal on Integrated Education. 1, 1 (Dec. 2018), 43-48. DOI:https://doi.org/10.31149/ijie.v1i1.481. https://journals.researchparks.org/index.php/IJIE/article/view/481/458 https://journals.researchparks.org/index.php/IJIE/article/view/481
In nuclear medicine, molecular imaging is applied. It employs various methods to picture biological processes that are reacting in the cells. Radiopharmaceuticals are used in molecular imaging. It is used in small quantities called radioactive markers. It offers detailed information about the biological processes that are occurring in the body especially at molecular and cellular levels. It can show the disease in the early stages. Other kinds of medical imaging are ultrasound imaging, CT and magnetic resonance imaging. The best feature of all these imaging systems is they function without ionizing radiation. Visit here https://www.alliedbusiness.co.in/ to know more about the medical imaging systems.
Advanced watermarking technique to improve medical images’ securityTELKOMNIKA JOURNAL
Advances in imaging technology have made medical images become one of the important
sources for information in supporting accurate diagnoses and treatment decisions by doctors for their
patients. However, the vulnerability of medical images’ security is high. The images can be easily
‘attacked’, which altered their information that can lead to incorrect diagnoses or treatment. In order to
make the images less vulnerable from outside attacks, this study proposes to secure them by advancing
the watermarking using dual-layer fragile technique. It is expected that this dual-layer fragile watermarking
will guarantee the integrity, authenticity, and confidentiality of patient’s and any other important information
and also the pixel data of the medical images. The work in this study implements two LSBs of image where
the role of the first LSB is as a tamper detector, and the second LSB is used to store patient’s and any
other important information. Medical images of four deadliest diseases in Indonesia were used to test
the proposed watermarking technique. Results from the conducted tests show that the proposed technique
able to generate a watermarked image that has no noticeable changes compared to its original image, with
PSNR value more than 44 dB and SSIM value of almost 1, where the tamper detector can correctly detect
and localize any tampering on the watermarked image. Furthermore, the proposed technique has shown to
have a higher level of security on medical images, compared to DICOM standard and standard
watermarking method.
This document provides an overview of medical devices, including definitions, classifications, examples of different types of devices used for diagnosis, treatment and monitoring, and the theoretical principles underlying their functions. It discusses the purpose of medical biophysics education which is to ensure safe and effective use of devices through understanding their physics and applying protocols to minimize risks to patients and users. Competencies for medical device users are outlined, such as understanding device functions, limitations, quality control, and adhering to relevant regulations.
Robotics is the Engineering science and technology of robots, and their design, manufacture, application, and Structural disposition.
Robotics is related to Electronics, Mechanics, and Software.
The term “Robotics” was coined by Isaac Asimov in his 1941 science fiction Short story “Liar”.
The document summarizes a presentation on semantic web activities in Russia. It discusses key players working in semantics and linked open data in Russia, including the W3C Russian office hosted by HSE. Products and projects presented include Eventos, OntosLive, OntoQUAD, and RIA Novosti's use of linked open data. Current activities focus on transforming data sources into linked open data, text understanding through NLP, and the RDFace editor. The presentation envisions expanding linked open data in Russia through applications on smart devices, collective intelligence, and improving the visibility of Russian universities and science.
Most research in Russian universities is performed by small groups of software enthusiasts, though interest has grown since 2013. Popular areas include natural language processing, ontology engineering, and linked data. Many projects are run by students and young researchers. Examples from NRU ITMO include linked learning projects, an ontology visualization tool, IoT projects, and open government data integration. Potential future areas include open government data, linked data in education, and digital libraries. The annual Russian Conference on Knowledge Engineering and Semantic Web grows each year and aims to include more international participation.
STI International is a non-profit organization that aims to address challenges of communication and collaboration at large scales through semantic technologies. It has 11 partner organizations, 15 members, and several fellows. STI holds biennial Semantic Summits to discuss strategic issues and directions for semantic technology. The 2013 summit agenda shows sessions on topics like the semantic web in Russia, data science curriculum, and future funding for semantics in Europe.
The document describes OntoQuad, a native RDF database management system for semantic web data. It provides benchmarks showing OntoQuad outperforming other RDF stores on query speed for the Berlin SPARQL Benchmark. It also describes running OntoQuad on various platforms including Android and Raspberry Pi, and examples of semantic datasets powered by OntoQuad.
This document outlines funding opportunities for various ICT-related challenges, research areas, and activities under Horizon2020. It provides details on funding levels, budgets, objectives, and types of projects (e.g. collaborative projects, coordination and support actions) for areas such as future internet, big data, language technologies, internet of things, and more. The overall goal is to support innovation and advancements in key ICT domains through research and development projects.
The document discusses the DIADEM data extraction methodology. It describes DIADEM as a domain-centric intelligent automated methodology for extracting structured data from unstructured documents. The methodology was developed by a research group at the University of Oxford and Vienna University of Technology led by Georg Gottlob and Tim Furche.
The document provides an overview of KAIST CSE (Computer Science and Engineering department). It discusses the establishment and history of KAIST CSE, including its merger with other departments. It outlines the department's core values and goals of becoming a top 10 computer science department globally and a competitive, specialized, and evolving department. It also provides statistics on faculty, students, research areas, rankings, and centers within KAIST CSE.
Ecis final paper-june2017_two way architecture between iot sensors and cloud ...Oliver Neuland
Improving health care with IoT - Research into a weight monitoring bed - ECIS 2017 paper.
Resulting from smart furniture applications research project in Germany, Oliver Neuland and partners from AUT developed a smart bed concept which utilizes weight monitoring for AAL and elderly care. Initially strategies were applied to find meaningful use cases, later a prototype was developed. Here a paper presented during ECIS in Portugal which describes the architecture of the prototype.
The document summarizes the development of ubiquitous healthcare (U-Healthcare) and a proposed elderly-friendly healthcare smart home system in Korea. It discusses the origins of concepts like house calls, telemedicine, and how U-Healthcare expanded medical services anywhere and anytime. It then describes a proposed smart home model that provides integrated health management for elderly residents through online and offline services linked across living spaces, community spaces, and medical facilities. The model aims to develop a low-cost system centered around residents' needs rather than diseases alone. Ideas are generated using design thinking methods and an example clinical decision support system is presented using various health sensors and feedback.
Development of Elderly-friendly Healthcare Smart Home SystemSNUCHIC
The document summarizes the development of a healthcare smart home system for elderly community residents in Korea. Key points include:
1) Design methods like IDEO cards were used to develop an elderly-friendly interface and clinical decision support system based on biosignal feedback.
2) Sensors were integrated throughout homes and community spaces to monitor things like blood pressure, glucose, pulmonary function, and more.
3) A gateway device guided measurements and displayed educational information. Data was analyzed on a server and doctors were consulted as needed.
4) The system aimed to provide a low-cost, resident-centric model of remote healthcare monitoring and management for the elderly within their residential community.
Our classification technique uses a deep CNN to classify skin lesions. An image is warped through the CNN architecture into a probability distribution over clinical skin disease classes. The CNN was pretrained on a large generic image dataset and fine-tuned on a dataset of over 129,000 skin lesions spanning 2,032 diseases. Data integration from multiple sources is key to future digital medicine, but challenges include data quality, availability, and privacy. Techniques like distributed learning models and homomorphic encryption can help address privacy concerns while enabling large-scale data sharing and analysis.
(1) The system segments histopathology images into epithelial and stromal regions and identifies nuclei.
(2) It constructs a rich set of quantitative features describing the relationships between different image objects.
(3) Using the features, a predictive model is built from images of patients with known 5-year survival outcomes. This model can then predict survival probabilities for new unlabeled images.
IRJET- Health Monitoring System using ArduinoIRJET Journal
This document describes a health monitoring system using Arduino that monitors patients' pulse rate, vital signs, and saline level. Sensors are used to collect this medical data, which is then sent to the cloud for storage and access by doctors. The system is meant to continuously monitor patients and alert doctors if any parameters exceed thresholds, to save lives in emergencies or when doctors are not present. It discusses how technologies like the Internet of Things and wireless sensors can help create remote health monitoring systems.
The document presents a proposed healthcare monitoring system using machine learning techniques to improve diagnosis of heart disease in an Internet of Medical Things (IoMT) cloud environment. It introduces a modified salp swarm optimization algorithm (MSSO) combined with an adaptive neuro-fuzzy inference system (ANFIS) called MSSO-ANFIS. MSSO-ANFIS aims to improve ANFIS prediction accuracy by optimizing its learning parameters. Simulation results show MSSO-ANFIS achieves higher accuracy, precision, and performance than other methods for predicting heart disease risk based on patient data like blood pressure, age, sex, etc.
An internet of things-based automatic brain tumor detection systemIJEECSIAES
Due to the advances in information and communication technologies, the usage of the internet of things (IoT) has reached an evolutionary process in the development of the modern health care environment. In the recent human health care analysis system, the amount of brain tumor patients has increased severely and placed in the 10th position of the leading cause of death. Previous state-of-the-art techniques based on magnetic resonance imaging (MRI) faces challenges in brain tumor detection as it requires accurate image segmentation. A wide variety of algorithms were developed earlier to classify MRI images which are computationally very complex and expensive. In this paper, a cost-effective stochastic method for the automatic detection of brain tumors using the IoT is proposed. The proposed system uses the physical activities of the brain to detect brain tumors. To track the daily brain activities, a portable wrist band named Mi Band 2, temperature, and blood pressure monitoring sensors embedded with Arduino-Uno are used and the system achieved an accuracy of 99.3%. Experimental results show the effectiveness of the designed method in detecting brain tumors automatically and produce better accuracy in comparison to previous approaches.
An internet of things-based automatic brain tumor detection systemnooriasukmaningtyas
Due to the advances in information and communication technologies, the usage of the internet of things (IoT) has reached an evolutionary process in the development of the modern health care environment. In the recent human health care analysis system, the amount of brain tumor patients has increased severely and placed in the 10th position of the leading cause of death. Previous state-of-the-art techniques based on magnetic resonance imaging (MRI) faces challenges in brain tumor detection as it requires accurate image segmentation. A wide variety of algorithms were developed earlier to classify MRI images which are computationally very complex and expensive. In this paper, a cost-effective stochastic method for the automatic detection of brain tumors using the IoT is proposed. The proposed system uses the physical activities of the brain to detect brain tumors. To track the daily brain activities, a portable wrist band named Mi Band 2, temperature, and blood pressure monitoring sensors embedded with Arduino-Uno are used and the system achieved an accuracy of 99.3%. Experimental results show the effectiveness of the designed method in detecting brain tumors automatically and produce better accuracy in comparison to previous approaches.
The document discusses public health surveillance systems. It covers the requirements of organized surveillance including data collection, analysis, interpretation, dissemination, and linking to public health action. The potential functions of surveillance systems are described as describing and monitoring health events, setting priorities, planning assistance, and evaluating public health interventions and programs. Potential ethical issues involve privacy concerns regarding the collection and use of surveillance and registry data. Applications in public health investigations include monitoring health events, following trends, and supporting factors analysis.
This document outlines Svitlana Volkova's thesis on entity extraction and animal disease-related event recognition from web documents. It provides background on existing animal disease monitoring systems, both manually supported web interfaces and automated web services. It then discusses related work on text categorization, entity extraction, relation extraction, and event recognition. The document outlines Volkova's proposed framework for epidemiological analytics, including the main system components of data collection, data sharing, search, data analysis, and visualization. It provides details on disease-related document classification, domain-specific entity extraction, and ontology-based entity extraction. The goal is to build a system that can automatically extract information on animal disease outbreaks from unstructured web data.
E-HEALTH BIOSENSOR PLATFORM FOR NONINVASIVE HEALTH MONITORING FOR THE ELDERLY...ijbesjournal
New technologies in the field of tele-health using biosensor systems for non-invasive vital signs monitoring of patients, especially elderly people who need long-term care, and marginalized areas with hard to reach health care services are emerging. A study involving a self-care approach within the cardiac domain, where late detection increases the likelihood of patient disability or of premature death is proposed. In the
study the application of e-health biosensors platform in medical services is experimented. The study resulted into the synthesis of vital signs from various body positions with biosensors that does not require a full coupled system. A model for the prevention of cardiovascular disease management based on noninvasive personal health monitoring systems with easy access for everybody, at any time or location is designed. A personal vital sign system such as ECG sensor which contain the functionality, allows recording anywhere and at any time a diagnostic quality ECG and analyzing it “on-board” by comparing it to a reference ECG, is modelled. The model called Mobile Health for the Elderly Persons (MOHELP)
which relies on with application in estimation and control of boolean processes based on noisy and incomplete measurements is designed. This enabled a reliable recommendation from a digital artificial intelligence-based diagnosis, which can support an elderly person to take timely and correct decisions upon his (her) health status. In a case of urgency, the assistant puts the elderly person in a contact with
healthcare providers. The signal pattern sensitivity related to sensors placement is one of the issues this study addressed using e-sensor platform. Sensors displacement errors have a direct impact on the medical diagnosis, especially if the diagnostic procedure is automated. The study resulted into the formulation of a methodology for e-Health Sensor Platform, in software architecture terms, that permits use of system
biosensors to adapt to the user-specific context for self-healthcare
This document summarizes an intelligent mobile health monitoring system (IMHMS) that collects biomedical and environmental data from sensors, analyzes the data using an intelligent medical server, and provides medical feedback to patients through their mobile devices. The system aims to improve healthcare access and provide personalized health monitoring anywhere through integration of biosensors, wireless networks, and mobile computing. It discusses related works in mobile health monitoring and care. Key aspects of IMHMS include its system architecture, characteristics like long-term ambulatory monitoring and real-time updates, impact on healthcare research through data mining, and future directions like developing the intelligent medical server.
This document discusses research challenges in signal processing, communication, and computing aspects of the Internet-of-Things (IoT). It focuses on human-in-loop cyber-physical systems and developing an integrated platform for intelligent infrastructure that connects people, sensors, social media, and traditional monitoring systems. Key challenges discussed include context discovery from physical sensors and human data sources, as well as challenges in signal processing, communication, and computing for IoT applications. Example applications discussed are healthcare monitoring using mobile phones and activity detection.
Amit Sheth, Pramod Anantharam, Krishnaprasad Thirunarayan, "kHealth: Proactive Personalized Actionable Information for Better Healthcare", Workshop on Personal Data Analytics in the Internet of Things at VLDB2014, Hangzhou, China, September 5, 2014.
Accompanying Video: http://youtu.be/pqcbwGYHPuc
Paper: http://www.knoesis.org/library/resource.php?id=2008
Augmented Personalized Health: using AI techniques on semantically integrated...Amit Sheth
Keynote @ 2018 AAAI Joint Workshop on Health Intelligence (W3PHIAI 2018), 2 February 2018, New Orleans, LA [Video: https://youtu.be/GujvoWRa0O8]
Related article: https://ieeexplore.ieee.org/document/8355891/
Abstract
Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease-focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven. While the ability to create and capture data is already here, the upcoming innovations will be in converting this big data into smart data through contextual and personalized processing such that patients and clinicians can make better decisions and take timely actions for augmented personalized health. In this talk, we will discuss how use of AI techniques on semantically integrated patient-generated health data (PGHD), environmental data, clinical data, and public social data is exploited to achieve a range of augmented health management strategies that include self-monitoring, self-appraisal, self-management, intervention, and Disease Progression Tracking and Prediction. We will review examples and outcomes from a number of applications, some involving patient evaluations, including asthma in children, bariatric surgery/obesity, mental health/depression, that are part of the Kno.e.sis kHealth personalized digital health initiative.
Background: Background: http://bit.ly/k-APH, http://bit.ly/kAsthma, http://j.mp/PARCtalk
Phoenix-Wearable Sensors for Monitoring Health and Wellness.pdfquochuynhtan1
The Catholic University of America's HomeCare & Telerehabilitation Technology Center (HCTR) aims to research, design, and test wearable sensor and telemonitoring technologies to facilitate health, wellness, and independence. Current HCTR projects include developing wearable inertial and physiological sensors integrated into smart clothing to monitor daily activities and health status. Algorithms will analyze the sensor data for early health changes detection. A portable wireless electroencephalogram system is also being developed to assess cognition, mental health, and diver training/performance using brain signal processing and data visualization. The goal is to implement these technologies on smartphones or smart clothing for remote health monitoring and evaluation.
This document describes a personal medical assistant system consisting of a wearable sensor bracelet/armband and smartphone app with cloud support. The sensors would collect vital signs like heart rate, blood pressure, oxygen levels, blood sugar, and the smartphone would track location and activity. Data is exchanged with an automated system for medical decision support. The system would be targeted at everyday fitness/health, professional sports, and diabetics. It integrates with medical records and cloud services and sends alerts if readings exceed limits, storing this in the user's history. The goal is to develop an intelligent biosensor platform and diagnostic engine that can correlate data from multiple sensors during movement.
Will Yu of Lumiata provides an overview of using real-time big analytics with ever-learning graph combining hundreds of healthcare data sets. Presented at YTH Live 2014 plenary session "Mapping Big Data, Infographics and other Good Stuff."
Similar to Summit2013 ho-jin choi - summit2013 (20)
The document discusses semantic technologies and their tipping points. It provides examples of past technologies that reached a tipping point such as databases, client-server computing, the web, and cloud computing. It examines the potential tipping points for semantic technologies and the semantic web, noting they provide higher-order functionality and productivity but have not reached a tipping point yet. Finally, it addresses big data challenges around scale and integration and the role of semantic technologies in providing meaningful solutions.
The document discusses the dynamic web and current approaches for web-based communication and interaction. It describes how events and actions are currently handled through technologies like complex event processing. It proposes a more reactive approach using event-condition-action rules and integrating this with semantic technologies. Finally, it presents a "layer cake" model for the dynamic web with different levels of abstraction.
The document discusses using usage analysis to improve ontology engineering. It describes analyzing query logs over datasets like DBpedia to identify frequently queried triples and patterns. This can reveal missing or inconsistent data and suggest new links between entities. The analysis helps increase data quality and acquire new knowledge that benefits both the dataset and Web of Data as a whole. While complete automation may not be needed, supporting usage analysis and endpoint access allows publishers to play a role in maintaining datasets and the Web of Data.
The document proposes applying Linked Data principles to services and data streams. It suggests representing service inputs and outputs as Linked Data by encoding parameters in URIs and returning RDF data. For data streams, it recommends using HTTP as an access protocol and streaming RDF triples over an open HTTP connection. This would allow services and streams to be easily integrated and linked with other Linked Data on the web.
The document discusses services and the web of data from an engineering perspective. It proposes that as linked data applications increase in complexity, there will need to be increased reuse of pre-existing solutions and components offered as services. Problem-solving methods research focused on decoupling problem-solving knowledge from domains to enable reuse. Infrastructure is needed to support systematically sharing and finding reusable functionality, including through the use of semantic technologies and problem-solving methods. Challenges include balancing overhead and performance with reuse and genericity.
The document discusses data integration challenges at large Fortune 100 companies. It notes that these companies typically have around 10,000 information systems and databases, with hundreds added each year. Data integration accounts for around 40% of software project costs due to the need to combine data from thousands of source databases across various business units. The conclusion is that every large organization depends critically on effective data and data integration to support their complex, interconnected information ecosystems.
1. The future of Semantic Technologies lies not in the current Semantic Web technology stack but in the underlying principles, such as making domain knowledge editable, shareable and linkable.
2. There are still many exciting topics for the future, such as pushing the boundaries of complex information processing in databases and using web-like data integration to tackle very large-scale data integration problems for entire enterprises or scientific fields.
This document discusses using visual analytics techniques on linked data. It begins by motivating the combination of these fields by noting that while linked data services excel at data access, they lack support for complex analytical scenarios. It then provides examples of how visual analytics has been used in other domains like analyzing financial data, patent trends, and simulating biological processes. Finally, it outlines how visual analytics could be applied to linked data, including aggregating and filtering data, implementing analytical workflows, and using visualization techniques to enable discovery and presentation of insights to domain experts. The goal would be supporting collaborative analytical tasks on a global scale.
1) Producing life sciences linked open data presents challenges as biologists want to publish and control their data but providing query and analysis services is expensive. They need technical assistance and funding support.
2) Consuming linked data in life sciences means connecting data to existing standards like pathways and proteins. Data analysis, mining, crawling and reasoning services are needed but expensive for individual database owners.
3) Scalability issues arise when reasoning over complex ontologies like BioPAX Level 3 with large datasets, as state-of-the-art reasoners cannot handle inconsistencies or provide query endpoints for such data.
The document discusses building semantic web applications using linked data. It describes typical applications, current approaches to supporting applications over linked data using representative architectures and crawling patterns. The document argues that semantics can help by providing SDKs underpinned by datasets and ontologies, supporting collaborative development, and using common front ends and application descriptions. Finally, it presents MicroWSMO and WSMO-Lite as ways to describe minimal service models and service lifecycles for semantic web applications.
Shortipedia is a website that collects assertions from various sources on the semantic web and displays them in an easy to understand format. It finds information about requested topics from Wikipedia, SameAs.org, and Sindice. Users can bind linked entities, see data from related entities, add their own assertions, and integrate additional data. Key lessons learned include that semantic web data can be noisy, hard to understand, and labels are unreliable. Representing diverse knowledge and deciding semantics is also challenging.
This document discusses issues surrounding privacy and data integration. It explores arguments for reduced privacy protections, such as the idea that individuals have zero privacy anyway and companies should be allowed to freely use customer data to enable innovation. However, others argue that a post-privacy society where all data is freely shared may not be desirable. The document examines stakeholders' perspectives and wider issues regarding data ownership and business models in a world with integrated data.
This document discusses diversity and the semantic web. It notes that the loss of serendipity, myths of numerical methods, and fragmentation/polarization are challenges. Policy and decision making processes can also be impacted. Understanding the emergence and impact of biases from collaborative content creation is challenging. Models are needed to represent provenance, trust, quality and predict biases. Algorithms also need to be designed to account for diversity, make biases explicit, and augment tools like ranking, filtering and recommendation to consider both producer and consumer biases.
This document summarizes a session on social semantics that included four presentations:
1. Mark Greaves discussed crowdsourcing semantics and whether crowdsourced knowledge acquisition via semantic web is likely to succeed.
2. Denny Vrandečić, Elena Simperl, and Rudi Studer presented on diversity and the semantic web.
3. Andreas Harth's presentation was titled "Beyond Privacy".
4. Denny Vrandečić also presented on Shortipedia.
The document discusses various ways to monetize the semantic web, including:
1) Providing metadata as a free asset to increase visibility and selling related products/services.
2) Offering basic entity data for free and charging for richer data through a "freemium" model.
3) Allowing free data dumps but charging for powerful paid features like advanced querying.
4) Outsourcing expensive data curation and aggregation tasks to create added value services.
Monetization raises issues about incentivizing contributions while allowing open collaboration.
The document discusses the limits of Linked Open Data (LOD) for industry solutions and proposes an extended approach. It argues that LOD is limited by its reliance on standardized RDF data and URIs, which do not apply well to distributed corporate data silos. It proposes extending LOD by enabling semantic integration of any data, dynamic links beyond RDF and URIs, linking data to actions, and scalable persistence without data migration. The document advocates a bottom-up approach of automatically deriving ontologies from data models rather than a top-down imposition of ontologies. It identifies potential research areas like SPARQL endpoints for heterogeneous data and automatically performing and consuming ontologies.
The document discusses the role of ontologies in linked data. It notes that while semantic web ontologies have been widely applied, linked data has grown rapidly using lightweight or no ontologies. However, ontologies could still provide benefits to linked data by helping integrate and reason over heterogeneous linked data sources. Open issues remain around how to best reuse and modularize ontologies for different linked data applications and domains.
The document discusses differences between databases (DB) and Resource Description Framework (RDF) in how they handle correlations in data. It notes that real data is highly correlated but databases assume attribute independence, leading to suboptimal query plans. When querying RDF data, SPARQL queries often result in many self-joins that database query optimizers cannot optimize well as they do not understand the correlations. The document proposes techniques for RDF engines to better handle correlations such as interleaving optimization and execution, partial path indexing, and graph "cracking".
This document summarizes a presentation given by Prof. Dr. Christian Bizer on global data integration and mining. It discusses the topology of the web of data, how global data integration can be achieved through a pay-as-you-go approach of publishing identity and vocabulary links, and how this enables global data mining. Examples of linked data uptake in different domains like government and libraries are also provided.
The document discusses digital worlds and applications at both the enterprise and national scales in the United States healthcare system. It notes the massive scale of healthcare data sources, including hundreds of thousands of healthcare offices and databases containing information on hundreds of millions of patients. The critical importance of making sense of this vast amount of heterogeneous healthcare data to improve human lives and health outcomes is also emphasized.
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Rasamanikya is a excellent preparation in the field of Rasashastra, it is used in various Kushtha Roga, Shwasa, Vicharchika, Bhagandara, Vatarakta, and Phiranga Roga. In this article Preparation& Comparative analytical profile for both Formulationon i.e Rasamanikya prepared by Kushmanda swarasa & Churnodhaka Shodita Haratala. The study aims to provide insights into the comparative efficacy and analytical aspects of these formulations for enhanced therapeutic outcomes.
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Osteoporosis - Definition , Evaluation and Management .pdfJim Jacob Roy
Osteoporosis is an increasing cause of morbidity among the elderly.
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Muktapishti is a traditional Ayurvedic preparation made from Shoditha Mukta (Purified Pearl), is believed to help regulate thyroid function and reduce symptoms of hyperthyroidism due to its cooling and balancing properties. Clinical evidence on its efficacy remains limited, necessitating further research to validate its therapeutic benefits.
Here is the updated list of Top Best Ayurvedic medicine for Gas and Indigestion and those are Gas-O-Go Syp for Dyspepsia | Lavizyme Syrup for Acidity | Yumzyme Hepatoprotective Capsules etc
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...Oleg Kshivets
Overall life span (LS) was 1671.7±1721.6 days and cumulative 5YS reached 62.4%, 10 years – 50.4%, 20 years – 44.6%. 94 LCP lived more than 5 years without cancer (LS=2958.6±1723.6 days), 22 – more than 10 years (LS=5571±1841.8 days). 67 LCP died because of LC (LS=471.9±344 days). AT significantly improved 5YS (68% vs. 53.7%) (P=0.028 by log-rank test). Cox modeling displayed that 5YS of LCP significantly depended on: N0-N12, T3-4, blood cell circuit, cell ratio factors (ratio between cancer cells-CC and blood cells subpopulations), LC cell dynamics, recalcification time, heparin tolerance, prothrombin index, protein, AT, procedure type (P=0.000-0.031). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and N0-12 (rank=1), thrombocytes/CC (rank=2), segmented neutrophils/CC (3), eosinophils/CC (4), erythrocytes/CC (5), healthy cells/CC (6), lymphocytes/CC (7), stick neutrophils/CC (8), leucocytes/CC (9), monocytes/CC (10). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
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Explore the benefits of combining Ayurveda with conventional Parkinson's treatments. Learn how a holistic approach can manage symptoms, enhance well-being, and balance body energies. Discover the steps to safely integrate Ayurvedic practices into your Parkinson’s care plan, including expert guidance on diet, herbal remedies, and lifestyle modifications.
1. 18 July 2013
Ho-Jin Choi
Dept. of Computer Science, KAIST
Systems Biomedical Informatics Research
Center (SBI-NCRC), SNU College of Medicine
Personalized Context-Aware Health Avatar in
Smart Phone Environment
The 2013 STI Semantic Summit
Suzdal, Russia, July 17-19, 2013
1
2. Outline
SBI-NCRC – A brief introduction
Research Topics
Activity Recognition for Personalized Life-Care
Healthcare Service Framework for Continuous Context
Monitoring
Text Mining for Extracting Knowledge from Web Contents
Personalized Bio and Medical Data Analysis
2
4. SBI-NCRC
NCRC (National Core Research Center)
Government initiative to support interdisciplinary research & education
Since 2004, one or two centers newly selected each year
Funding scale, 2 million USD/year * 6.5 years
Systems Biomedical Informatics (SBI) Research Center
An NCRC established jointly by SNU Hospital and KAIST Computer Science
Born in September 2010
24 professors/researchers participating from 4 organizations
SNUH, KAIST, Ajou University, ETRI
Goals for SBI-NCRC
To define and realize “Digital Self” or “Health Avatar” prescriptive medicine
To integrate clinical information and bio-information using IT
To launch an interdisciplinary program in Biomedical Informatics
To collaborate towards Joint KAIST-SNUH BIT Campus in Inchon area
4
5. 4P Medicine
Preventive medicine
Predictive medicine
Personalized medicine
Participatory medicine
Tests for early detection
Risk evaluation Prevention
Targeted
monitoring
Diagnosis Treatment
Results
monitoring
Caring Diseases Caring Health
5
6. Middleware
Integrative analyses
OCS PACS EMR LIS Seq. Exp. Prot. Tissue CGH
HL-7
DICOM
CDA
LOINC
BSML
MAGE
MIAPE
TMA
?
SNP
HapMap
2DPage
ProtChip
Tissue
MA
BAC
Chip
Phenomic Self Extractor Genomic Self Extractor
Clinical Genomics
BioData Acquisition
Pattern
Recognizer
DNA
Chip
Transformer
XML Binder
DBConnector
HL-7 / CDA Protocols
Hospital
caBIO
EVS caDSR
CRF CDE/CTEP
caCORE
IDE
Foundation Self
Warehouse
유방암
Application
폐암
Application
혈액암
Application
Legacy System
Authentication/Authorization
Interface
자료 수용기
CGI-
gateway
WebServer
XML-Validation
Ontology-Enhancement
Data Indexing
Clinical Trials Knowledge
Base
XML
CGI-gateway
Retrieval
engine
Query
Constructor
Clinical Research
& Clinical Trial KB
Application
Processor
Search engine
Statistical analysis
Visualization
Simulation
Communications
Workflow
Middleware
Ontology Server
Vocabulary Server
Taxonomy Server
Public Bio-DBs
Digital Self
Simulated Self
Individuated Second Self
Foundation Self
Molecular & Cellular Foundations of Self
Ubiquitous Self
Life Logs and Distributed Collaborations
Genomic Self: Translational Bioinformatics
for Genomic Health and Molecular Medicine
Phenomic Self: Data and Measurement driven
Discovery and Understanding of Human Disorders
Physiomic Self: Multi-scale Modeling of Physical and
Physiological Systems of Human Body
Semantic Self: Ontological Representation
and Engineering of Health Avatar
Augmented Self: Multi-modal Assessment and
Treatment to Retain and Enhance Human Performance
Connected Self: Life Logs and Stream-
Type Data Mining for Health Protection
Distributed Self: Customized and Context-aware
Healthcare Service Agents in Smart Phone Environment
7. Teaming
7
Group/Project Title PI’s Major
Group 1
Foundation Self: Molecular and Cellular Foundations
of Self
SNUH, Ajou U.
Project 1-1
Genomic Self: Translational Bioinformatics for Genomic
Health and Molecular Medicine
Psychiatry(1), Surgery(1),
Bioinformatics(1), Statistics(1)
Project 1-2
Phenomic Self: Data and Measurement driven
Discovery and Understanding of Human Disorders
Pathology(2), Bioinformatics(1)
Project 1-3
Physiomic Self: Multi-scale Modeling of Physical and
Physiological Systems of Human Body
Biomedical Engineering(2),
Neurosurgery(1), General
Practice(1)
Group 2 Simulated Self: Individuated Second Self SNUH, KAIST
Project 2-1
Semantic Self: Ontological Representation and
Engineering of Health Avatar
Nursing Informatics(2), Internal
Medicine(1), Pathology(1)
Project 2-2
Augmented Self: Multi-modal Assessment and
Treatment to Retain and Enhance Human Performance
NLP(1), Graphics(1), Image
Processing(1), Psychiatry(1)
Group 3
Ubiquitous Self: Life Logs and Distributed
Collaborations
KAIST, ETRI
Project 3-1
Distributed Self: Customized and Context-aware
Healthcare Service Agents in Smart Phone Environment
AI(1), Software Engineering(1),
Bioinformatics(1)
Project 3-2
Connected Self: Life Logs and Stream-Type Data Mining
for Health Protection
Information Systems(1), Data
Mining(1)
9. 9
Target healthcare domains
Obesity, diabetes, dementia
On-going research topics
Activity Recognition for Personalized Life-Care
(Prof. Ho-Jin Choi)
Healthcare Service Framework for Continuous
Context Monitoring (Prof. Jun-Hwa Song)
Text Mining for Extracting Knowledge from Web
Contents (Prof. Key-Sun Choi)
Personalized Bio and Medical Data Analysis (Prof.
Gwan-Su Yi)
Research Topics
10. Activity Recognition for Personalized
Life-Care
Prof. Ho-Jin Choi
Dept. of Computer Science
KAIST
10
11. Multi-Sensor Surveillance for Elderly Care
11
“Patient #1234 is
in a risky situation”
Data observed from microphones helps
the system detect the potentially risky
situations .
The agent estimates patient #1234’s behaviors.
When preliminary conditions of
dangerous situations are occurred
to the patient, the agent alarms to
the caregiver.
12. 12
Activity Recognition from Video Image with Depth Sensor
Action Recognition with Automatically Detected Essential Body Joints
13. Technologies Involved
Understand Image Data
- RGB images (camera) and
depth images (depth sensor)
are sent to the system
- System then do
-Find a patient in a scene
-Track the patient
-Understand behaviors of
the patient
★ Issues to challenge
- The level of complexity
of scenes and behaviors
- Scenes may contain
various objects and
backgrounds
- Human-behaviors should
be understood as much
as possible.
13
Understand Audio Data
-Audio data (microphones)
is sent to the system
-System then do
-Detect abnormal sounds
★ Issues to challenge
- How accurate the system
detects abnormal sounds
Detect Risky Situation
-After analyzing data from
various sensors, the system
determines whether the
situation is potentially risky
-System constructs a
database for predefined
risky situations
-For every situation, the
system calculates the
likelihood of being risky
-If the likelihood scores
more than a threshold, it
alarms to the caregiver
★ Issues to challenge
-How well the system
constructs the database
-The accuracy of likelihoods
Find Patient’s Location
-Smartphone gives and
receives various signals to
update patient’s geographic
information
★ Issues to challenge
- How accurately the system
locates the patient
14. Wrist-Type Device Based Human Behavior Recognition
14
Mediated Interface for human-robot interaction
….
Health Care
Care Services
Raw data
(Behavior pattern,
Vital Signal, etc)
Old People
How to get “Raw Data”
From Old People?
Robots
Care-giver
Activity, Gesture,
Vital signal,
Location,
Identification(MI: Mediated Interface)
Ex: Watch, Ring
Robots
Care-giver
Elderly Care Services Using Robots
Suggestion
Fall
Detection
Wandering
Monitoring
Location
Monitoring
Care Services
15. Wrist-Type Device Based Human Behavior Recognition
15
Wrist-type and waist-type monitors
MCU Cortex-M3 (STM32F100)
RF(Zigbee) CC2520
Sensors 3-axis accelerometer(LIS331DLH)
3-axis gyro (L3G4200D)
Temperature/humidity (SHT21)
Brightness (TCS3414CS)
IR Photodiode (TSOP85238)
Emergency
button
1개 (front side)
Memory card MicroSD
Battery [Li-Ion 600mAh]
Recharger External rechager
Strap Wrist: nato band
Waist: elastic belt
16. Lifestyle Manager Using SNS and Activity Recognition
16
Life-style patterns
Clinical history
Genetic information
Server
Smartphone
users
Lifestyle
ranking
Life
log
Lifestyle
disease risk
Default
behavior
registration
Location - time
elapse
threshold
Localization by
Wifi signal
17. 17
Analysis of life log and SNS
Lifestyle = Eating habit(timing and food types) + CAR(Circadian activity rhythm)
Server
Many smart phone users
Location dimension
Sleep : My room, Park, Motel
Rest : TV room, Living room, Lounge
Work or study : Work place, Study place
Enjoy : Shopping place, Cultural place, Attractions
Usual food : Restaurant
Exercise : Exercise place
Religious activities : Church, Buddhist temple
Fast food or snack : Fast food place, Mc. Donald,
Convenience store
Sugar-sweetened beverage : Cafeteria,
Convenience store
Smoking : Smoking place, Convenience store,
Alcohol : Alcohol place, Bar
Drug : Drug store
UNKNOWN
1. Lifestyle
recommendation
2. Measurement of
Lifestyle Metric
Data matrix
Tries for users’ visiting patterns on
location & time dimension
People
Healthcare organizationsProactive/Reactive Services
Lifestyle Manager Using SNS and Activity Recognition
18. Lifestyle Manager Using SNS and Activity Recognition
18
- Home, Hotel
- Smoking place
- Drinking place
-Working place, Studying place
- Restaurant
- Cafeteria, Coffee shop
- Exercising place
- Religious place
-Attractions, Shopping place,
Cultural place, Enjoy place
- Hospital, Pharmacy
- Unknown
Location manager
- Facebook :
contains more
daily lives than
others
( e.g.,
“I ate a hamburger,
so cool.“ 11:45AM )
Social Network
Services
-Walking
- Exercise / Sport
- Running
- Riding an automobile
- Riding a bicycle
- No activity
Activity Recognition
-Accelerometer
- Illuminance sensor
-WiFi
- GPS
Sensor Handler
- Name
- SNS information
-Address ( GPS )
- BMI
- …
User profile
- Lifelog
- Carlorie counting
(day, week, …)
- Lifestyle disease risk
Service Provider
20. 20
Problem Document1
Solution Document1
Original Document1
Original Document2
Original Document3
Original Document4
Original Document10
...
Problem
Document10. . .
Solution
Document10. . .
Split to problem and
solution documents
Topic Mining for Problems and Solutions
22. Healthcare Service Framework for
Continuous Context Monitoring
Prof. Jun-Hwa Song
Dept. of Computer Science
KAIST
22
23. Context-Aware Healthcare Service Scenarios
23
Example Scenarios
Obesity monitoring
Continuously monitors people’s activity level
and consumed calories, and suggests proper
exercises to the people.
Elderly people monitoring
Continuously monitors an elderly people’s
emergency situation such as slipping down on
a wet floor, and expedites an emergency call.
Cardiac patient monitoring
Continuously monitors a cardiac patient’s ECG,
and expedites an emergency call.
24. DietSense: Smartphone-Based Diet Monitoring for Enhancing
Obesity Self-Care
24
Comparing diet and physical activity
Monitoring Physical ActivityCapturing Diet
Calories consumed
from food
Calories burned during
physical activity
camera
microphone
accelerometer
25. Activity Log
Smartphone
1. Collecting activity data from the patient
2. Training ML algorithms for analyzing activity patterns
3. Figuring out the right does time without interrupting
the current work activity
4. Notify the does time and subsequent reminder
MedicineTaker
Motion Sensor
Activity Log
Place A Place A
Task 1 Task 2 Task 3
Action 1-1
Action 1-2
Action 1-3 Action 2-1
Action 2-2
Action 3-1
Type 1
Type 2
Smart Alarming for Long-Term Medicine Adherence
25
26. Continuous Context Monitoring
26
Continuous monitoring of user’s context
A key building block for personal context-aware applications
Often requires complex, multi-step, continuous processing for multiple devices
E.g., Running situation -> sensing in three 3-axis accelerometers, FFT processing,
recognition
Location-based
Services
HealthMonitoring
U-Trainer
U-Secretary
U-Reminder
Dietdiary
U-Learning
Behaviorcorrection
S
F C
S
S
F
F
C
SS
F
C S
S
F
C
S
F
C
Sensing
Feature extraction
Context recognition
PAN-scale dynamic
distributed computing
platform
Context monitoring
(e.g., sensing, feature extraction,
recognition)
Application logic
Location-based
Services
HealthMonitoring
U-Trainer
U-Secretary
U-Reminder
Dietdiary
U-Learning
Behaviorcorrection
A A
A App logic
27. Mobile Healthcare Service Framework
27
Develop a healthcare
service framework
To support multiple and long
running healthcare services with
highly scarce and dynamic
resources
Efficient resource utilization
Longer lasting operation (and
service) under highly scarce
resource situation
Quick and efficient abnormal
situation detection
Seamless (stable) operation
even under high resource
dynamics
Challenges
Limited battery power due to
mobility
Scarce computing resources of
mobile devices
Dynamic join/leave of
heterogeneous sensors
Multiple healthcare services
share highly limited resources
Resource Manager
Policy
Manager
Energy Manager
Sensor Broker
Sensor Detector
Communication
Manager
… …Heartbeat monitoringFall monitoring
Healthcare services
API
Message
Interpreter
Sensor Data Processor
Resource
Monitor
Network protocols (e.g., ZigBee, BT)
Health Context Monitor
Sensor data
Requests
Sensor availability/status
Results
Sensor detection/control, Data/status report
Sensors in BAN/PAN
Application Broker
Application
Interface
Result Manager Message Parser
Diet diary
GPSBVP/GSR Accelerometers
……
Anomaly Detector
Feature Extractor
Resource Coordinator
28. Healthtopia – Healthcare Platform
Providing API
for utilizing
health sensors
Saving power
consumption
for concurrent
multiple apps
28
29. Text Mining for Extracting Knowledge
from Web Contents
Prof. Key-Sun Choi
Dept. of Computer Science
KAIST
29
30. Food Ingredients and Recipe Advice for Controlling Obesity
Web Environment
Ontology
Mobile Environment
Recipe
Extraction
Web /Wikipedia
Automatic
User Experience
Extraction
Target Food/Dish
Recognition
Manual
User Experience
Input
Web Log / SNS
Equipment
How-to
Food/Dish
Restaurant
DB
Scenario 2.
New Recipe (Low calories)
Suggestion w/ same Ingredients
Scenario 1.
Food-NutritionAssociationVisualization
Nutrition
Ingredients
Food-Nutrition
Extraction
30
31. Mining Connections between Multiple Sources
31
Literature Web Clinical Data
HeterogeneousTextual Sources
-Textbook
- PubMed
- Blogs
-Wikipedia
- Personal health record
Medical information sources
Literature contents affect the Web contents
As background factual knowledge
Web contents have other benefits
Wide coverage
Huge collaborators (confidence)
Aggregating information from multiple sources
Analysis of trend evolving on literature/Web to identify factors that will improve the
quality of patient care
Reliability: Literature > News > Web (Wikipedia, blog, SNS)
Accessibility: Web ≥ News > Literature
32. Detecting MeSH Keywords from Web Pages
32
Medical Subject Headings (MeSH)
NLM controlled vocabulary thesaurus used for indexing articles for PubMed
Tree structure (http://www.nlm.nih.gov/mesh/trees.html)
Provide an efficient way of accessing and organizing biomedical information
Examples of MeSH Headings
Body Weight, Kidney, Dental Cavity Preparation, Self Medication, Brain Edema
Extracting Candidates
Matching
Obesity is a medical condition in which excess body fat has a
ccumulated to the extent that it may have an adverse effect on
health, leading to reduced life expectancy and/or increased he
alth problems.[1][2] Body mass index (BMI), a measurement
which compares weight and height, defines people as overweig
ht (pre-obese) if their BMI is between 25 and 30 kg/m2, and o
bese when it is greater than 30 kg/m2.
• Hyperinked terms are extracted as term candidatesLanguage Handling
33. Detecting MeSH Keywords from Web Pages
33
Extracting Candidates
Matching
Obesity
Medical
condition
Body
fat
Body Mass Index
weight
Dieting
Obesity
Medical
condition
Body
fat
Body Mass Index
Body
Weight
Diet
Link
Structure
MeSH
term
Language Handling
Language Handling
Polysemy and homonymy problem
35. 35
맛있는 감자탕 1그릇을 먹을경우 177Kcal를 섭취하게 된다고 합니다.
Parsing the sentence
Extracting knowledge
<감자탕 1그릇, 열량, 177Kcal>
Infobox DB
Extracting Knowledge from Unstructured
Texts using Infobox DB
36. Personalized Bio and Medical Data Analysis
Prof. Gwan-SuYi
Dept. of Bio and Brain Engineering
KAIST
36
37. Personalized Diseases Risk Analysis
User
Agent
Disease risk
Prediction model
Personal genome
Data processing model
Drug response
Prediction model
Disease risk info.
(SNP-Disease)
Drug response info.
(SNP-Drug)
Personal genome
info.
Personal sequence
data
New info. on
disease risk
New info. on drug
response
Update Update
request
result
Personalized
disease risk
Genome
profile
Personalized drug
response
Storage
Build database
Personalized Personalized
Drug
response
Diseases
risk
Obesity, Diabetes Obesity, Diabetes
37
38. Constructing Databases for Diseases Risk and Drug
Response
38
184(Type I Diabetes), 203(Type II Diabetes), 82(Obesity) entries for diseases related SNP markers
collected
228 drugs, 830 SNP markers, 1341entries for drug-SNP related information collected
Diseases
Drugs
Diseases risk info.
SNP ID
Gene
Gene Region (Locus)
Risk Allele
Odds Ratio
P-value
Reference
…
PharmGKB
Drug Bank
Drug response info.
SNP ID
Gene
Gene Region (Locus)
Drug
Condition
Reference
…
Integrated database for
diseases risks and drug responses
Public database
Drug related info.
23andMe
Navigenics
Pathway Genomics
Gene sequencing
service drug related
info.
23andMe
Navigenics
deCODEme
Gene sequencing
service GWAS info.
HugeNavigator
GAD
NCBI (HapMap &
NHGRI catalog)
Public database
GWAS info.
39. Developing Methods for Analyzing Diseases Risk and
Drug Response
39
Diseases
OMIM
PharmGKB
DrugBank
Drugs
PharmGKB
DrugBank
SNPs
dbSNP
HapMap
Genome type
WTCCC
Genome body
UCSC
Ensembl
AceView
Genome
Entrez
Bio. pathway
KEGG
Reactome
NCI pathway
Panther
SNPs
dbSNP
HapMap
Genome type
WTCCC
Biological information
SNP
SNP
Analysis tech. for diseases risk
Analysis tech. for drug response
Obesity, Diabetes
• Extraction of drug response related SNP’s
• Drug targeting and biological pathway based function analysis
• Drug response prediction
• Obesity (Diabetes) related SNP or SNP combinations info.
• Genomic and biological pathway based function analysis
• Diseases risk prediction
40. Service Platform for Personalized Information about
Diseases Risk and Drug Response
Agent
User
Plug-ins from
life-logging team
Diseases risk
prediction model
Personal genome info.
data processing model
Drug response
prediction model
Diseases risk info.
(SNP-Disease)
Drug response info.
(SNP-Drug)
Diseases DrugsGenome
body
SNP PathwayGenome
type
Life-logging
database
Personal genome
info.
40