A study on “impact of artificial intelligence in covid19 diagnosis”Dr. C.V. Suresh Babu
Although the lungs are one of the most vital organs in the body, they are vulnerable to infection and injury. COVID-19 has put the entire world in an unprecedented difficult situation, bringing life to a halt and claiming thousands of lives all across the world. Medical imaging, such as X-rays and computed tomography (CT), is essential in the global fight against COVID-19, and newly emerging artificial intelligence (AI) technologies are boosting the power of imaging tools and assisting medical specialists. AI can improve job efficiency by precisely identifying infections in X-ray and CT images and allowing further measurement. We focus on the integration of AI with X-ray and CT, both of which are routinely used in frontline hospitals, to reflect the most recent progress in medical imaging and radiology combating COVID-19.
A study on “impact of artificial intelligence in covid19 diagnosis”Dr. C.V. Suresh Babu
A study on “Impact of Artificial Intelligence in COVID-19 Diagnosis”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
Insomnia analysis based on internet of things using electrocardiography and e...TELKOMNIKA JOURNAL
Insomnia is a disorder to start, maintain, and wake up from sleep, has many sufferers in the world. For patients in remote locations who suffer from insomnia, which requires testing, the gold standard performed requires patients to take the time and travel to the health care center. By making alternatives to remote sleep insomnia testing using electrocardiography and electromyography connected to the internet of things can solve the problem of patients' access to treatment. Delivery of patient data to the server is done to make observations from the visualization of patient data in real-time. Furthermore, using artificial neural networks was used to classify EMG, ECG, and combine patient data to determine patients who have Insomnia get resulted in patient classification errors around 0.2% to 2.7%.
A PROPOSED NEURO-FUZZY MODEL FOR ADULT ASTHMA DISEASE DIAGNOSIScscpconf
The task of medical diagnosis with the help different intelligent system techniques is always crucial because it require high level of accuracy and less time consumption in decision making.
Among all other AI techniques Artificial Neural Networks (ANN) as a tool for medical diagnosis has become the most popular in last few decades due to its flexibility and accuracy. ANN was
developed after getting the inspiration from biological neurons. There are various diseases that are still needed to be diagnosed. Among many other critical diseases like cancer, thyroid disorder, diabetes, heart diseases, neuro diseases, asthma disease was also tried to bediagnosed
effectively with various ANN mechanisms by different researchers. Due to various uncertainties about symptoms the study of Neuro-Fuzzy technique in this context became very popular in last few years. Neuro-Fuzzy now-a-days is one of the most advanced technique that is mainly concatenation of two model-neural networks and the fuzzy logic. In this model various
parameters are used that are much crucial if ill-chosen and may led to failure of the whole system. Recent trend in analysis is following this model for advanced expert work. In this study
an enhanced Neuro-fuzzy model has been proposed for the proper diagnosis of adult Asthma disease and to foster the proper aid or medication to the patients and make physicians alert forthe upcoming disease pattern otherwise they may lack in the process of providing improper medication at right time. In the first phase data collected from various hospitals are used to
train by three different types of learning of ANN like ANN with Self Organizing Maps (SOM),ANN with Learning Vector Quantization (LVQ) and ANN with Backpropagation Algorithm
(BPA) through NF tool for much accurate result. In the second phase fuzzy rule base is appliedto the classified data for the diagnosis of the disease.
A general framework for improving electrocardiography monitoring system with ...journalBEEI
As one of the most important health monitoring systems, electrocardiography (ECG) is used to obtain information about the structure and functions of the human heart for detecting and preventing cardiovascular disease. Given its important role, it is vital that the ECG monitoring system provides relevant and accurate information about the heart. Over the years, numerous attempts were made to design and develop more effective ECG monitoring system. Nonetheless, the literature reveals not only several limitations in conventional ECG monitoring system but also emphasizes on the need to adopt new technology such as machine learning to improve the monitoring system as well as its medical applications. This paper reviews previous works on machine learning to explain its key features, capabilities as well as presents a general framework for improving ECG monitoring system.
A study on the impact of data analytics in COVID-19 health care systemDr. C.V. Suresh Babu
Through the disperse of novel coronavirus illness globally, existence became considerably contrived. Data analytics have experienced powerful development over the past few years. As it happens, it’s exceptionally considerable to take advantage of data analytics to assist mankind in a prompt as well as factually precise method to forestall additionally restrain the advancement of the widespread, sustain gregarious balance and evaluate the influence of the widespread. The unforeseen significant number of coronavirus disease instances has disturbed medical care system in many economies furthermore eventuated in an insufficiency of dormitory in the hospices. For this reason, prognosticating quantity of coronavirus infection instances is indispensable for administrations to adopt the necessary measures. The count of coronavirus disease instances could be correctly anticipated by taking into account historical records of announced instances side by side few extraneous components that impact the disseminate of the COVID-19 . Hence, the principal aim out of this research is to contemporaneously consider historical data and the extraneous components. This paper explores how data analytics can play a role in health care especially in novel coronavirus illness.
A study on “impact of artificial intelligence in covid19 diagnosis”Dr. C.V. Suresh Babu
Although the lungs are one of the most vital organs in the body, they are vulnerable to infection and injury. COVID-19 has put the entire world in an unprecedented difficult situation, bringing life to a halt and claiming thousands of lives all across the world. Medical imaging, such as X-rays and computed tomography (CT), is essential in the global fight against COVID-19, and newly emerging artificial intelligence (AI) technologies are boosting the power of imaging tools and assisting medical specialists. AI can improve job efficiency by precisely identifying infections in X-ray and CT images and allowing further measurement. We focus on the integration of AI with X-ray and CT, both of which are routinely used in frontline hospitals, to reflect the most recent progress in medical imaging and radiology combating COVID-19.
A study on “impact of artificial intelligence in covid19 diagnosis”Dr. C.V. Suresh Babu
A study on “Impact of Artificial Intelligence in COVID-19 Diagnosis”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
Insomnia analysis based on internet of things using electrocardiography and e...TELKOMNIKA JOURNAL
Insomnia is a disorder to start, maintain, and wake up from sleep, has many sufferers in the world. For patients in remote locations who suffer from insomnia, which requires testing, the gold standard performed requires patients to take the time and travel to the health care center. By making alternatives to remote sleep insomnia testing using electrocardiography and electromyography connected to the internet of things can solve the problem of patients' access to treatment. Delivery of patient data to the server is done to make observations from the visualization of patient data in real-time. Furthermore, using artificial neural networks was used to classify EMG, ECG, and combine patient data to determine patients who have Insomnia get resulted in patient classification errors around 0.2% to 2.7%.
A PROPOSED NEURO-FUZZY MODEL FOR ADULT ASTHMA DISEASE DIAGNOSIScscpconf
The task of medical diagnosis with the help different intelligent system techniques is always crucial because it require high level of accuracy and less time consumption in decision making.
Among all other AI techniques Artificial Neural Networks (ANN) as a tool for medical diagnosis has become the most popular in last few decades due to its flexibility and accuracy. ANN was
developed after getting the inspiration from biological neurons. There are various diseases that are still needed to be diagnosed. Among many other critical diseases like cancer, thyroid disorder, diabetes, heart diseases, neuro diseases, asthma disease was also tried to bediagnosed
effectively with various ANN mechanisms by different researchers. Due to various uncertainties about symptoms the study of Neuro-Fuzzy technique in this context became very popular in last few years. Neuro-Fuzzy now-a-days is one of the most advanced technique that is mainly concatenation of two model-neural networks and the fuzzy logic. In this model various
parameters are used that are much crucial if ill-chosen and may led to failure of the whole system. Recent trend in analysis is following this model for advanced expert work. In this study
an enhanced Neuro-fuzzy model has been proposed for the proper diagnosis of adult Asthma disease and to foster the proper aid or medication to the patients and make physicians alert forthe upcoming disease pattern otherwise they may lack in the process of providing improper medication at right time. In the first phase data collected from various hospitals are used to
train by three different types of learning of ANN like ANN with Self Organizing Maps (SOM),ANN with Learning Vector Quantization (LVQ) and ANN with Backpropagation Algorithm
(BPA) through NF tool for much accurate result. In the second phase fuzzy rule base is appliedto the classified data for the diagnosis of the disease.
A general framework for improving electrocardiography monitoring system with ...journalBEEI
As one of the most important health monitoring systems, electrocardiography (ECG) is used to obtain information about the structure and functions of the human heart for detecting and preventing cardiovascular disease. Given its important role, it is vital that the ECG monitoring system provides relevant and accurate information about the heart. Over the years, numerous attempts were made to design and develop more effective ECG monitoring system. Nonetheless, the literature reveals not only several limitations in conventional ECG monitoring system but also emphasizes on the need to adopt new technology such as machine learning to improve the monitoring system as well as its medical applications. This paper reviews previous works on machine learning to explain its key features, capabilities as well as presents a general framework for improving ECG monitoring system.
A study on the impact of data analytics in COVID-19 health care systemDr. C.V. Suresh Babu
Through the disperse of novel coronavirus illness globally, existence became considerably contrived. Data analytics have experienced powerful development over the past few years. As it happens, it’s exceptionally considerable to take advantage of data analytics to assist mankind in a prompt as well as factually precise method to forestall additionally restrain the advancement of the widespread, sustain gregarious balance and evaluate the influence of the widespread. The unforeseen significant number of coronavirus disease instances has disturbed medical care system in many economies furthermore eventuated in an insufficiency of dormitory in the hospices. For this reason, prognosticating quantity of coronavirus infection instances is indispensable for administrations to adopt the necessary measures. The count of coronavirus disease instances could be correctly anticipated by taking into account historical records of announced instances side by side few extraneous components that impact the disseminate of the COVID-19 . Hence, the principal aim out of this research is to contemporaneously consider historical data and the extraneous components. This paper explores how data analytics can play a role in health care especially in novel coronavirus illness.
A study on “Diagnosis Test of Diabetics and Hypertension by AI”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
A study on “the impact of data analytics in covid 19 health care system”Dr. C.V. Suresh Babu
A Study on “The Impact of Data Analytics in COVID-19 Health Care System”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
A STUDY OF ELECTROMAGNETIC RADIATION EFFECTS FROM MOBILE PHONE BASE STATIONS ...IAEME Publication
Nowadays, several electrical appliances such as the radio, television, computer, microwave oven, mobile phone are inevitably involved with events in our lives. All of them commonly generate electromagnetic radiation of different frequencies, especially mobile phones, the fifth basic necessity which has recently become part of our everyday lives. During the last decade, the rate of mobile phone subscription has extensively increased to 6.8 million people in 2012 and tends to further increase to 9.7 million people worldwide by 2017. Therefore, it is required that the number of base stations for signal transmission through radiofrequency electromagnetic radiation be expanded by 1.4 so as to support the increasing consumption needs of the present. Such rise in the number of base stations may make people living nearby concerned about electromagnetic radiation effects on both short- and long-term health problems. In order to explain the previous studies of electromagnetic radiation effects on human body, this research focuses on the effects of electromagnetic radiation on various health aspects, i.e. an increase in body temperature, cancer incidence, and abnormalities at cellula r and DNA levels. All the contents in this paper can enable us to understand the overall picture of study and research methodologies from the past up to the present. This will lead to development of Thailand’s research in the future.
Wireless Transmission Of Spirometric… By Stephen A. Raymond, Ph DchallPHT
Wireless Transmission of Spirometric Measurements to ePRO Devices Used by Subjects with Asthma
by Stephen A. Raymond, PhD
Chief Scientific Officer and Founder
PHT Corporation
Medical Technology will save our minds and bodiesAshley Dibley
What is medical technology?
History of Medical Technology.
Advanced Medical Technology.
Pro's/Con's of Medical Technology
Different Types of Modern Medical Technology
Analysing Tuberculosis Trends in South Asia IJECEIAES
Tuberculosis (TB) has been one of the top ten causes of death in the world. As per the World Health Organization (WHO) around 1.8 million people have died due to tuberculosis in 2015. This paper aims to investigate the spatial and temporal variations in TB incident in South Asia (India, Bangladesh, Pakistan, Maldives, Nepal, and Sri-Lanka). Asia had been counted for the largest number of new TB cases in 2015. The paper underlines and relates the relationship between various features like gender, age, location, occurrence, and mortality due to TB in these countries for the period 1993-2012.
Wireless Body Area Networks for Healthcare: A Surveyijasuc
Wireless body area networks (WBANs) are emerging as important networks, applicable in various
fields. This paper surveys the WBANs that are designed for applications in healthcare. We present a
comprehensive survey consisting of stand-alone sections focusing on important aspects of WBANs. We
examine the following: monitoring and sensing, power efficient protocols, system architectures, routing
and security. We conclude by discussing some open research issues, their potential solutions and future
trends.
A study on “Diagnosis Test of Diabetics and Hypertension by AI”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
A study on “the impact of data analytics in covid 19 health care system”Dr. C.V. Suresh Babu
A Study on “The Impact of Data Analytics in COVID-19 Health Care System”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
A STUDY OF ELECTROMAGNETIC RADIATION EFFECTS FROM MOBILE PHONE BASE STATIONS ...IAEME Publication
Nowadays, several electrical appliances such as the radio, television, computer, microwave oven, mobile phone are inevitably involved with events in our lives. All of them commonly generate electromagnetic radiation of different frequencies, especially mobile phones, the fifth basic necessity which has recently become part of our everyday lives. During the last decade, the rate of mobile phone subscription has extensively increased to 6.8 million people in 2012 and tends to further increase to 9.7 million people worldwide by 2017. Therefore, it is required that the number of base stations for signal transmission through radiofrequency electromagnetic radiation be expanded by 1.4 so as to support the increasing consumption needs of the present. Such rise in the number of base stations may make people living nearby concerned about electromagnetic radiation effects on both short- and long-term health problems. In order to explain the previous studies of electromagnetic radiation effects on human body, this research focuses on the effects of electromagnetic radiation on various health aspects, i.e. an increase in body temperature, cancer incidence, and abnormalities at cellula r and DNA levels. All the contents in this paper can enable us to understand the overall picture of study and research methodologies from the past up to the present. This will lead to development of Thailand’s research in the future.
Wireless Transmission Of Spirometric… By Stephen A. Raymond, Ph DchallPHT
Wireless Transmission of Spirometric Measurements to ePRO Devices Used by Subjects with Asthma
by Stephen A. Raymond, PhD
Chief Scientific Officer and Founder
PHT Corporation
Medical Technology will save our minds and bodiesAshley Dibley
What is medical technology?
History of Medical Technology.
Advanced Medical Technology.
Pro's/Con's of Medical Technology
Different Types of Modern Medical Technology
Analysing Tuberculosis Trends in South Asia IJECEIAES
Tuberculosis (TB) has been one of the top ten causes of death in the world. As per the World Health Organization (WHO) around 1.8 million people have died due to tuberculosis in 2015. This paper aims to investigate the spatial and temporal variations in TB incident in South Asia (India, Bangladesh, Pakistan, Maldives, Nepal, and Sri-Lanka). Asia had been counted for the largest number of new TB cases in 2015. The paper underlines and relates the relationship between various features like gender, age, location, occurrence, and mortality due to TB in these countries for the period 1993-2012.
Wireless Body Area Networks for Healthcare: A Surveyijasuc
Wireless body area networks (WBANs) are emerging as important networks, applicable in various
fields. This paper surveys the WBANs that are designed for applications in healthcare. We present a
comprehensive survey consisting of stand-alone sections focusing on important aspects of WBANs. We
examine the following: monitoring and sensing, power efficient protocols, system architectures, routing
and security. We conclude by discussing some open research issues, their potential solutions and future
trends.
Performance Evaluation for Production of 5000kgHydraulic JackIOSR Journals
The report submitted presents detailed performance evaluation analysis for production of 5tonne
hydraulic jack. The main task is to produce it using two approaches namely conversional and reverse
engineering. Conversional design team were able to design the jack with all the necessary tolerance and limits,
those involve design calculations, producing standard drawing and cost analysis on each part involve. While
reverse engineering team were able to produce the jack through reverse engineering procedures and approach,
this involve selection of materials needed to produce the parts with our machines in the workshop, test analysis
for each component, assembling and testing to ensure effective performance
A gsm based intelligent wireless mobile patient monitoring systemeSAT Journals
Abstract Monitoring one’s heart rate and body temperature continuously from a remote area is impossible for a medical expert by using typical monitoring devices. To overcome this problem we can implement a GSM based system using microcontroller and LM35 sensor which is low-cost and use-friendly. Here, a heart beat sensor is used to detect the heart rate and an LM35 sensor to sense the body temperature. These signals are processed by a PIC microcontroller. Then, an SMS alert will be sent to the medical expert by using a GSM module. Thus, doctors can monitor the health condition of a patient continuously from a remote place and can suggest the patient about taking an immediate remedy. As a result, we can save many lives by providing them a quick service using this system. Keywords: Telemedicine, Remote monitoring system, Heart Beat Rate, Body Temperature, Photoplethysmograph, LM35, Microcontroller, GSM Modem etc…
Hypertension prediction using machine learning algorithm among Indonesian adultsIAESIJAI
Early risk prediction and appropriate treatment are believed to be able to
delay the occurrence of hypertension and attendant conditions. Many
hypertension prediction models have been developed across the world, but
they cannot be generalized directly to all populations, including for
Indonesian population. This study aimed to develop and validate a
hypertension risk-prediction model using machine learning (ML). The
modifiable risk factors are used as the predictor, while the target variable on
the algorithm is hypertension status. This study compared several machine-learning algorithms such as decision tree, random forest, gradient boosting,
and logistic regression to develop a hypertension prediction model. Several
parameters, including the area under the receiver operator characteristic area
under the curve (AUC), classification accuracy (CA), F1 score, precision,
and recall were used to evaluate the models. Most of the predictors used in
this study were significantly correlated with hypertension. Logistic
regression algorithm showed better parameter values, with AUC 0.829, CA
89.6%, recall 0.896, precision 0.878, and F1 score 0.877. ML offers the
ability to develop a quick prediction model for hypertension screening using
non-invasive factors. From this study, we estimate that 89.6% of people with
elevated blood pressure obtained on home blood pressure measurement will
show clinical hypertension.
Mining Health Examination Records A Graph Based Approachijtsrd
EHR Electronic Health Records collects data on yearly basis and it is used in many countries for healthcare.HER Health Examination Records collects the data on regular basis and identifies the participants at risk that is important for early warning and prevention.the fundamental challenge is for learning classification model for risk prediction with unlabelled data and live data string that established the majority of the collected dataset.the unlabelled data string describes the participants in health examintions whose health conditions can be vary from healthy to highly risky or very ill.in this paper, we propose a graph based,semisupervised learning algorithm called SHG health semi supervised heterogenous graph on Health for risk prediction and assessment to classify a progressively developing condition with the majority of the data unlabelled. An efficient iterative algorithm is designed and developed to proof the convergence is given.extensive experiments based on both real health examination dataset and live datasets to show effectiveness of our method. Jayashri A. Sonawane | Dr. Swati A. Bhavsar ""Mining Health Examination Records - A Graph Based Approach"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd22810.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/22810/mining-health-examination-records---a-graph-based-approach/jayashri-a-sonawane
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.
Chronic disease (CD) such as kidney disease and causes severe challenging issues to the people all around the world. Chronic kidney disease (CKD) and diabetes mellitus (DM) are considered in this paper. Predicting the diseases in earlier stage, gives better preventive measures to the people. Healthcare domain leads to tremendous cost savings and improved health status of the society. The main objective of this paper is to develop an algorithm to predict CKD occurrence using machine learning (ML) technique. The commonly used classification algorithms namely logistic regression (LR), random forest (RF), conditional random forest (CRF), and recurrent neural networks (RNN) are considered to predict the disease at an earlier stage. The proposed algorithm in this paper uses medical code data to predict disease at an earlier stage.
mHEALTH: REVIEW OF MOBILE HEALTH MONITORING SYSTEMSIAEME Publication
With rise in world population, cost of healthcare also increased rapidly which led to the demand of low cost health monitoring solutions. In recent times, non-invasive wearable sensors have played an important role in healthcare applications. With advancement in wireless communication technologies, ubiquitous computing and embedded systems, the sensors need not be invasive anymore to accurately monitor a patient's health status, rather can be managed by user itself so as to keep a record of one's health condition. The advancement of healthcare technologies has enabled patients to monitor their vital health parameters on their own, and saves them from regular tiring hospital visits & high cost of laboratory medical checkups. It has also reduced the burden of healthcare service providers, thereby reducing overall medical costs. This paper provides a review of current status of mobile healthcare applications.
An Intelligent Healthcare Serviceto Monitor Vital Signs in Daily Life – A Cas...IJERA Editor
Vital signs monitoring for elderly in daily life environment is a promising concept that efficiently can provide medical services to people at home. However, make the system self-served and functioning as personalized provision makes the challenge even larger. This paper presents a case study on a Health-IoT system where an intelligent healthcare service is developed to monitor vital signs in daily life. Here, a generic Health-IoT framework with a Clinical Decision Support System (CDSS) is presented. The generic framework is mainly focused on the supporting sensors, communication media, secure and safe data communication, cloud-based storage, and remote accesses of the data. The CDSS is used to provide a personalized report on persons‟ health condition based on daily basis observation on vital signs. Six participants, from Spain (n=3) and Slovenia (n=3) have been using the proposed healthcare system for eight weeks (e.g. 300+ health measurements) in their home environments to monitor their health. The sensitivity, specificity and overall accuracy of the DSS‟s classification are achieved as 90%, 97% and 96% respectively while k=2 i.e., top 2 most similar retrieved cases are considered. The initial user evaluation resultdemonstrates the feasibility and performance of the implemented system through the proposed framework.
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.
Detection of myocardial infarction on recent dataset using machine learningIJICTJOURNAL
In developing countries such as India, with a large aging population and limited access to medical facilities, remote and timely diagnosis of myocardial infarction (MI) has the potential to save the life of many. An electrocardiogram is the primary clinical tool utilized in the onset or detection of a previous MI incident. Artificial intelligence has made a great impact on every area of research as well as in medical diagnosis. In medical diagnosis, the hypothesis might be doctors' experience which would be used as input to predict a disease that saves the life of mankind. It is been observed that a properly cleaned and pruned dataset provides far better accuracy than an unclean one with missing values. Selection of suitable techniques for data cleaning alongside proper classification algorithms will cause the event of prediction systems that give enhanced accuracy. In this proposal detection of myocardial infarction using new parameters is proposed with increased accuracy and efficiency of the existing model. Additional parameters are used to predict MI with more accuracy. The proposed model is used to predict an early diagnosis of MI with the help of expertise experiences and data gathered from hospitals.
Review on hypertension diagnosis using expert system and wearable devicesIJECEIAES
The popularity of smartphones and wearable devices is increasing in the global market. These devices track physical exercise records, heartbeat, medicines, and self-health diagnosis. The wearable devices can also collect personal health parameters include hypertension diagnosis. Hypertension is one of the risk factors for cardiovascular-related diseases among the Malaysian population. Many mobile applications are paired with wearable devices to monitor health conditions, but none of them able to diagnose hypertension. In this study, we reviewed research papers that focused on hypertension using expert systems and wearable devices. We performed a systematic literature review based on hypertension factors, expert systems, and wearable devices. We found 15 specific research papers after the filtering process. The key findings highlighted three main focuses, which are the factors of hypertension, the expert system techniques, and the types of sensors in wearable devices. Blood pressure is the most common factor of hypertension that can be collected by wearable devices. As for the expert system techniques, we determined the three most common techniques are machine learning, neural network, and fuzzy logic. Lastly, the wrist band is the most common sensor for wearable devices in hypertension-related research.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
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Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Integrated E-Health Approach For Early Detection of Human Body Disorders in Real-Time
1. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE)
e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 5, Issue 4 (May. - Jun. 2013), PP 29-33
www.iosrjournals.org
www.iosrjournals.org 29 | Page
Integrated E-Health Approach For Early Detection of Human
Body Disorders in Real-Time
Ms.Renu Ravi1
, Mrs.K.Vanmathi2
1
(PG Scholar (EEE), Hindusthan College of Engineering and Technology, Coimbatore)
2
(Asst.Professor(EEE), Hindusthan College of Engineering and Technology, Coimbatore)
Abstract: Largest ever study of deaths show that heart ailments and respiratory failure have replaced
communicable diseases as the biggest killer in rural and urban areas of the country. Population based studies in
the youth show that the precursors of heart disease start in adolescence. In order to stem the tide of these
diseases, early detection and primary prevention is needed. Early detection and primary prevention starts with
education and awareness that these diseases poses the greatest threat and measures to prevent or reverse this
disease must be taken. Here comes the need for automatic disease detection technique that would aid the
physicians in an early detection of human body abnormalities. Heart rate, respiration and body temperature of
the subjects are collected and testing is done using samples from reference database. All these three parameters
are monitored using different sensors and these measured values are transferred to the PC using ZigBee that
provides wireless transfer of data. As a result the patient health status can be acquired, monitored and
synthesized immediately in a clear and easy way. The simulations are done using LabView software.
Keywords: atherosclerosis, e-Health, low cost approach, monitoring, patient specific health care, wireless
transfer.
I. INTRODUCTION
Due to certain myths and misconceptions, most of the people do not come out in the open to get
themselves diagnosed and treated. In case of people who believe that all these diseases are fatal, contagious,
genetic and that it can’t be treated, death becomes inevitable. Since the population mainly belongs to an
intermediate risk group, conventional risk factors have low predictive power and here comes the necessity for
the integrated e-health approach for early detection of human body disorders. Health care practice supported by
electronic processes and communication, dating back to at least 1999 is termed e-health. In other words it is the
health [1] care practices using the internet.
Early detection is the key to successfully treating most types of disorders. Early disease detection is the
use of screening tests to find health problems before symptoms appear. It can also be defined as diagnostic tests,
medical examinations, and self-examinations to detect a disease or other health problem early in its course.
Early disease detection is made use of due to many reasons. Often, the earlier a disease is diagnosed,
the more sooner it can be cured or successfully handled. Dealing with a disease, especially early in its course,
may lower its impact on our life, prevent or delay serious complications. The tests suggested for early detection
of human body disorders depend on the age, health, and gender. Often, they also depend on the risk factors.
The risk factors may include age, family history, smoking habits etc. When and how often screening tests should
be done may depend on the age, gender, family history, health status, lifestyle, and the cost of testing. Certain
screening times can be scheduled based on expert guidelines. In some cases, testing is also done as part of a
routine checkup. Here body parameters like heart rate, respiration and body temperature are being monitored
using noninvasive techniques. This detection by means of noninvasive techniques for the evaluation of structural
and/or functional parameters could provide a major opportunity in the early diagnosis and prevention of human
body diseases.
Cardiovascular diseases, CVD [2]-[5] is a class of diseases that affects the cardiovascular system and
its associated blood vessels. Most CVDs reflect chronic conditions while some may be acute events such as
heart attacks and strokes. The process of atherosclerosis evolves over decades, and begins as early as childhood.
However, most adolescents are more concerned about other risks such as cancer, HIV and accidents than
cardiovascular disease. The most recent studies show that 1 in 3 people will die from complications attributable
to atherosclerosis. Heart Rate and Heart Rate Variability are important measures that reflect the state of the
cardiovascular system. HRV analysis which is a non invasive measurement has gained prominence in the field
of cardiology for detecting CVDs. Thus CVD detection by means of non invasive evaluation of structural or
functional vascular parameters could provide a major opportunity in the early diagnosis and prevention of
cardiovascular diseases.
Respiration monitoring is one of the most important elements of accessing the physiological state.
Respiration failure can be difficult to predict. In just a few minutes life-threatening conditions can arise. So by
2. Integrated E-Health Approach For Early Detection of Human Body Disorders in Real-Time
www.iosrjournals.org 30 | Page
monitoring the chest movement continuous measurement and free access to all vital organs can be done. This
makes possible the measurement of not only the respiratory signal frequency but also the analysis of the
patients’ respiratory cycle. This non invasive evaluation of respiration helps in early diagnosis and prevention of
respiratory accidents with an advantage of providing reliable and accurate information about the extent of
respiratory motion magnitude.
Any abnormalities in human body cause a variation to the normal body temperature. This is one of the
most easily detectable changes that occur initially. As a result body temperature is also measured using different
sensors [6].
II. Block Diagram
Fig.1 Block diagram
Wireless communication systems have been gaining popularity as it provides mobility and
convenience. Development in this technology has given rise to numerous options of data transfer with coverage
ranging from a few meters to thousand kilometers.
Zigbee can be defined as a low cost, low power, wireless mesh network standard. It is used in mesh
network form to transmit data over longer distances. This data is passed through intermediate devices so that it
can reach more distant ones. It is targeted at applications that require a long battery life, secure networking and
low data rate. Zigbee also provides short range wireless transfer of data at relatively low rates. It is simpler and
less expensive than WPANs such as Bluetooth. Another advantage of using Zigbee is that it provides large
network capacity and saves power. RS232 provides connection between a Data Terminal Equipment (DTE) and
a Data Circuit Terminating Equipment (DCE). Is is commonly used in computer serial ports. RS232 can also be
used as a standard for serial binary single-ended data and control signals.
III. Simulation Model
Heart Beat
Fig. 2 Heart beat simulation model
3. Integrated E-Health Approach For Early Detection of Human Body Disorders in Real-Time
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Respiration
Fig. 3 Respiration simulation model
Body Temperature
Fig. 4 Body temperature simulation model
Heart rate, respiration and body temperature of the subjects are monitored using different sensors [6]
and these measured values are transferred to the PC using zigbee that provides wireless [7] transfer of data. As a
result the patient health status can be acquired, monitored and synthesized immediately in a clear and easy way.
The simulation is done using labview.
The normal values for heart rate, respiration and body temperature are earlier fed into the system. The
measured values of the subject’s heart rate, respiration rate and body temperature [8] are then loaded into the
system. All the three parameters including heart rate, respiration rate and body temperature acquired using
different sensors are then tested using samples from the reference database. If the measured value of the subject
differ from the normal value then there will be an indication showing that the parameter of the subject under
analysis is abnormal. Healthy subjects show no difference between calculated and estimated risk values.
Repeatable non-invasive technology is being used for this purpose. Thus detection by means of noninvasive
techniques for the evaluation of structural and/or functional parameters provides a major opportunity in the early
diagnosis and prevention of human body diseases and also improves patient specific diagnosis.
IV. Results And Discussion
Heart Rate
4. Integrated E-Health Approach For Early Detection of Human Body Disorders in Real-Time
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Respiration
Body Temperature
Fig. 5 Simulation results
The signals for heart rate, respiration and body temperature are monitored for further evaluation. The
signal conditioning, classification and user-interface of these recorded signals is implemented in software using
Labview 8.6. The main advantage is that multiple parameters can be monitored at a time. The parameters
including heart rate, respiration and body temperature can be acquired, monitored and immediately synthesized
in a clear and easy way by considering a minimum amount of data. All these provide benefits of patient specific
monitoring and treatment support tools for early detection of human body disorders. More over this can be made
use at our own convenience using computer aided instruction [9-13]. The introduction to wireless connections
to exchange sensor’s data also provides a great flexibility for both patient and medical staff. Moreover low cost
and repeatable noninvasive technology is justified.
V. Conclusion
The main advantage of this paper is the benefit of patient specific monitoring and treatment support
tools for early detection of human body disorders. Its recommendations should not be used as a basis for
delaying, or else as a substitute for, evaluation and treatment by a physician. Leading a healthy lifestyle and also
paying heed to the suggestions of experts is recommended. Higher awareness among people are required in
order to avoid undue advantage of the patient’s desperation. They should be aware that health decisions should
not be based on hope and desperation but should be rational and practical.
The work presented is aimed for the early detection and prevention of human body abnormalities in
real-time.
Acknowledgement
Authors would like to thank all the researchers who have contributed in this field of research. The
comments of anonymous reviewers to improve the quality of this paper are also acknowledged.
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