This document proposes a remote health monitoring system using wearable body sensors to monitor cardiovascular patients. The system has three tiers: 1) Wearable sensors like a Holter monitor collect physiological data. 2) A personal server stores and analyzes the data using an intelligent assistant and notifies medical staff of emergencies. 3) A medical server connected to the cloud allows doctors and family to access the data from anywhere. The system prioritizes critical data like ECG to ensure emergency situations are addressed promptly while compressing other data to efficiently use storage. This new technology could help reduce mortality by enabling real-time monitoring of patients' cardiovascular health.
This document summarizes a remote health monitoring system using wearable body sensors to monitor cardiovascular disease patients. The system consists of three parts: 1) Wearable body sensors that collect physiological data from patients, 2) A personal server (PDA) that prioritizes and transfers data to 3) A medical server connected to the cloud where data can be accessed by medical staff. The system aims to efficiently respond to emergencies by prioritizing vital sign data and notifying medical staff of changes in a patient's heart health.
Wireless Body Area Networks for Healthcare Applications: An OverviewTELKOMNIKA JOURNAL
Healthcare systems have been facing various new challenges due to increasing and rising aging
population in healthcare. Advance information and communication technologies have introduced Wireless
Body Area Networks (WBANs) for healthcare systems. WBANs provide different monitoring services in
healthcare sector for monitoring their patients with more convenience. WBANs are economical solutions
and non-invasive technology for healthcare applications. This review paper provides a comprehensive
review on WBANs applications, services and recent challenges.
M health an emerging trend an empirical studycsandit
The advent and advancement in technology specific to medical field has seen a migration of its
work across the globe, adapting higher and newer levels of m-health. Technology has been
successful in transforming the way traditional monitoring and alert system work to a modern
approach wherein minimizing the need for physical monitoring. Today, the field of healthcare
use varied monitoring systems to monitor the health of patients using ubiquitous and nonubiquitous
devices. These are sensor based devices that can read vital signs of patients and send
the data to the required personnel’s using mobile networks. This paper understands and
analyses how the monitoring and alert system works specific to m-health. m-health including
wearable and non-wearable devices read various vital signs and have the ability to monitor
health real-time and transfer the information collected using mobile network. m-health has
become an useful tool for elderly in this fast paced world where almost all the family members
are working or studying to keep track and maintain optimal health status. m-health alert system
involves the patient, the caretaker and medical service provider wherein the patient wears the
device and vital signs recorded are transferred the medical service provider who then analyses
the data collected and required changes in the medication are implemented. This paper
proposes a medical alert system that enlightens the capabilities of m-health making health
monitoring easy and reliable. It contains a three-level severity check and raises an alarm to the
caretaker, the physician or the ambulatory service provider.
This document reviews a wireless biomedical parameter monitoring system using an ARM microcontroller. The proposed system continuously monitors key patient vital signs like temperature, heartbeat, ECG, blood sugar, and oxygen levels using biosensors. The data is transmitted wirelessly to an ARM server using a Zigbee network. If any measurements exceed thresholds, an alarm is triggered and a message is sent to the doctor's phone via GSM. The system aims to allow for remote monitoring of patients after discharge to alert doctors to emergencies in real-time.
This document discusses the future of intensive care units and information technology. It outlines how precision medicine, big data, medical devices, virtual reality, and the internet of things can transform ICU care. Specifically:
- Precision medicine and identifying patient subphenotypes can lead to personalized treatment protocols. Big data from medical devices, images, and sensors can help with this approach.
- Medical devices are becoming informatics platforms that can integrate with hospital systems to share vital sign data, detect adverse events, and measure asynchrony during ventilation.
- Virtual reality and early neurocognitive rehabilitation are emerging technologies being studied to benefit ICU patients.
- The internet of things, smart alerts, and continuous remote monitoring via mobile
In this paper, a novel cloud-based WBAN health management system is introduced to. This system can be used for people’s health information collection, record, storage and transmission, health status monitoring and assessment, health education, telemedicine, and remote health management. Therefore it can provide health management services on-demand timely, appropriately and without boundaries.
This document summarizes a survey on wireless body area networks (WBANs). It begins by defining WBANs and their applications in health monitoring. It describes the typical architecture of a WBAN system, which consists of on-body and in-body sensor nodes that communicate wirelessly with a coordinator that transfers data to medical servers. The document then discusses some key differences between WBANs and traditional wireless sensor networks, such as lower node density and support for human mobility in WBANs. It also outlines several challenges for WBANs, such as limited power, security, interference, and regulatory requirements due to devices being implanted or worn on the human body. Finally, it provides examples of medical and
This document discusses health monitoring using mobile phones. It provides an overview of existing works on mobile health monitoring systems, comparing their characteristics such as the types of vital signs measured, communication approaches, and trial implementations. Some key issues with existing systems are also addressed, such as usability for older patients and handling private health data. The document concludes that mobile health monitoring has significant potential to improve healthcare, but further work is needed to develop more inclusive and robust systems.
This document summarizes a remote health monitoring system using wearable body sensors to monitor cardiovascular disease patients. The system consists of three parts: 1) Wearable body sensors that collect physiological data from patients, 2) A personal server (PDA) that prioritizes and transfers data to 3) A medical server connected to the cloud where data can be accessed by medical staff. The system aims to efficiently respond to emergencies by prioritizing vital sign data and notifying medical staff of changes in a patient's heart health.
Wireless Body Area Networks for Healthcare Applications: An OverviewTELKOMNIKA JOURNAL
Healthcare systems have been facing various new challenges due to increasing and rising aging
population in healthcare. Advance information and communication technologies have introduced Wireless
Body Area Networks (WBANs) for healthcare systems. WBANs provide different monitoring services in
healthcare sector for monitoring their patients with more convenience. WBANs are economical solutions
and non-invasive technology for healthcare applications. This review paper provides a comprehensive
review on WBANs applications, services and recent challenges.
M health an emerging trend an empirical studycsandit
The advent and advancement in technology specific to medical field has seen a migration of its
work across the globe, adapting higher and newer levels of m-health. Technology has been
successful in transforming the way traditional monitoring and alert system work to a modern
approach wherein minimizing the need for physical monitoring. Today, the field of healthcare
use varied monitoring systems to monitor the health of patients using ubiquitous and nonubiquitous
devices. These are sensor based devices that can read vital signs of patients and send
the data to the required personnel’s using mobile networks. This paper understands and
analyses how the monitoring and alert system works specific to m-health. m-health including
wearable and non-wearable devices read various vital signs and have the ability to monitor
health real-time and transfer the information collected using mobile network. m-health has
become an useful tool for elderly in this fast paced world where almost all the family members
are working or studying to keep track and maintain optimal health status. m-health alert system
involves the patient, the caretaker and medical service provider wherein the patient wears the
device and vital signs recorded are transferred the medical service provider who then analyses
the data collected and required changes in the medication are implemented. This paper
proposes a medical alert system that enlightens the capabilities of m-health making health
monitoring easy and reliable. It contains a three-level severity check and raises an alarm to the
caretaker, the physician or the ambulatory service provider.
This document reviews a wireless biomedical parameter monitoring system using an ARM microcontroller. The proposed system continuously monitors key patient vital signs like temperature, heartbeat, ECG, blood sugar, and oxygen levels using biosensors. The data is transmitted wirelessly to an ARM server using a Zigbee network. If any measurements exceed thresholds, an alarm is triggered and a message is sent to the doctor's phone via GSM. The system aims to allow for remote monitoring of patients after discharge to alert doctors to emergencies in real-time.
This document discusses the future of intensive care units and information technology. It outlines how precision medicine, big data, medical devices, virtual reality, and the internet of things can transform ICU care. Specifically:
- Precision medicine and identifying patient subphenotypes can lead to personalized treatment protocols. Big data from medical devices, images, and sensors can help with this approach.
- Medical devices are becoming informatics platforms that can integrate with hospital systems to share vital sign data, detect adverse events, and measure asynchrony during ventilation.
- Virtual reality and early neurocognitive rehabilitation are emerging technologies being studied to benefit ICU patients.
- The internet of things, smart alerts, and continuous remote monitoring via mobile
In this paper, a novel cloud-based WBAN health management system is introduced to. This system can be used for people’s health information collection, record, storage and transmission, health status monitoring and assessment, health education, telemedicine, and remote health management. Therefore it can provide health management services on-demand timely, appropriately and without boundaries.
This document summarizes a survey on wireless body area networks (WBANs). It begins by defining WBANs and their applications in health monitoring. It describes the typical architecture of a WBAN system, which consists of on-body and in-body sensor nodes that communicate wirelessly with a coordinator that transfers data to medical servers. The document then discusses some key differences between WBANs and traditional wireless sensor networks, such as lower node density and support for human mobility in WBANs. It also outlines several challenges for WBANs, such as limited power, security, interference, and regulatory requirements due to devices being implanted or worn on the human body. Finally, it provides examples of medical and
This document discusses health monitoring using mobile phones. It provides an overview of existing works on mobile health monitoring systems, comparing their characteristics such as the types of vital signs measured, communication approaches, and trial implementations. Some key issues with existing systems are also addressed, such as usability for older patients and handling private health data. The document concludes that mobile health monitoring has significant potential to improve healthcare, but further work is needed to develop more inclusive and robust systems.
This document provides an overview of a senior design project to create a prototype wireless body area network (WBAN) consisting of a custom body sensor unit (BSU) and an Android-based body control unit (BCU). The BSU hardware prototype measures motion data from an accelerometer and gyroscope, timestamps the data, transmits it to the BCU via Bluetooth, and stores 30 minutes of data locally. The BCU is an Android phone running a custom app that receives the data, stores 8 hours of data locally, and allows the user to view the data. The project aimed to design compact, lightweight, long-lasting devices to monitor patients and help reduce healthcare costs through remote monitoring.
The presentation discusses body area networks (BANs), which are wireless networks of wearable devices that communicate data about the human body. BANs include sensors that can monitor vital signs and actuators that provide feedback or treatment. Common applications of BANs in healthcare include monitoring heart function, diabetes, and movement disorders. The presentation covers the hardware and software architecture of BANs, challenges around security and privacy, and the potential for BANs to improve healthcare through continuous remote patient monitoring.
A body area network (BAN), also referred to as a wireless body area network (WBAN) or a body sensor network (BSN) or a medical body area network (MBAN), is a wireless network of wearable computing devices.
Body based sensor network and its applicationsShashank Gupta
Body-based sensor networks (BBSN) involve small wearable sensors that monitor aspects of human health. They work by collecting data from various sensors attached to the body and transmitting it wirelessly to central monitoring devices. Key applications of BBSNs include real-time detection of medical conditions like heart attacks using sensors that monitor electrocardiograms, temperature, and other vital signs. This can enable early diagnosis and treatment, reducing healthcare costs and deaths from conditions that currently go undetected. Future BBSNs are expected to allow for more proactive healthcare management and improved quality of life by facilitating continuous health monitoring.
This document outlines a proposed wireless body area network (WBAN) system for ubiquitous and affordable healthcare. It begins with an introduction to WBANs and their use in continuous health monitoring. A 3-tier network architecture is proposed, consisting of wearable sensor nodes, a personal server, and a medical server. The document discusses the existing holter monitor system, proposed WBAN system capabilities, data flow, network positioning, system requirements, security considerations, applications, and comparisons to other wireless networks. Potential advantages include remote health monitoring and early disease detection, while challenges include interference between devices and lack of sensor integration.
Real Time Health Monitoring System: A Reviewijtsrd
Generally in critical case patients are supposed to be monitored continuously for their heart rate, oxygen saturation level, blood pressure, body temperature, pulse-oximetry (SPO2) and ECG etc. In the previous methods, the doctors need to be present physically on sight, so that the real time health monitoring system is used every field such as hospital, home care unit, sports using wireless sensor network. This health monitoring system use for chronicle diseases patients who have daily check-up. So, researchers design a system as portable device. Researcher designed different health monitoring system based on requirement. Different platform like Microcontroller, ASIC, PIC microcontroller and embedded systems are used to design the system based on this performance and in the recent years cloud based e-healthcare systems have emerged. In future FPGA based or using IoT we can develop a system which will help to monitor different health parameters. Ajinkya Anant Bandegiri | Pradip Chandrakant Bhaskar"Real Time Health Monitoring System: A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd7092.pdf http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/7092/real-time-health-monitoring-system-a-review/ajinkya-anant-bandegiri
The FCC recently dedicated spectrum for Medical Body Area Networks (MBANs) to allow multiple wireless sensors to monitor patients. An MBAN consists of a central hub that collects data from body-worn sensors and transmits it over a healthcare facility's network to monitoring stations. The FCC will permit MBANs to operate in the 2360-2400 MHz band either indoors with coordination or anywhere without coordination. This will enhance patient safety and mobility by reducing wired connections while supporting new medical applications and wireless devices.
The document describes several healthcare IT systems implemented in Tamil Nadu, India:
1. A disease surveillance system for HIV/AIDS that automates data gathering, reporting, and provides mapping and analytics at the village level.
2. An electronic medical record system for ART patients with biometric identification and access to records across centers.
3. A patient management system using digital pen technology for physicians to record exam notes and prescriptions.
4. Remote patient monitoring services for ICU, radiology and cardiology using devices like ECG monitors and mobile transmission of data.
5. An ambulatory patient monitoring system called SmartChair that measures vital signs and transmits data via SMS or to a central
This seminar presentation summarizes the implementation of a Wireless Body Area Network (WBAN) for monitoring physiological data. The WBAN system consists of sensor nodes that measure body temperature, heart rate, and blood oxygen levels. The sensor nodes transmit the physiological data via ZigBee to a Body Control Unit (BCU) for processing. The BCU then sends the data to a remote server for storage and visualization. The presentation outlines the system architecture, hardware and software requirements, and performance evaluation of the WBAN for real-time health monitoring and e-health applications.
This document discusses wireless body area networks (WBANs), which allow for inexpensive and continuous health monitoring through connecting various medical sensors and appliances located inside and outside the human body via wireless communication. WBANs have a three-tier architecture, consisting of intelligent sensor nodes on the body (Tier 1), a personal server like a cell phone (Tier 2) that interfaces with the sensors, and a medical server (Tier 3) that authenticates users, stores patient data, analyzes sensor data, and can alert emergency services if needed. WBANs allow remote monitoring of patients with chronic conditions and can alert hospitals to health issues even before symptoms occur.
This document provides an overview of wireless body area networks (WBANs). It defines WBANs as low-power wireless networks designed for use on or around the human body to monitor vital signs. The document outlines the key components of a WBAN including body sensor units that measure parameters, a body control unit that receives and saves data, and a 3-tier architecture involving sensors, personal devices, and medical servers. Challenges, applications, research areas and the future scope of WBANs are also discussed.
Security Requirements, Counterattacks and Projects in Healthcare Applications...arpublication
Healthcare applications are well thought-out as interesting fields for WSN where patients can be examine using wireless medical sensor networks. Inside the hospital or extensive care surroundings there is a tempting need for steady monitoring of essential body functions and support for patient mobility. Recent research cantered on patient reliable communication, mobility, and energy-efficient routing. Yet deploying new expertise in healthcare applications presents some understandable security concerns which are the important concern in the inclusive deployment of wireless patient monitoring systems. This manuscript presents a survey of the security features, its counter attacks in healthcare applications including some proposed projects which have been done recently.
This document describes an intelligent health care monitoring system using a wireless sensor network. It discusses using sensors to monitor patient vital signs like temperature, humidity, and heart rate. Sensor data is transmitted via CC2500 low power wireless radios to a centralized control room. The system aims to improve patient monitoring by making equipment more portable and allowing remote access to patient data by doctors through mobile devices. It concludes the proposed system can check various health parameters in real-time to monitor patient health more efficiently through energy efficient wireless communication between sensor nodes.
1. A new handheld ECG device has been developed to allow users to easily record their electrocardiogram (ECG) data anywhere and anytime without the help of medical technicians.
2. Clinical studies show the handheld ECG provides accurate ECG measurements and reliable wireless data transmission capabilities.
3. The handheld ECG can be used for clinical screening and health monitoring as part of a new telemedicine system, allowing physicians to remotely monitor patients' heart function.
1. The document proposes a wireless sensor network architecture for remote health monitoring of assisted living residents.
2. Sensors embedded in the body and environment continuously monitor vital signs and environmental conditions. Data is transmitted to a central database for access by caregivers.
3. An experimental smart home has been set up with motion, temperature, and other sensors communicating over a wireless network to a central computer. Preliminary results found no false detections over one week.
This document summarizes a student's seminar presentation on Wireless Body Area Networks (WBANs). The key points are:
1. WBANs allow for monitoring of a person's health conditions anywhere through integration of intelligent, low-power sensor nodes on or inside the body.
2. A 3-tier architecture is used, including sensors on the body (Tier 1), a personal server (Tier 2) that connects to sensors and sends data to medical servers, and medical servers (Tier 3) that analyze data and manage medical records.
3. Common technologies used in WBANs include ZigBee, IEEE 802.15.4, and Bluetooth Low Energy due to their
Intelligent Healthcare Monitoring in IoTIJAEMSJORNAL
The developing of IoT-based health care systems must ensure and increase the safety of the patients, their quality of life and other health care activities. We may not be aware of the health condition of the patient during the sleeping hours. To overcome this problem. This paper proposes an intelligent healthcare monitoring system which monitors and maintains the patient health condition at regular intervals. The heart rate sensor and temperature sensor would help us analyze the patients’ current health condition. In case of major fluctuations in consecutive intervals a buzzer is run in order to notify the hospital staff and doctors. The monitored details are stored in the cloud "ThingSpeak". The doctor can view the patient health condition using Virtuino simulator. This system would help in reducing the random risks of tracing a patient medical highly. Arduino UNO is used to implement this intelligent healthcare monitoring system.
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.
In the age of today, technology pays attention to how it can be implemented in keeping people alive. It is clear that technology is offering the healthcare industry a much needed upgrade to mobile apps from medical translation resources that help patients lead healthier lives. One of the dizzying innovations that could change the healthcare industry is the wireless body area network WBAN .WBAN derives from the wireless sensor network WSN that deploys sensors over the human body. Wireless Body Area Network WBAN is a wireless networking system based on radio frequency RF that interconnects tiny nodes with sensor or actuator capabilities in, on, or around a human body. WBAN also links large and local area networks. As compared to WSN, WBAN has its own characteristics. Preeti Sondhi | Javaid Ahmad Malik "A Review of Wireless Body Area Network" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38384.pdf Paper Url: https://www.ijtsrd.com/computer-science/computer-network/38384/a-review-of-wireless-body-area-network/preeti-sondhi
Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...nikhilpatewar
The document describes a wireless medical surveillance system using a Raspberry Pi and X-Bee devices. It discusses how existing patient monitoring systems use wired connections that make it difficult to monitor patients who need to be moved. The proposed system uses wireless sensors connected to an X-Bee module to transmit patient data like temperature, oxygen levels, ECG readings to a Raspberry Pi base station. This allows for continuous remote monitoring of patients and alerts caregivers if readings exceed thresholds, making the system more flexible and effective for medical care.
This document provides an overview of a senior design project to create a prototype wireless body area network (WBAN) consisting of a custom body sensor unit (BSU) and an Android-based body control unit (BCU). The BSU hardware prototype measures motion data from an accelerometer and gyroscope, timestamps the data, transmits it to the BCU via Bluetooth, and stores 30 minutes of data locally. The BCU is an Android phone running a custom app that receives the data, stores 8 hours of data locally, and allows the user to view the data. The project aimed to design compact, lightweight, long-lasting devices to monitor patients and help reduce healthcare costs through remote monitoring.
The presentation discusses body area networks (BANs), which are wireless networks of wearable devices that communicate data about the human body. BANs include sensors that can monitor vital signs and actuators that provide feedback or treatment. Common applications of BANs in healthcare include monitoring heart function, diabetes, and movement disorders. The presentation covers the hardware and software architecture of BANs, challenges around security and privacy, and the potential for BANs to improve healthcare through continuous remote patient monitoring.
A body area network (BAN), also referred to as a wireless body area network (WBAN) or a body sensor network (BSN) or a medical body area network (MBAN), is a wireless network of wearable computing devices.
Body based sensor network and its applicationsShashank Gupta
Body-based sensor networks (BBSN) involve small wearable sensors that monitor aspects of human health. They work by collecting data from various sensors attached to the body and transmitting it wirelessly to central monitoring devices. Key applications of BBSNs include real-time detection of medical conditions like heart attacks using sensors that monitor electrocardiograms, temperature, and other vital signs. This can enable early diagnosis and treatment, reducing healthcare costs and deaths from conditions that currently go undetected. Future BBSNs are expected to allow for more proactive healthcare management and improved quality of life by facilitating continuous health monitoring.
This document outlines a proposed wireless body area network (WBAN) system for ubiquitous and affordable healthcare. It begins with an introduction to WBANs and their use in continuous health monitoring. A 3-tier network architecture is proposed, consisting of wearable sensor nodes, a personal server, and a medical server. The document discusses the existing holter monitor system, proposed WBAN system capabilities, data flow, network positioning, system requirements, security considerations, applications, and comparisons to other wireless networks. Potential advantages include remote health monitoring and early disease detection, while challenges include interference between devices and lack of sensor integration.
Real Time Health Monitoring System: A Reviewijtsrd
Generally in critical case patients are supposed to be monitored continuously for their heart rate, oxygen saturation level, blood pressure, body temperature, pulse-oximetry (SPO2) and ECG etc. In the previous methods, the doctors need to be present physically on sight, so that the real time health monitoring system is used every field such as hospital, home care unit, sports using wireless sensor network. This health monitoring system use for chronicle diseases patients who have daily check-up. So, researchers design a system as portable device. Researcher designed different health monitoring system based on requirement. Different platform like Microcontroller, ASIC, PIC microcontroller and embedded systems are used to design the system based on this performance and in the recent years cloud based e-healthcare systems have emerged. In future FPGA based or using IoT we can develop a system which will help to monitor different health parameters. Ajinkya Anant Bandegiri | Pradip Chandrakant Bhaskar"Real Time Health Monitoring System: A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd7092.pdf http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/7092/real-time-health-monitoring-system-a-review/ajinkya-anant-bandegiri
The FCC recently dedicated spectrum for Medical Body Area Networks (MBANs) to allow multiple wireless sensors to monitor patients. An MBAN consists of a central hub that collects data from body-worn sensors and transmits it over a healthcare facility's network to monitoring stations. The FCC will permit MBANs to operate in the 2360-2400 MHz band either indoors with coordination or anywhere without coordination. This will enhance patient safety and mobility by reducing wired connections while supporting new medical applications and wireless devices.
The document describes several healthcare IT systems implemented in Tamil Nadu, India:
1. A disease surveillance system for HIV/AIDS that automates data gathering, reporting, and provides mapping and analytics at the village level.
2. An electronic medical record system for ART patients with biometric identification and access to records across centers.
3. A patient management system using digital pen technology for physicians to record exam notes and prescriptions.
4. Remote patient monitoring services for ICU, radiology and cardiology using devices like ECG monitors and mobile transmission of data.
5. An ambulatory patient monitoring system called SmartChair that measures vital signs and transmits data via SMS or to a central
This seminar presentation summarizes the implementation of a Wireless Body Area Network (WBAN) for monitoring physiological data. The WBAN system consists of sensor nodes that measure body temperature, heart rate, and blood oxygen levels. The sensor nodes transmit the physiological data via ZigBee to a Body Control Unit (BCU) for processing. The BCU then sends the data to a remote server for storage and visualization. The presentation outlines the system architecture, hardware and software requirements, and performance evaluation of the WBAN for real-time health monitoring and e-health applications.
This document discusses wireless body area networks (WBANs), which allow for inexpensive and continuous health monitoring through connecting various medical sensors and appliances located inside and outside the human body via wireless communication. WBANs have a three-tier architecture, consisting of intelligent sensor nodes on the body (Tier 1), a personal server like a cell phone (Tier 2) that interfaces with the sensors, and a medical server (Tier 3) that authenticates users, stores patient data, analyzes sensor data, and can alert emergency services if needed. WBANs allow remote monitoring of patients with chronic conditions and can alert hospitals to health issues even before symptoms occur.
This document provides an overview of wireless body area networks (WBANs). It defines WBANs as low-power wireless networks designed for use on or around the human body to monitor vital signs. The document outlines the key components of a WBAN including body sensor units that measure parameters, a body control unit that receives and saves data, and a 3-tier architecture involving sensors, personal devices, and medical servers. Challenges, applications, research areas and the future scope of WBANs are also discussed.
Security Requirements, Counterattacks and Projects in Healthcare Applications...arpublication
Healthcare applications are well thought-out as interesting fields for WSN where patients can be examine using wireless medical sensor networks. Inside the hospital or extensive care surroundings there is a tempting need for steady monitoring of essential body functions and support for patient mobility. Recent research cantered on patient reliable communication, mobility, and energy-efficient routing. Yet deploying new expertise in healthcare applications presents some understandable security concerns which are the important concern in the inclusive deployment of wireless patient monitoring systems. This manuscript presents a survey of the security features, its counter attacks in healthcare applications including some proposed projects which have been done recently.
This document describes an intelligent health care monitoring system using a wireless sensor network. It discusses using sensors to monitor patient vital signs like temperature, humidity, and heart rate. Sensor data is transmitted via CC2500 low power wireless radios to a centralized control room. The system aims to improve patient monitoring by making equipment more portable and allowing remote access to patient data by doctors through mobile devices. It concludes the proposed system can check various health parameters in real-time to monitor patient health more efficiently through energy efficient wireless communication between sensor nodes.
1. A new handheld ECG device has been developed to allow users to easily record their electrocardiogram (ECG) data anywhere and anytime without the help of medical technicians.
2. Clinical studies show the handheld ECG provides accurate ECG measurements and reliable wireless data transmission capabilities.
3. The handheld ECG can be used for clinical screening and health monitoring as part of a new telemedicine system, allowing physicians to remotely monitor patients' heart function.
1. The document proposes a wireless sensor network architecture for remote health monitoring of assisted living residents.
2. Sensors embedded in the body and environment continuously monitor vital signs and environmental conditions. Data is transmitted to a central database for access by caregivers.
3. An experimental smart home has been set up with motion, temperature, and other sensors communicating over a wireless network to a central computer. Preliminary results found no false detections over one week.
This document summarizes a student's seminar presentation on Wireless Body Area Networks (WBANs). The key points are:
1. WBANs allow for monitoring of a person's health conditions anywhere through integration of intelligent, low-power sensor nodes on or inside the body.
2. A 3-tier architecture is used, including sensors on the body (Tier 1), a personal server (Tier 2) that connects to sensors and sends data to medical servers, and medical servers (Tier 3) that analyze data and manage medical records.
3. Common technologies used in WBANs include ZigBee, IEEE 802.15.4, and Bluetooth Low Energy due to their
Intelligent Healthcare Monitoring in IoTIJAEMSJORNAL
The developing of IoT-based health care systems must ensure and increase the safety of the patients, their quality of life and other health care activities. We may not be aware of the health condition of the patient during the sleeping hours. To overcome this problem. This paper proposes an intelligent healthcare monitoring system which monitors and maintains the patient health condition at regular intervals. The heart rate sensor and temperature sensor would help us analyze the patients’ current health condition. In case of major fluctuations in consecutive intervals a buzzer is run in order to notify the hospital staff and doctors. The monitored details are stored in the cloud "ThingSpeak". The doctor can view the patient health condition using Virtuino simulator. This system would help in reducing the random risks of tracing a patient medical highly. Arduino UNO is used to implement this intelligent healthcare monitoring system.
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.
In the age of today, technology pays attention to how it can be implemented in keeping people alive. It is clear that technology is offering the healthcare industry a much needed upgrade to mobile apps from medical translation resources that help patients lead healthier lives. One of the dizzying innovations that could change the healthcare industry is the wireless body area network WBAN .WBAN derives from the wireless sensor network WSN that deploys sensors over the human body. Wireless Body Area Network WBAN is a wireless networking system based on radio frequency RF that interconnects tiny nodes with sensor or actuator capabilities in, on, or around a human body. WBAN also links large and local area networks. As compared to WSN, WBAN has its own characteristics. Preeti Sondhi | Javaid Ahmad Malik "A Review of Wireless Body Area Network" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38384.pdf Paper Url: https://www.ijtsrd.com/computer-science/computer-network/38384/a-review-of-wireless-body-area-network/preeti-sondhi
Wireless Medical Surveillance System Using Raspberry Pi and X-Bee By. Nikhil ...nikhilpatewar
The document describes a wireless medical surveillance system using a Raspberry Pi and X-Bee devices. It discusses how existing patient monitoring systems use wired connections that make it difficult to monitor patients who need to be moved. The proposed system uses wireless sensors connected to an X-Bee module to transmit patient data like temperature, oxygen levels, ECG readings to a Raspberry Pi base station. This allows for continuous remote monitoring of patients and alerts caregivers if readings exceed thresholds, making the system more flexible and effective for medical care.
best biomedical project center chennai- recent advances in wearable sensors f...ASHOKKUMAR RAMAR
Recent advances in wearable sensors and systems have potential for ubiquitous healthcare monitoring. Ubiquitous healthcare aims to provide access to services anytime and anywhere through wireless body area networks, mobile devices, and cloud services. This allows for remote health data acquisition and personalized healthcare monitoring. The document discusses a system using wireless sensors and smartphones to continuously monitor cardiac patients' ECG data in real-time and alert caregivers if help is needed.
The document discusses recent advances in wearable sensors. It describes how wearable sensors composed of wireless body area networks, personal servers, and medical servers are being used for health monitoring. Key medical use cases discussed are monitoring Parkinson's disease using movement sensors, stroke rehabilitation using exercise coaching sensors, and detecting head impacts using accelerometers. The document outlines advantages like early disease detection and cost savings, disadvantages like cost and weight of units, and applications in health/wellness monitoring, safety, and sports. The conclusion is that wearable sensors show promise for remote healthcare monitoring with improved integration of sensors and power sources.
The document discusses recent advances in wearable sensors. It describes how wearable sensors composed of wireless body area networks, personal servers, and medical servers are being used for health monitoring. Key medical use cases discussed are monitoring Parkinson's disease using movement sensors, stroke rehabilitation using exercise coaching sensors, and detecting head impacts using accelerometers. The document outlines advantages like early disease detection and cost savings, disadvantages like cost and weight of units, and applications in health/wellness, safety, and sports monitoring. The conclusion is that wearable sensors show promise for remote healthcare monitoring with improved diagnostic capabilities.
In the last decade the healthcare monitoring systems have drawn considerable attentions of the researchers. The prime goal was to develop a reliable patient monitoring system so that the healthcare professionals can monitor their patients, who are either hospitalized or executing their normal daily life activities. In this work we present a mobile device based wireless healthcare monitoring system that can provide real time online information about physiological conditions of a patient. Our proposed system is designed to measure and monitor important physiological data of a patient in order to accurately describe the status of her/his health and fitness. In addition the proposed system is able to send alarming message about the patient’s critical health data by text messages or by email reports. By using the information contained in the text or e-mail message the healthcare professional can provide necessary medical
advising. The system mainly consists of sensors, the data acquisition unit, microcontroller (i.e., Arduino), and software (i.e., LabVIEW). The patient’s temperature, heart beat rate, muscles, blood pressure, blood glucose level, and ECG data are monitored, displayed, and stored by our system. To ensure reliability and accuracy the proposed system has been field tested. The test results show that our system is able to measure the patient’s physiological data with a very high accuracy.
As the world's aging population increases, wireless sensor networks can help monitor the health of elderly patients. These networks allow continuous monitoring of vital signs from wearable sensors. Researchers are working to optimize these networks for power efficiency, security, and management. Wireless health monitoring provides advantages over wired systems by allowing remote patient monitoring and emergency alerts anywhere. However, data transmission over infrastructure networks may not always be possible, so ad hoc wireless networks are needed for continuous monitoring in more locations.
Energy-efficient cluster-based security mechanism for Wireless Body Area Netw...IJSRD
Rapid expansion of wireless technologies permits continuous healthcare monitoring of mobile patients using compact biomedical wireless sensor motes. These tiny wearable devices –have limited amount of memory, energy, computation, & communication capabilities – are positioned on a patient; after that , they self-configure to create a networked cluster that is capable to continuously monitor important signs like blood pressure and flow, ECG, core temperature, the oxygen saturation, and CO2 concentration (i.e. for the respiration monitoring). The WBAN is an energizing innovation that guarantees to convey the human services to a novel level of the personalization. The scaled down sensors can be worn on body and they can non-rudely screen individual's physiological state. The numerous sensors speak with mobile utilizing the remote interfaces shaping WBAN. The WBANs empower checking a singular's wellbeing consistently in the free living conditions, where individual is allowed to direct his or her day by day action. In propose, design a enhance cluster based protocol.
2013 ieee human health monitoring mobile phone application by using the wirel...tilottama_deore
This document describes a mobile phone application for human health monitoring using wireless nanosensors and an embedded system. Nanosensors placed in mobile phones can monitor various health parameters like asthma, cancer, blood pressure and ECG by detecting chemical levels and temperature changes in the human body. The data is transmitted via Zigbee to a hospital management system which can alert patients and send ambulances if levels go outside normal ranges. The system aims to remotely monitor patients at low cost without needing frequent doctor visits.
The last several decades have seen cardiovascular illnesses become the leading cause of mortality globally, in both industrialized and developing nations alike. Clinical staff monitoring and early diagnosis of heart disorders can both lower death rates. However, because it takes more intelligence, time, and skill, precise cardiac disease identification in every case and 24-h patient consultation by a doctor are not yet possible. With the use of machine learning techniques, a preliminary concept for a cloud-based system to predict heart disease has been put out in this study. An effective machine-learning strategy should be applied for the precise identification of cardiac illness. This method was created after a thorough comparison of many machine learning methods in MATLAB coding. The application may thus be utilized by the medical professionals to monitor the patient’s real-time sensor data and begin live video streaming if urgent care is necessary. The ability of the suggested method to notify both parties right away when the patient checks the stage while the doctor isn’t there was a crucial component.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
The epidemic growth of wireless technology and mobile services in this epoch is creating a great impact on our life style. Some early efforts have been taken to utilize these technologies in medical industry. In this field, ECG sensor based advanced wireless patient monitoring system concept is a new innovative idea. This system aims to provide health care to the patient. We have sensed the patient’s ECG through 3 lead electrode system via AD8232 which amplifies minor and small bio-signals to the arduino which processes them, along with saline level. Saline level is detected through IR sensors. The output of the electrical pulse is shown with the serial monitor. The saline level is indicated by LCD. The major output ECG analog signal is displayed on serial plotter. The outputs are displayed through mobile application.
An IoT-based healthcare system leverages Internet of Things technology to improve the quality and efficiency of healthcare services. It involves the use of interconnected devices and sensors to monitor patients' health remotely and in real time. These devices can track vital signs such as heart rate, blood pressure, body temperature, and glucose levels, among others. The data collected is transmitted securely to healthcare providers, who can analyze it and provide timely interventions when necessary. IoT healthcare systems can also integrate with electronic health records, offering a comprehensive view of a patient's medical history and current health status. This enables personalized care and more informed medical decisions. Additionally, IoT can facilitate telemedicine, allowing patients to consult with healthcare professionals from the comfort of their homes. This can improve access to healthcare, especially for those in remote or underserved areas. However, the implementation of IoT-based healthcare systems also requires careful attention to data privacy and security to protect sensitive patient information. Overall, IoT in healthcare promises to revolutionize the industry by enhancing patient outcomes and streamlining healthcare delivery.
IoT and machine learning (ML) are becoming increasingly efficient in the medical and telemedicine areas all around the world. This article describes a system that employs latest technology to give a more accurate method of forecasting disease. This technology uses sensors to collect data from the body of the patient. The obtained sensor information is collected with NodeMcU before being transferred to the Cloud Platform "ThinkSpeak" through an ESP8266 Wi-Fi module. ThinkSpeak is a cloud server that provides real-time data streams in the cloud. For the best results, data currently saved in the cloud is evaluated by one of the machine learning algorithms, the KNN algorithm. Based on the findings of the analysis and compared with the data sets, the disease is predicted and a prescription for the relevant disease is issued.
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
UBIQUITOUS HEALTHCARE MONITORING SYSTEM USING INTEGRATED TRIAXIAL ACCELEROMET...ijujournal
Ubiquitous healthcare has become one of the prominent areas of research inorder to address the
challenges encountered in healthcare environment. In contribution to this area, this study developed a
system prototype that recommends diagonostic services based on physiological data collected in real time
from a distant patient. The prototype uses WBAN body sensors to be worn by the individual and an android
smart phone as a personal server. Physiological data is collected and uploaded to a Medical Health
Server (MHS) via GPRS/internet to be analysed. Our implemented prototype monitors the activity, location
and physiological data such as SpO2 and Heart Rate (HR) of the elderly and patients in rehabilitation. The
uploaded information can be accessed in real time by medical practitioners through a web application.
UBIQUITOUS HEALTHCARE MONITORING SYSTEM USING INTEGRATED TRIAXIAL ACCELEROMET...ijujournal
Ubiquitous healthcare has become one of the prominent areas of research inorder to address the
challenges encountered in healthcare environment. In contribution to this area, this study developed a
system prototype that recommends diagonostic services based on physiological data collected in real time
from a distant patient. The prototype uses WBAN body sensors to be worn by the individual and an android
smart phone as a personal server. Physiological data is collected and uploaded to a Medical Health
Server (MHS) via GPRS/internet to be analysed. Our implemented prototype monitors the activity, location
and physiological data such as SpO2 and Heart Rate (HR) of the elderly and patients in rehabilitation. The
uploaded information can be accessed in real time by medical practitioners through a web application.
IRJET- Design and Implementation of Health Monitoring SystemIRJET Journal
This document summarizes the design and implementation of a health monitoring system. The system uses sensors like pulse, ECG and temperature sensors connected to an Arduino board to monitor a patient's health status. The sensor data is sent wirelessly to a cloud-based ThingSpeak server for storage and real-time monitoring via a mobile application. The system allows doctors to remotely monitor patients' health parameters like temperature, pulse and ECG from anywhere without needing to visit in-person.
A Low Power Wearable Physiological Parameter Monitoring Systemijsrd.com
The design and development of a low power wearable physiological parameter monitoring system have been developing and reporting in this paper. The system can be used to monitor physiological parameters, such as ECG signals, temperature and heartbeat. The system consists of an electronic device which is worn on the wrist and finger, by an at-risk person. Using several sensors to measure different vital signs, the person is wirelessly monitored within his own home. An epic sensor has been used to detect ECG signals. The device is battery powered for use outdoors. The device can be easily adapted to monitor athletes and infants. The low cost of the device will help to lower the cost of home monitoring of patients recovering from illness. A prototype of the device has been fabricated and extensively tested with very good results.
Visensia is ph
ysiological monitoring software that collates and analyses data from bedside
monitors on 5
vital signs to produce a single patient health status score. This is used for early
identification of deterior
ation that might lead to cardiac or respir
atory arrest. One prospectiv
e,
single-centre, before-and-after study found that patients monitored with Visensia had a
statistically significantly shorter a
verage dur
ation of an
y cardio-respir
atory instability and fewer
episodes of serious and persistent instability
, although changes in patient management ma
y have
influenced these findings. The Visensia software requires e
xisting ph
ysiological monitors to pro
vide
data and costs £1950 for a 1-bed perpetuity licence; individual hospital systems are priced
according to size and include installation and configur
ation charges
The document discusses systems and their fundamental elements. It defines a system as composed of three key elements: transport, process, and storage. Transport represents movement/input-output. Process represents transformation. Storage represents structure/containment. An example is given of a computer system with a keyboard/monitor for transport, a CPU for process, and hard drive/RAM for storage. The document contrasts open systems from feedback systems, which use sensors and controllers to achieve goals. Understanding systems theory can help see connections across complex systems.
This document proposes a novel framework for securely sharing personal health records (PHRs) stored in the cloud. The framework uses attribute-based encryption to encrypt PHRs and allow fine-grained, patient-centric access control. It divides the system into multiple security domains (public and personal) with different types of users (e.g. doctors, friends). Role attributes are defined for public domains while data attributes are used for personal domains. The framework aims to reduce key management overhead while providing strong privacy and flexibility for PHR owners to specify access policies. It analyzes the complexity and compares to previous solutions. The proposed system uses HTML, JSP and Google App Engine for the web interface and cloud storage.
The document discusses predictions for cloud computing trends in 2016. Key predictions include large companies increasingly adopting cloud infrastructure to cut costs and risks; the rise of cloud analytics to help IT monitor cloud deployment costs; hybrid cloud strategies becoming more common and supported by cloud vendors; and security becoming a priority as more sensitive data and applications move to the cloud. It also summarizes Amazon Web Services' (AWS) Well-Architected Framework for designing cloud architectures, which focuses on security, reliability, performance efficiency, and cost optimization.
This document proposes a performance analysis model for big data applications in cloud computing. It introduces challenges in analyzing performance for big data applications running on cloud infrastructure and resources. The model aims to provide a framework to measure key performance indicators like response time, throughput, resource utilization, scalability, and energy efficiency. It outlines components of the model including workload profiling, resource profiling, performance metrics, and a monitoring system to collect data.
This document summarizes prior work on using IoT sensors for patient monitoring. It discusses research on using wearable sensors to remotely monitor patients' vital signs outside of hospitals. It also reviews efforts to use sensors inside homes and buildings to automatically collect health data from elderly and disabled patients to identify issues needing medical attention. Prior work demonstrated using sensors and weight monitors on medication bottles to track medication adherence. Research also explored using social robots equipped with sensors as mobile monitoring platforms to provide companionship for older adults. Challenges identified included ensuring the reliability of interconnected sensor devices and data transmission for critical health applications.
- Content-Based Image Retrieval (CBIR) is a technique used to retrieve images from large databases based on their visual content. It involves extracting features from an input query image and finding similar images from the database based on extracted features.
- The paper proposes a CBIR technique based on color feature extraction, where the queried image is divided into parts and color features are extracted to form a feature vector, which is then compared to feature vectors of images in the database to find similar images.
- The technique currently only uses color as the feature for similarity comparison, which limits its effectiveness, so future work involves combining multiple features like texture and shape for more accurate image retrieval.
1) The WHO Solidarity Trial studied the effects of Remdesivir and other drugs on over 11,000 COVID-19 patients across 30 countries. It found no statistically significant difference in mortality between the Remdesivir and control groups.
2) However, the reviewer notes some limitations with the trial design, including a lack of standardization across sites and incomplete reporting of important baseline characteristics and co-interventions between groups.
3) Given the limitations and preliminary nature of the results, the reviewer believes it is too early to change clinical practice and recommends continuing Remdesivir use selectively until more definitive data is available.
1) Diabetes mellitus affects approximately 5-8% of the population and is a leading cause of death, blindness, and renal failure. There are two main types: type 1 usually develops before age 30 and requires insulin therapy, while type 2 usually develops after age 40 and may be managed with diet and oral medications.
2) Insulin regulates carbohydrate, fat, and protein metabolism. In diabetes, insulin deficiency leads to hyperglycemia, glucosuria, dehydration, and ketosis. Various insulin preparations including short-acting, intermediate-acting, and long-acting types are used to treat diabetes.
3) Oral medications for type 2 diabetes include sulfonylureas, metformin
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow, releases endorphins, and promotes changes in the brain which help enhance one's emotional well-being and mental clarity.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like depression and anxiety.
1) The WHO Solidarity Trial studied the effects of Remdesivir and other drugs on over 11,000 COVID-19 patients across 30 countries. It found no statistically significant difference in mortality between the Remdesivir and control groups.
2) However, the reviewer notes some limitations with the trial design, including a lack of standardization across sites and incomplete reporting of important baseline characteristics and co-interventions between groups.
3) Given the limitations and preliminary nature of the results, the reviewer believes it is too early to change clinical practice and recommends continuing Remdesivir use selectively until more definitive data is available.
This document provides a summary and critical appraisal of a clinical trial on the use of remdesivir in treating COVID-19. The trial involved over 1,000 patients from sites across 10 countries who received either remdesivir or a placebo. Patients who received remdesivir had a median recovery time that was 5 days shorter than those who received the placebo. Remdesivir was also found to improve clinical status at day 15 and reduce mortality, with an estimated number needed to treat of 26 to prevent one death. The appraisal found the trial to have very good internal and external validity. Based on the consistent benefits shown, the author would recommend using remdesivir to treat eligible COVID-19 patients.
This document discusses several psychological tests and scales:
- The Leader Behaviour Scale measures six dimensions of leader behavior: emotional stability, team building, performance orientation, potential extraction, social intelligence, and value inculcation.
- The Quality of Work-life Scale measures 10 factors related to an employee's satisfaction with personal and work needs.
- The Sodhi Attitude Scale measures the attitudes of students toward teachers, parents, discipline, community, country, and religion.
- The Comprehensive Interest Scale helps identify interests in eight vocational areas like administration, defense, creative arts, medicine, computing, education, nature, and clerical work.
- The Asha Job Satisfaction Scale
This document discusses Energy-Karezza, a technique for prolonged and intimate sexual activity between partners without male ejaculation. It claims that practicing Karezza can increase sexual pleasure and intimacy for both partners, strengthen marital bonds, improve male self-confidence and endurance, and allow for deeper spiritual experiences. The document provides a manual for performing Karezza, including techniques for controlling arousal and prolonging sexual activity through specific movements, positions, and methods of handling arousal. It also discusses the historical roots of Karezza and reasons why avoiding ejaculation may be beneficial.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
1. SET CONFERENCES 2016
SCOPE M.sc (CS)
Project guide by: Students Reg No:
Mr. R.Rajkumar 15msc0015
SCOPE Bio Informatics HOD 15msc0017
Mail id: rrajkumar@vit.ac.in 15msc0034
VIT UNIVERSITY
2. Remote health monitoring systems using Wearable Body Sensors
Abstract:
Monitoring of physical, environmental conditions can be done by using Wireless sensor
network (WSN). In recent times WSN is found its application in healthcare and healthcare
management system. This study is done for the use of WSN in providing real-time feedback
to the user as well as the medical staff. For this study medical sensors were employed in order
to collect and monitor various physiological data and vital signs of cardiovascular disease
(CVD’s) patients for the efficient response to emergency conditions and the transmission of
signals to medical server and intelligent personal digital assistant (IPDA) through optical
cables and 4G communications respectively. Lightweight medical sensors such as Holter
monitor also known as ambulatory electrocardiography device can be used to create a
wireless body area network (WBAN) so that vital health signs can be monitored efficiently.
In the present study we propose the use of Medical Super Sensor to collect data sensed by the
sensors and transfer the information to a cloud server where the data can be accessed by the
medical staff from distant locations.
Keywords: Wireless sensor network, Holter monitor, Wireless body area networks,
intelligent personal digital assistant systems.
Introduction:
Recently, Wireless sensor networks (WSN) have been used in various fields such as
Environmental/Earth sensing, air pollution monitoring, forest fire detection, water quality
monitoring, healthcare management, military surveillance etc. WSN is widely used in
industries machine health monitoring, data logging, waste water monitoring etc. Recent
technology advances in manufacturing of microprocessors radio interface with single chip
have created a new league of wireless sensor networks which can be used in various fields.
Several nodes which are interconnected to each other which is connected to several sensors
comprises the WSN. The sensor consists of various parts such has microcontroller and radio
transceiver with an internal antenna or it is connected to an external antenna. Such a complex
yet efficient system makes WSNs a robust, fault tolerance system with an increase in spatial
coverage. This setup of WSN are contrary to the traditional sensor networks which were
developed in a predetermined manner. WSN can be used to track and monitor the health
3. conditions of patients in urban and rural areas. The use of WSN will decrease the work load
of the medical staff and also decrease the medical errors caused due to human negligence and
carelessness.
The mortality rate in hospitals can be decreased if the correct information is given to the
patient at the right time. In order to provide the correct information the medical staff and the
doctors should be having accurate information in the given period of time and the medical
staff should be able to access the information for any distances and there should be no delay
in receiving or the delivering of the information.In severe conditions of health crisis such as
heart attack the efficiency of the treatment provided to the patient can be improved if the staff
is able to access the previous reports of the patients. Therefore providing a secured and low
transmission latency to patient’s vital health signs are of importance in life threating diseases
like cardiovascular diseases (CVD), blood pressure, cancer etc. The placement of sensors can
be done on human body thus creating a network called a wireless body area network
(WBAN) this network can be used to collect patient’s vital signs.it must be noted that the
power consumption by the sensors takes place through battery and the amount of power
utilised is very minimal and there should be reliable data transfer between personal server and
WBAN.
With the use of sensors in combination with communication devices such as cell phones i.e
PDA General packet data service (GPRS), 4g and the internet the sensor network can keep
the caregivers, doctors and the medical staff well informed about the health condition of the
patient and also it can show the trends in the variation of vital health signs. The wireless
sensor network can also be referred to as wireless biomedical sensor network (WBSN) when
it is used in biomedical areas. When multiple sensors are connected to the body of individual
the network of such sensors can be called body sensor network (BSN).BSNs have major
advantages in healthcare management systems such as; since they are in close contact with
the body they can detect minute variation in the physiological condition of an individual and
report accurate results. Thus they can monitor efficiently. These sensors use minimal energy
and when such sensors are connected to a high efficiency communication device they can
help in the transmission of signals with low error rate. These sensors help in minimising the
work load of the hospital staff and also by the use of such sensors the physician can access
several reports of the patients at the same time. The sensor helps to categorize the data based
on the severity of the condition and hence it helps the doctor to give first preference to more
4. critical conditions. The sensor also helps the doctor and the medical staff to get access to the
patients profile from a distance place when the information is stored in a cloud network.
In the present study a proposal is made for the use of Medical Super Sensor (MSS) to collect
multiple physiological data which is sensed by the sensors of WBAN and forward it to a
cloud server. An Intelligent Personal Digital Assistant (IPDA) is used, this has the ability to
prioritize the data collected by the sensor and transfer it to the cloud server based of the
patient’s current health condition and content of the data.
Healthcare applications of wireless sensors:
The common applications of wireless sensors are as follows:
Diabetes mellitus:Diabetes mellitus involves the improper levels of glucose in the blood of
the patient. It is been reported the about 1.1 million people died due to this condition in the
year 2005. World Health Organization (WHO) also reported that 220 million people suffer
from this condition worldwide. Diabetes also causes series of other complications such has
kidney problem, heart disease, stroke, high blood pressure etc. Treatment includes insulin
injections, exercise and changes in eating habits.WBAN can to made use in this condition for
the efficient detection of glucose level and this method being less invasive is better preferred
for the accurate transferring of data collected.
Cardiovascular diseases : Cardiovascular diseases includes a large number of conditions
associated with heart and the vascular system. This includes high blood pressure, myocardial
infraction, block in the coronary artery, cardiac arrest etc. In these condition it is very
important that the vital signs are detected earlier and the treatment is administered as soon as
possible. It is mostly seen that the patient dies mostly when the signs are neglected in the
early stages.WBANs can be used to detect the changes in the pulse rate, heartbeat, the blood
pressure and transfer the data from the patient to the physician and also this can be prioritized
in order to alert the physician in case of emergency.
Asthma:Asthma involves uneasiness in breathing. This is majorly caused due to the allergens
present in the air. Hence air quality is very important and is a crucial condition for the well-
being of patients with this condition. WBANs as we know is used to sense the air quality and
pollution levels of air. When WBANs is combined with Global Positioning System (GPS)
which gives an exact location of the patient the air quality present in that location can be
5. sensed and the patient can be alerted about the situation hence proper care can be taken so
that no problem is caused to the patient.
Cancer Detection:Currently, cancer is considered as one of the biggest threats to human
kind. The number of cancer cases is been increased drastically. WBNs in combination with
other miniaturized sensors can be used in the diagnosis of cancer as the cancer cells express
distinct types of surface markers, enabling the physician to diagnose cancer patients with
better efficiency and accuracy.
Bone health:Usually women above 50 years of age are found to lose the deposited calcium
in their body and a condition called osteoporosis is caused. This condition can cause
complications such has fracture, lesser bone density, bone fragility etc.WBANs combined
with other sensors can be used to know the bone density and also check the amount of
calcium present in the body so this condition can be treated as early as possible.
Artificial Retina:Certain chips called as Optaelectronic Retina Prosthesis (ORP) could be
implanted in the rear part of human eye, this system can help blind individuals and people
with low vision to view normally.
System Architecture:
This describes the overview of the remote healthcare monitoring systems used for
cardiovascular diseases (CVD’s). This component consists of three tiers shown in the
Figure 1. This is composed of
1. Wearable body sensor
2. Personal Server (PPS) using PDA
3. Medical server connected to the cloud device
First tier:
This component is mainly the patient, it consists of different types of wearable body
sensors which is with the patient inorder to detect the physiological changes in the
body of the patient. In this case a Holter monitor is used with detects the heart
condition of patient the basic components of this system is as follows
6. Recorder
The span of the recorder varies relying upon the maker of the gadget. The normal
measurements of today's Holter screens are around 110x70x30 mm yet some are just
61x46x20 mm and weigh 99 g. Most of the gadgets work with two AA batteries. On the off
chance that the batteries are drained, a few Holters permit their substitution actually amid
checking. The vast majority of the Holters screen the ECG just in a few channels. Contingent
upon the model (maker), distinctive tallies of leads and lead frameworks are utilized. Today's
pattern is to minimize the quantity of prompts guarantee the persistent's solace amid
recording. Albeit 2/3 channel recording has been utilized for quite a while as a part of the
Holter checking history, as of late 12 channel Holters have showed up. These frameworks
utilize the fantastic Mason-Likar lead framework, hence creating the sign in the same
representation as amid the regular rest ECG and/or anxiety test estimation. These Holters then
permit to substitute anxiety test examination in cases the anxiety test is unrealistic for the
current patient. They are additionally suitable when examining patients after myocardial
localized necrosis. Recordings from these 12-lead screens are of an essentially lower
determination than those from a standard 12-lead ECG and now and again have been
demonstrated to give deluding ST section representation, despite the fact that a few gadgets
permit setting the inspecting recurrence up to 1000 Hz for unique reason exams like the late
potential.
An alternate intriguing development is the vicinity of a triaxial development sensor, which
records the patient physical action, and later shows in the product three separate statuses:
resting, remaining up, or strolling. This helps the cardiologist to better investigate the
recorded occasions having a place with the patient movement and journal. Holter checking is
an extremely helpful piece of an ECG. Some advanced gadgets additionally can record a
vocal patient journal entrance that can be later listened to by the specialist.
Analysing software:
At the point when the recording of ECG sign is done (for the most part following 24 or 48
hours), it is dependent upon the doctor to perform the sign examination. Since it would be to
a great degree time requesting to scan through such a long flag, there is a coordinated
programmed investigation transform in every Holter programming which naturally decides
7. distinctive sorts of heart thumps, rhythms, and so forth. However the achievement of the
programmed examination is nearly connected with the sign quality. The quality itself chiefly
relies on upon the connection of the terminals to the patient body. In the event that these are
not appropriately appended, electromagnetic aggravation can impact the ECG sign bringing
about an extremely loud record. In the event that the patient moves quickly, the mutilation
will be significantly greater. Such record is then exceptionally hard to process. Other than the
connection and nature of cathodes, there are different components influencing the sign
quality, for example, muscle tremors, testing rate and determination of the digitized sign
(superb gadgets offer higher examining recurrence). The programmed examination regularly
gives the doctor data about heart pulsated morphology, thumped interim estimation, heart rate
variability, musicality diagram and patient journal (minutes when the patient pressed the
patient catch). Progressed frameworks likewise perform otherworldly investigation, ischemic
trouble assessment, diagram of persistent's movement or PQ section examination. An
alternate necessity is the capacity of pacemaker discovery and examination. Such capacity is
helpful when one needs to check the right pacemaker capacity
8. Second Tier:
Personal server:
This is he server of the hospital in which the data of the patient is being stored. This server
can be accessed by registered family members of the patient, medical staff and the doctor.
Since, it is difficult to categorise each and every information this server is implemented with
Intelligent Personal Digital Assistant (IPDA) so that the major trends seen in the heart health
of the patient is viewed in the form of a graphical representation by the registered members of
the server.Certain cirtical signs are notified to the medical staff and the doctor. Hence, during
emergency the patient can be treated.
Priority Signaling and Data compression:
Since this is a wearable body sensor it has to be in contact with the patient most of the time
and the data which is colleced is consumes a huge amount of the storage space and
enoromous amount of data cannot to managed by the medical stff as a result even if the data
has certain important information, there is high chances that the data can be lost and the vital
signs can be negelted. Due to the above reasons we propose prioritising the data. Data such
has electrocardiograph, oxygen saturation, blood pressure and the pulse of the patient is given
importance. These data are given high traffic rate in the server. Other data which are thought
to be less imortant are given low data traffic. The high traffic dat are sent to the server via a
4G connection system whereas the data with less traffic are sent to the system via a 3G
connection system. In this manner the data collected can be effectively managed by the
medical staff and vital signs can be given high priority. Using this ysytem the data traffic can
be managed in an effeient manner.During emergency situation or when the trends of the heart
health is found be varying in a large amount, a notification is sent to the medical staff in
charge of the patient, when proper response is not given to such situation the notification is
also sent to the group of cardiologist doctors.
Third Tier:
This categry of the system architecture mainly deals with the communication system between
the family members of the patient, the medical staff and the group of cardiologist doctors.
During certain emergency condition when the patient is not present in the hospital, the IPDA
is programmed to send a notification to the ambulance system of the hosital with the exact
9. location of the patient. This is made possible with the help of a GPS system which is tagged
with the wearable body sensor. This module is also concerned with the communication
system between the medical staff and the group of cardiologist. In this system the doctor can
direct the medical staff with certain modes of treatment when the doctor is in a far distance.
However, such treatment must be given to the patient in the presence of an experienced
general physican. This module is also concerned with the data management system of the
cloud server. The data which is present in the local medical server must be deleted at regular
interval of time so that there is efficient utilization of the memory of the server. This can be
done only by the registered cardiologist doctor. The data which is found to be junk and is of
less importance for future use can be deleted by the doctor alone. However the data can be
deleted only in the local medical server. The cloud device will still contain the data, this data
can be managed future when the need arises.
Conclusion:
The above proposal ismainly with the view of treating cardiovascular patients in an effective
manner so that the mortality rate due to delayed treatment can be reduced. Since the mode of
communication is 4G the communication betwwen the patient and the doctor incharge of the
patient can be fast and the huge data generated by the wearable body sensors can be
effectively used for the treatment of the patient and the compressionof such data helps in less
memory utilization of the server and faster accessibility. Hence, this new technology can be
used to monitor the patient regularly and give a real-time feedback of the cardiovascular
health of the patient.
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