Model Monitoring Physical Exercise Heart Rate Using Internet of Things (MMPEH-IOT) has
been developed and designed with its integral functionalities exposing through the six model
components: SmartHeart, WNEt, SoftAPP, Knowledgebase, Server and User interface. The model
was designed using Unified Modeling Language (UML) sequence diagram, identifying objects
exchanging messages. The model forecasts future benefits into smart devices and Internet of
Things (IoT).
IRJET- IoT based Smart Fitness Tracker for GymnasiumsIRJET Journal
This document summarizes a research project that aims to design a smart fitness tracker system for gymnasiums. The system would record users' indoor fitness routines by automatically counting sets and repetitions of weight exercises using sensors, rather than manual counting. It would distinguish members using RFID tags and update individual data on a fitness tracking app and database. The system is intended to provide accurate logging of data and suggestions on progress to help users set goals. It would classify as green IT by using cloud services.
IRJET- Human Activity Recognition using Flex SensorsIRJET Journal
This document discusses a system for human activity recognition using flex sensors. Flex sensors are attached to the body and can detect movements. The flex sensor data is fed into a neural network model to recognize activities. The model is trained using flex sensor data from various human activities. The trained model can then accurately recognize activities based on new flex sensor input data. The system is meant to help elderly people or those with disabilities by allowing them to control devices with body movements detected by flex sensors. It aims to provide a modular system that can adapt to new users and disabilities. Flex sensors make the system customizable while neural networks enable accurate activity recognition.
1) The document describes an IoT-based e-prognosis system that monitors patients' temperature and heartbeat using sensors. The sensors send the medical data over the Internet to be accessed by medical professionals.
2) If the system detects a constant rise in the patient's temperature, it will diagnose the issue and send treatment information and remedies to the patient, caretaker, or doctor via IoT.
3) The system is meant to help disabled or elderly people who need monitoring but may not have constant caretaker assistance. It allows remote monitoring using wearable sensors connected to the Internet.
Application of Big Data Analysis and Internet of Things to the Intelligent Ac...gerogepatton
With the advent and rising usage of Internet of Things (IoT) eco-systems, there is a consequent, parallel
rise in opportunities where technology can find its place to improve a number of human conditions.
However, this is nothing new - we have been perfecting the usage of tools to aid our daily living
throughout history. The true evolution lies in the interaction between us and the tools we create. Tools
are now smart devices, yielding an opportunity where human-device interaction is giving us the very
knowledge on how to improve that particular synthesis. From improving our fitness to detecting
bradycardia and response of traumatic brain injury patient, we have come to a point where we are able
to gain actionable insight into a lot of aspects of our health and condition. This creates a certain
autonomy in understanding the unique make-up of every single person, in addition to yielding
information that can be used by health practitioners to help in diagnosis, determination of medical
approach and right recovery and follow-up methods. All of this supported by two major factors: IoT
platforms and Big Data Analysis (BDA).
This paper takes a deep dive into exemplary set-up of IoT platform and BDA framework necessary to
support the improvement of human condition. Our SmartLeg prosthetic device integrates advanced
prosthetic and robotic technology with the state-of-the-art machine learning algorithms capable of
adapting the working of the prosthesis to the optimal gait and power consumption patterns, which
provide means to customize the device to a particular user.
APPLICATION OF BIG DATA ANALYSIS AND INTERNET OF THINGS TO THE INTELLIGENT AC...ijaia
With the advent and rising usage of Internet of Things (IoT) eco-systems, there is a consequent, parallel rise in opportunities where technology can find its place to improve a number of human conditions. However, this is nothing new - we have been perfecting the usage of tools to aid our daily living throughout history. The true evolution lies in the interaction between us and the tools we create. Tools are now smart devices, yielding an opportunity where human-device interaction is giving us the very knowledge on how to improve that particular synthesis. From improving our fitness to detecting bradycardia and response of traumatic brain injury patient, we have come to a point where we are able to gain actionable insight into a lot of aspects of our health and condition. This creates a certain autonomy in understanding the unique make-up of every single person, in addition to yielding information that can be used by health practitioners to help in diagnosis, determination of medical approach and right recovery and follow-up methods. All of this supported by two major factors: IoT platforms and Big Data Analysis (BDA).
This paper takes a deep dive into exemplary set-up of IoT platform and BDA framework necessary to support the improvement of human condition. Our SmartLeg prosthetic device integrates advanced prosthetic and robotic technology with the state-of-the-art machine learning algorithms capable of adapting the working of the prosthesis to the optimal gait and power consumption patterns, which provide means to customize the device to a particular user.
APPLICATION OF BIG DATA ANALYSIS AND INTERNET OF THINGS TO THE INTELLIGENT AC...gerogepatton
This document discusses applying big data analysis and internet of things technologies to develop an intelligent, active robotic prosthesis for transfemoral amputees. It proposes integrating advanced prosthetic and robotic technologies with machine learning algorithms to customize a prosthesis to a user. Sensors would collect data on the prosthesis's usage, which would be analyzed using big data techniques to adapt the prosthesis's operation to optimal gait and power consumption patterns for individual users. The system aims to provide customized control of the prosthesis's knee and ankle joints through onboard actuators powered by an external source to assist with activities like stair climbing.
An intelligent approach to take care of mother and baby healthIJECEIAES
This is the era of technology and is widely used in every sector. In Bangladesh the use of technology is increasing day by day in many sectors. Health sector is one of them. This research is designed and developed to help the pregnant women to get weekly information on development and conditions of their health and the growing child inside their womb. This system will notify expectant mothers automatically about their health checkup date and time. It provides general and special health information to the expectant mothers. It is designed with user friendly interface so that an expectant mother can use this system very effectively. This system allows a unique secure login system and provides a unique suggestion to the expectant mothers.This system is very user friendly and useful.
IRJET- Predicting Heart Disease using Machine Learning AlgorithmIRJET Journal
1) The document discusses using machine learning algorithms like Naive Bayes and Decision Trees to predict heart disease using a dataset from Kaggle.
2) It describes preprocessing the dataset, training models, and evaluating accuracy. Decision Trees were found to more accurately predict heart disease than Naive Bayes.
3) The models use 13 attributes like age, sex, cholesterol levels, and examine classification performance to identify individuals at risk of heart disease.
IRJET- IoT based Smart Fitness Tracker for GymnasiumsIRJET Journal
This document summarizes a research project that aims to design a smart fitness tracker system for gymnasiums. The system would record users' indoor fitness routines by automatically counting sets and repetitions of weight exercises using sensors, rather than manual counting. It would distinguish members using RFID tags and update individual data on a fitness tracking app and database. The system is intended to provide accurate logging of data and suggestions on progress to help users set goals. It would classify as green IT by using cloud services.
IRJET- Human Activity Recognition using Flex SensorsIRJET Journal
This document discusses a system for human activity recognition using flex sensors. Flex sensors are attached to the body and can detect movements. The flex sensor data is fed into a neural network model to recognize activities. The model is trained using flex sensor data from various human activities. The trained model can then accurately recognize activities based on new flex sensor input data. The system is meant to help elderly people or those with disabilities by allowing them to control devices with body movements detected by flex sensors. It aims to provide a modular system that can adapt to new users and disabilities. Flex sensors make the system customizable while neural networks enable accurate activity recognition.
1) The document describes an IoT-based e-prognosis system that monitors patients' temperature and heartbeat using sensors. The sensors send the medical data over the Internet to be accessed by medical professionals.
2) If the system detects a constant rise in the patient's temperature, it will diagnose the issue and send treatment information and remedies to the patient, caretaker, or doctor via IoT.
3) The system is meant to help disabled or elderly people who need monitoring but may not have constant caretaker assistance. It allows remote monitoring using wearable sensors connected to the Internet.
Application of Big Data Analysis and Internet of Things to the Intelligent Ac...gerogepatton
With the advent and rising usage of Internet of Things (IoT) eco-systems, there is a consequent, parallel
rise in opportunities where technology can find its place to improve a number of human conditions.
However, this is nothing new - we have been perfecting the usage of tools to aid our daily living
throughout history. The true evolution lies in the interaction between us and the tools we create. Tools
are now smart devices, yielding an opportunity where human-device interaction is giving us the very
knowledge on how to improve that particular synthesis. From improving our fitness to detecting
bradycardia and response of traumatic brain injury patient, we have come to a point where we are able
to gain actionable insight into a lot of aspects of our health and condition. This creates a certain
autonomy in understanding the unique make-up of every single person, in addition to yielding
information that can be used by health practitioners to help in diagnosis, determination of medical
approach and right recovery and follow-up methods. All of this supported by two major factors: IoT
platforms and Big Data Analysis (BDA).
This paper takes a deep dive into exemplary set-up of IoT platform and BDA framework necessary to
support the improvement of human condition. Our SmartLeg prosthetic device integrates advanced
prosthetic and robotic technology with the state-of-the-art machine learning algorithms capable of
adapting the working of the prosthesis to the optimal gait and power consumption patterns, which
provide means to customize the device to a particular user.
APPLICATION OF BIG DATA ANALYSIS AND INTERNET OF THINGS TO THE INTELLIGENT AC...ijaia
With the advent and rising usage of Internet of Things (IoT) eco-systems, there is a consequent, parallel rise in opportunities where technology can find its place to improve a number of human conditions. However, this is nothing new - we have been perfecting the usage of tools to aid our daily living throughout history. The true evolution lies in the interaction between us and the tools we create. Tools are now smart devices, yielding an opportunity where human-device interaction is giving us the very knowledge on how to improve that particular synthesis. From improving our fitness to detecting bradycardia and response of traumatic brain injury patient, we have come to a point where we are able to gain actionable insight into a lot of aspects of our health and condition. This creates a certain autonomy in understanding the unique make-up of every single person, in addition to yielding information that can be used by health practitioners to help in diagnosis, determination of medical approach and right recovery and follow-up methods. All of this supported by two major factors: IoT platforms and Big Data Analysis (BDA).
This paper takes a deep dive into exemplary set-up of IoT platform and BDA framework necessary to support the improvement of human condition. Our SmartLeg prosthetic device integrates advanced prosthetic and robotic technology with the state-of-the-art machine learning algorithms capable of adapting the working of the prosthesis to the optimal gait and power consumption patterns, which provide means to customize the device to a particular user.
APPLICATION OF BIG DATA ANALYSIS AND INTERNET OF THINGS TO THE INTELLIGENT AC...gerogepatton
This document discusses applying big data analysis and internet of things technologies to develop an intelligent, active robotic prosthesis for transfemoral amputees. It proposes integrating advanced prosthetic and robotic technologies with machine learning algorithms to customize a prosthesis to a user. Sensors would collect data on the prosthesis's usage, which would be analyzed using big data techniques to adapt the prosthesis's operation to optimal gait and power consumption patterns for individual users. The system aims to provide customized control of the prosthesis's knee and ankle joints through onboard actuators powered by an external source to assist with activities like stair climbing.
An intelligent approach to take care of mother and baby healthIJECEIAES
This is the era of technology and is widely used in every sector. In Bangladesh the use of technology is increasing day by day in many sectors. Health sector is one of them. This research is designed and developed to help the pregnant women to get weekly information on development and conditions of their health and the growing child inside their womb. This system will notify expectant mothers automatically about their health checkup date and time. It provides general and special health information to the expectant mothers. It is designed with user friendly interface so that an expectant mother can use this system very effectively. This system allows a unique secure login system and provides a unique suggestion to the expectant mothers.This system is very user friendly and useful.
IRJET- Predicting Heart Disease using Machine Learning AlgorithmIRJET Journal
1) The document discusses using machine learning algorithms like Naive Bayes and Decision Trees to predict heart disease using a dataset from Kaggle.
2) It describes preprocessing the dataset, training models, and evaluating accuracy. Decision Trees were found to more accurately predict heart disease than Naive Bayes.
3) The models use 13 attributes like age, sex, cholesterol levels, and examine classification performance to identify individuals at risk of heart disease.
This document describes a proposed healthy sport monitoring system that uses wearable biometric sensors and wireless communication technologies. The system is intended to allow sports consultants to remotely monitor individuals' vital signs during physical activity in real-time. This would help consultants design safe and effective workout plans and identify any potential health issues. The system would use the Arduino and E-Health sensor platform to collect data from sensors measuring pulse, respiration, temperature and other biometrics. Data would be sent via 3G to an application where consultants can view readings, set limits, and generate reports. The goal is to encourage safe physical activity while reducing health monitoring costs.
Real-time Heart Pulse Monitoring Technique Using Wireless Sensor Network and ...IJECEIAES
This summarizes a document describing a real-time heart pulse monitoring system using a wireless sensor network and mobile application. The proposed system measures a patient's heart pulse using an infrared sensor. It then amplifies and filters the signal before sending it over a network using an Arduino board and Ethernet shield. The heart pulse values are displayed on both a computer-based and smartphone-based application in real-time. The system was tested on 10 people of varying ages, genders, and health statuses, and the results were within normal heart pulse ranges according to medical standards.
Framework for propagating stress control message using heartbeat based iot re...IJECEIAES
Abnormal level of stress is the root indicator factor to have significant impact over the health of heart and there is a close relationship between the stress levels with heart rate. Review of the existing literature showcase that there has been various work that has been carried out towards investigation of considering heart rate with an internet-of-things (IoT) system. Apart from this, existing system doesnt offer any instantaneous solution where certain intimation is offered in real-time to the user with wearables as a solution to control the stress condition. Therefore, the current paper introduces a novel framework where the sampled heart rates of the patients are captured by IoT deivices. The aggregated data are further forwarded to the cloud analytic system that uses correlation to extract the appropriate message. The system after being applied with teh machine learning approach could further extract the elite outcome followed by forwarding the contextual data to teh user. Using an analytical modelliig, the proposed system shows that it offers better accuracy and reduced processing time when compared with other machine learning approach and thereby it proves to be cost effective solution in IoT system over medical case study.
The heart is a vital organ that serves to pump blood to the whole body. A heart rate can be used as a healthy body parameter conditions. Growing evidence suggests that IT-based health records play essential role to drive medical revolution especially on data storage and processing. The heart rate measurement (HRM) process usually involves wearable sensor devices to record patient’s data. This data is recorded to help the doctors to analyze and provide a better diagnose in order to determine the best treatment for the patients. Connecting the sensor system through a wireless network to a cloud server will enable the doctor to monitor remotely. This paper presents fit-NES wearable bracelet, an alternative method for integrating a HR measurement device using optical based pulse sensor and Bluetooth-based communication module. This paper is also present the benchmarking of proposed system with several various commercial HR measurement devices.
IRJET- Review on: A Wireless IoT System for Gait Detection in Stroke PatientIRJET Journal
This document summarizes a proposed wireless IoT system for gait detection in stroke patients. The system would use sensors embedded in a smart shoe to discreetly monitor a patient's insole pressure and acceleration during walking. The data collected from the shoe sensors and a smartphone's built-in sensors would be used to detect any abnormal or cautious gait patterns that could predict risk of falling. The system aims to warn patients about risky gaits and potentially prevent injuries. It discusses how IoT and wireless communication could help create a portable system to continuously monitor patients' gaits outside of a clinical setting.
Applications of Sensors to Detect the Behavior of Human. A Survey PaperIRJET Journal
This document summarizes research on using sensors to detect human behavior. It discusses four papers that explored wearable sensors to monitor health signals, gesture recognition using data gloves, wireless body area networks of biosensors, and a homecare kit for multi-signal acquisition. The applications of these sensors include health monitoring, emergency response systems, transmitting emergency data from biosensors, and supporting medical care through daily signal measurement. Overall, the document reviews work using circuits and embedded systems to process sensor data and identify human behavior and feelings through technologies like smartwatches.
This document summarizes a research paper that designed a smart waist belt for health monitoring. The belt tracks steps, posture, heart rate and classifies activities using sensors and a random forest machine learning algorithm. It achieved high accuracy rates between 90-95% for classifying activities like sitting, walking and standing. The smart waist belt addresses issues with current fitness trackers and promotes an active lifestyle. It provides real-time health data to a mobile app and cloud for access and analysis. This allows users to conveniently self-monitor health metrics and get notifications about posture.
Development of a Home-based Wrist Rehabilitation System IJECEIAES
There are several factors that may result to wrist injuries such as athlete injuries and stroke. Most of the patients are unable to undergo rehabilitation at healthcare providers due to cost and logistic constraint. To solve this problem, this project proposes a home-based wrist rehabilitation system. The goal is to create a wrist rehabilitation device that incorporates an interactive computer game so that patients can use it at home without assistance. The main structure of the device is developed using 3D printer. The device is connected to a computer, where the device provides exercises for the wrist, as the user completes a computer game which requires moving a ball to four target positions. Data from an InvenSense MPU-6050 accelerometer is used to measure wrist movements. The accelerometer values are read and used to control a mouse cursor for the computer game. The pattern of wrist movements can be recorded periodically and displayed back as sample run for analysis purposes. In this paper, the usefulness of the proposed system is demonstrated through preliminary experiment of a subject using the device to complete a wrist exercise task based on the developed computer game. The result shows the usefulness of the proposed system.
Study of AI Fitness Model Using Deep LearningIRJET Journal
1. The document describes an AI fitness app called "AI Fitness Genie" that uses computer vision algorithms like YOLO and OpenPose to track a user's exercise poses, count repetitions, and provide feedback to improve form.
2. It detects body position using skeleton or contour modeling and compares the user's pose to 3D models to assess accuracy and provide recommendations for corrections.
3. An evaluation of the app found it could detect poses with 98.51% accuracy to guide users through proper exercise form.
IRJET- Review on: Virtual Assistant and Patient Monitoring System by usin...IRJET Journal
1) The document discusses a virtual assistant and patient monitoring system using artificial intelligence and data science. It analyzes different methodologies for health goals and allows patients to get medical assistance and reports anytime, anywhere.
2) The proposed system uses algorithms for disease recognition, abnormality detection, and prediction. It accurately and quickly analyzes patient data like ECG, blood pressure, and sugar levels that is stored on a server.
3) Experimental results showed the proposed method is more accurate and faster than traditional methods, allowing patients to access medical services remotely.
New methodology to detect the effects of emotions on different biometrics in...IJECEIAES
This document presents a new methodology to detect the effects of emotions on different biometrics in real time. Two designs were implemented based on a microcontroller and National Instruments myRIO to measure four vital parameters (temperature, heartbeat, blood pressure, body resistance) in real-time while recording the effects of different emotions on those parameters. Over 400 people were tested while exposed to videos and music representing different emotions. The results showed that the design using NI myRIO achieved more accurate results and faster response time compared to the microcontroller-based design, qualifying it for use in intensive care units. The methodology contributes to early diagnosis of diseases by analyzing the impact of emotions on vital readings.
The document describes a proposed IoT powered wearable health band system. The system would monitor an individual's health using sensors to detect depression, blood oxygen levels, blood pressure, temperature and pulse rate. Data from the health band would be sent to an Android application via Bluetooth. The app would analyze the data and send notifications to a guardian in emergency situations using algorithms like SVM. The system aims to provide more health information and warnings to users and caregivers.
This document describes an assistive technology (AT) for lower limb rehabilitation of post-stroke patients. The AT uses a Kinect sensor and surface electromyography sensor to provide real-time biofeedback to users during a virtual snowboarding game. The system was evaluated positively by users based on usability, functionality, and goal attainment scales. The AT shows potential for future clinical use in stroke rehabilitation.
IRJET- Web-based Application to Detect Heart Attack using Machine LearningIRJET Journal
This document presents a web-based application that uses machine learning to detect heart attacks. The application builds an interactive risk prediction system that calculates an individual's vulnerability to having a heart attack based on their risk factor. It analyzes medical data using classification algorithms like logistic regression and Naive Bayes to predict whether someone has a high or low risk of a heart attack. The results are displayed to users through a simple web interface, and alerts are sent to patients' phones. The goal is to automate risk prediction to reduce the time and effort required from doctors.
Activity and health monitoring systems
This paper presents an Open Platform Activity and health monitoring systems which are also called e-Health systems. These systems measure and store parameters that reflect changes in the human body. Due to continuous monitoring (e.g. in rest state and in physical effort state), a specialist can learn about the individual's physiological parameters. Because the human body is a complex system, the examiner can notice some changes within the body by looking at the physiological parameters. Six different sensors ensure us that the patient's individual parameters are monitored. The main components of the device are: A Raspberry Pi 3 small single-board computer, an e-Health Sensor Platform by Cooking-Hacks, a Raspberry Pi to Arduino Shields Connection Bridge and a 7-inch Raspberry Pi 3 touch screen. The processing unit is the Raspberry Pi 3 board. The Raspbian operating system runs on the Raspberry Pi 3, which provides a solid base for the software. Every examination can be controlled by the touch screen. The measurements can be started with the graphical interface by pressing a button and every measured result can be represented on the GUI’s label or on the graph. The results of every examination can be stored in a database. From that database the specialist can retrieve every personalized data
Emerging technologies like smartphones, wearable devices, virtual reality, big data, and cloud computing are enabling a more connected global healthcare system. Smartphones provide personalized health information and tools like medical apps. Wearable devices allow for continuous, unobtrusive health monitoring. Virtual reality and 3D gaming can simulate real-world medical scenarios for education and training. Big data, machine learning, and cloud computing collectively support unlimited data storage, advanced analytics, and on-demand access and sharing of healthcare information on a global scale. These emerging technologies are helping to transition the world toward more informed, connected, and effective healthcare.
Qadri et Al., en su trabajo “The Future of Healthcare Internet of Things (H-IoT): A Survey of Emerging Technologies” propone como uno de los desafíos del H-IoT:
Monitoreo de Desórdenes neurológicos
Ambient Assisted Living (AAL)
Fitness Tracking
Uso de técnicas de Big Data
Uso de Edge Computing
Internet of Nano-Things
A LOW COST EEG BASED BCI PROSTHETIC USING MOTOR IMAGERY ijitcs
Brain Computer Interfaces (BCI) provide the opportunity to control external devices using the brain
ElectroEncephaloGram (EEG) signals. In this paper we propose two software framework in order to
control a 5 degree of freedom robotic and prosthetic hand. Results are presented where an Emotiv
Cognitive Suite (i.e. the 1st framework) combined with an embedded software system (i.e. an open source
Arduino board) is able to control the hand through character input associated with the taught actions of
the suite. This system provides evidence of the feasibility of brain signals being a viable approach to
controlling the chosen prosthetic. Results are then presented in the second framework. This latter one
allowed for the training and classification of EEG signals for motor imagery tasks. When analysing the
system, clear visual representations of the performance and accuracy are presented in the results using a
confusion matrix, accuracy measurement and a feedback bar signifying signal strength. Experiments with
various acquisition datasets were carried out and with a critical evaluation of the results given. Finally
depending on the classification of the brain signal a Python script outputs the driving command to the
Arduino to control the prosthetic. The proposed architecture performs overall good results for the design
and implementation of economically convenient BCI and prosthesis.
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.
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
This document describes a proposed healthy sport monitoring system that uses wearable biometric sensors and wireless communication technologies. The system is intended to allow sports consultants to remotely monitor individuals' vital signs during physical activity in real-time. This would help consultants design safe and effective workout plans and identify any potential health issues. The system would use the Arduino and E-Health sensor platform to collect data from sensors measuring pulse, respiration, temperature and other biometrics. Data would be sent via 3G to an application where consultants can view readings, set limits, and generate reports. The goal is to encourage safe physical activity while reducing health monitoring costs.
Real-time Heart Pulse Monitoring Technique Using Wireless Sensor Network and ...IJECEIAES
This summarizes a document describing a real-time heart pulse monitoring system using a wireless sensor network and mobile application. The proposed system measures a patient's heart pulse using an infrared sensor. It then amplifies and filters the signal before sending it over a network using an Arduino board and Ethernet shield. The heart pulse values are displayed on both a computer-based and smartphone-based application in real-time. The system was tested on 10 people of varying ages, genders, and health statuses, and the results were within normal heart pulse ranges according to medical standards.
Framework for propagating stress control message using heartbeat based iot re...IJECEIAES
Abnormal level of stress is the root indicator factor to have significant impact over the health of heart and there is a close relationship between the stress levels with heart rate. Review of the existing literature showcase that there has been various work that has been carried out towards investigation of considering heart rate with an internet-of-things (IoT) system. Apart from this, existing system doesnt offer any instantaneous solution where certain intimation is offered in real-time to the user with wearables as a solution to control the stress condition. Therefore, the current paper introduces a novel framework where the sampled heart rates of the patients are captured by IoT deivices. The aggregated data are further forwarded to the cloud analytic system that uses correlation to extract the appropriate message. The system after being applied with teh machine learning approach could further extract the elite outcome followed by forwarding the contextual data to teh user. Using an analytical modelliig, the proposed system shows that it offers better accuracy and reduced processing time when compared with other machine learning approach and thereby it proves to be cost effective solution in IoT system over medical case study.
The heart is a vital organ that serves to pump blood to the whole body. A heart rate can be used as a healthy body parameter conditions. Growing evidence suggests that IT-based health records play essential role to drive medical revolution especially on data storage and processing. The heart rate measurement (HRM) process usually involves wearable sensor devices to record patient’s data. This data is recorded to help the doctors to analyze and provide a better diagnose in order to determine the best treatment for the patients. Connecting the sensor system through a wireless network to a cloud server will enable the doctor to monitor remotely. This paper presents fit-NES wearable bracelet, an alternative method for integrating a HR measurement device using optical based pulse sensor and Bluetooth-based communication module. This paper is also present the benchmarking of proposed system with several various commercial HR measurement devices.
IRJET- Review on: A Wireless IoT System for Gait Detection in Stroke PatientIRJET Journal
This document summarizes a proposed wireless IoT system for gait detection in stroke patients. The system would use sensors embedded in a smart shoe to discreetly monitor a patient's insole pressure and acceleration during walking. The data collected from the shoe sensors and a smartphone's built-in sensors would be used to detect any abnormal or cautious gait patterns that could predict risk of falling. The system aims to warn patients about risky gaits and potentially prevent injuries. It discusses how IoT and wireless communication could help create a portable system to continuously monitor patients' gaits outside of a clinical setting.
Applications of Sensors to Detect the Behavior of Human. A Survey PaperIRJET Journal
This document summarizes research on using sensors to detect human behavior. It discusses four papers that explored wearable sensors to monitor health signals, gesture recognition using data gloves, wireless body area networks of biosensors, and a homecare kit for multi-signal acquisition. The applications of these sensors include health monitoring, emergency response systems, transmitting emergency data from biosensors, and supporting medical care through daily signal measurement. Overall, the document reviews work using circuits and embedded systems to process sensor data and identify human behavior and feelings through technologies like smartwatches.
This document summarizes a research paper that designed a smart waist belt for health monitoring. The belt tracks steps, posture, heart rate and classifies activities using sensors and a random forest machine learning algorithm. It achieved high accuracy rates between 90-95% for classifying activities like sitting, walking and standing. The smart waist belt addresses issues with current fitness trackers and promotes an active lifestyle. It provides real-time health data to a mobile app and cloud for access and analysis. This allows users to conveniently self-monitor health metrics and get notifications about posture.
Development of a Home-based Wrist Rehabilitation System IJECEIAES
There are several factors that may result to wrist injuries such as athlete injuries and stroke. Most of the patients are unable to undergo rehabilitation at healthcare providers due to cost and logistic constraint. To solve this problem, this project proposes a home-based wrist rehabilitation system. The goal is to create a wrist rehabilitation device that incorporates an interactive computer game so that patients can use it at home without assistance. The main structure of the device is developed using 3D printer. The device is connected to a computer, where the device provides exercises for the wrist, as the user completes a computer game which requires moving a ball to four target positions. Data from an InvenSense MPU-6050 accelerometer is used to measure wrist movements. The accelerometer values are read and used to control a mouse cursor for the computer game. The pattern of wrist movements can be recorded periodically and displayed back as sample run for analysis purposes. In this paper, the usefulness of the proposed system is demonstrated through preliminary experiment of a subject using the device to complete a wrist exercise task based on the developed computer game. The result shows the usefulness of the proposed system.
Study of AI Fitness Model Using Deep LearningIRJET Journal
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Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
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Chapter 5
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Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
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MODEL MONITORING PHYSICAL EXERCISE HEART RATE USING INTERNET OF THINGS (MMPEH-IOT)
1. International Journal of Advanced Information Technology (IJAIT) Vol. 8, No.1/2, April 2018
DOI : 10.5121/ijait.2018.8202 21
MODEL MONITORING PHYSICAL EXERCISE HEART
RATE USING INTERNET OF THINGS (MMPEH-IOT)
Ejiofor C. I and Mgbeafuluike .I .J
Department of Computer Science, Chukwuemeka OdumegwuOjukwu University
ABSTRACT
Model Monitoring Physical Exercise Heart Rate Using Internet of Things (MMPEH-IOT) has
been developed and designed with its integral functionalities exposing through the six model
components: SmartHeart, WNEt, SoftAPP, Knowledgebase, Server and User interface. The model
was designed using Unified Modeling Language (UML) sequence diagram, identifying objects
exchanging messages. The model forecasts future benefits into smart devices and Internet of
Things (IoT).
KEYWORDS
Internet of Things (IoT), Physical Exercise, Smart Devices
1. INTRODUCTION
The combination of activities which excite the body organ with the aim of maintaining,
enhancing, supporting physical fitness and overall body wellness is seen as physical exercise
(Kylasov and Gavrov, 2011). Physical usually have either a personally, physical or mental
connotation which is performed at best for different reasons ranging from growth, development,
preventing aging, muscular stamina, weight loss, mental balance, cardiovascular body
maintenances even sexual enhancement (Stampfer et al., 2000). Physical exercises have found it
usefulness in reducing momentary stress, a principal contributor for varied mental illness
inclusive of depression, dementia and even Alzheimer (Pimlott, 2010). Physical exercises have
also been used efficiently and vehemently in controlling and monitoring blood sugar levels,
which have resulted in the prompt prevention of numerous classes of illness inclusive of diabetes
and even high blood pressure (Hu et al., 2001). Succeeding health benefits, physical exercise can
encourage social cultural integration, culturally education and meaningful socialization (Boecker
et al., 2008).
Physical exercises are can be perceived from three main types: Aerobic exercise, which is seen
as any large muscle group, causing tremendously body oxygen consumption. Aerobic exercise
increases cardiovascular endurance, which may include, running jogging, brisk walking,
skipping, hiking (Wilmore and Knuttgen, 2003). It may also include anaerobic exercise
traced to strength and resistance training, strength and tone muscle as well as improving
body strength, balance and coordination. Anaerobic exercise may include weight training,
eccentric training and interval training (De Vos et al., 2005). Physical exercise could also
be seen as flexibility exercise, which may include stretch; joint flexibility and muscle limber
2. International Journal of Advanced Information Technology (IJAIT) Vol. 8, No.1/2, April 2018
22
(O'Connor et al., 2005). Physical exercise may include training that focuses on accuracy, agility,
power, and speed (De Vos et al., 2005, O'Connor et al., 2005).
Although, physical exercise forecast and provides needed health benefits, it is indeed, not without
associated risk usually for aerobic and anaerobic exercise. It associated risk may include cardiac
arrest, muscle injuries: feet, ankles and knees. It can also incite illness like nausea, heartburn,
diarrhea, and gastrointestinal bleeding. These illnesses could be traced to serious heart rate
increase tremendously during physical exercises. Therefore, it is the intent of this research paper
to Monitoring Physical Exercise Heart Rate Using Internet of Things (IOT).
2. RELATED LITERATURE
This section is segmented with the view of identifying and reviewing previous researches on IOT,
identifying their strength, weakness and identifying area of future study. This limitation provides
an avenue to prosing a novel architecture or model in addressing the identified laps or gaps in
researches. Tables 2.1 provide a brief review of related literatures pertaining to Internet of Things
(IoT)
Table 2.1: Review of Related works on Internet of Things (IoT)
Table 2.1 identifies existing researches on Internet of Things (IoT) with notable limitations. Most
of the researches focus plainly on investigative and descriptive works with little attention paid to
model base solution in addressing IoTissues. Therefore base on the limitation of these literatures,
3. International Journal of Advanced Information Technology (IJAIT) Vol. 8, No.1/2, April 2018
23
it is the intent of this research paper to monitoring physical exercise heart rate using internet of
things (IoT)
3. MONITORING PHYSICAL EXERCISE HEART RATE USING INTERNET OF
THINGS (IOT)
The Monitoring Physical Exercise Heart Rate Using Internet of Things (MPEH-IOT) was
designed with the aim of extending previous model aimed at achieving Internet of Things (IoT).
Figure 3.1 graphically portray the Internet of Things Model Monitoring Physical Exercise Heart
Rate.
Figure 3.1: Model Monitoring Physical Exercise Heart Rate Using Internet of Things (MMPEH-IOT)
The model: Monitoring Physical Exercise Heart Rate Using Internet of Things (MMPEH-IOT)
comprises of six main phases: SmartHeart, WNEt, SoftAPP, knowledgebase, server and user
interface.
a. SmartHeart: The SmartHeart is known as the data collection module. This module is
responsible for collecting human read heart information identified per minute and
transmits it to the appropriate modules succeeding it. Therefore, all individuals engaging
in such physical exercise wear the devices in returning appropriate heart rating.
b. WNet: The Wireless Network (WNet) provides the needed platform in transmitting
relevant collection data from the SmartHeart to the point of analysis or evaluation. The
wireless network applied for the model provide needed platform in integrating the data
4. International Journal of Advanced Information Technology (IJAIT) Vol. 8, No.1/2, April 2018
24
collection module with the analysis and evaluation modules. Without this module, the
integration and remote communication possibilities will be total impossible.
c. SoftAPP: The SoftApp provides the software application for analyzing and evaluating
the collected data. The data are analyzed specifically for heart rate in determining
simultaneously, if a patient is exerting his heart to much or not. This periodic analyze is
stored within the knowledgebase which interface periodic with the smartheart.
d. Knowledgebase: The knowledgebase is the central repository which holds both the
collected and evaluated data. This data are analyzed and stored periodically by the
knowledgebase. The knowledgebase also hold the analysis rules upon which the systems
runs. The two communications between the knowledgebase and the softApp, identify
information integration and storage from the server and knowledgebase respectively.
e. Server: The interface serves as the intermediary between the specialized knowledgebase
and the user request. This request passed through the SoftApp which is the mediator
between the server and the knowledgebase. The two communications between the server
and the user interface identified obtained user request and returned user request.
f. User Interface: The user interface provides an avenue for individual system user to
verify and visualized evaluated and analyzed results. This result shows are presented
periodically upon the rate of exercises. The two communications between the server and
the user interface shows clearly.
4. UNIFIED MODELING LANGUAGE DESIGN (UML) FOR MODEL
MONITORINGPHYSICAL EXERCISE HEART RATE USING INTERNET OF
THINGS (MMPEH-IOT)
Unified Modeling Language (UML) was employed in designing the Model: the Monitoring
Physical Exercise Heart Rate Using Internet of Things (MPEH-IOT). UML been a standard
modeling language provides a number of graphical tools that can be used to visualize a model
from different viewpoints (Philippe, 2000 and Chris, 2000).This research paper focuses mainly on
the behavioral view showing the chain of exchange. Figure 4.1 provide the sequence diagram
view depicting the Monitoring Physical Exercise Heart Rate Using Internet of Things (MPEH-
IOT).
5. International Journal of Advanced Information Technology (IJAIT) Vol. 8, No.1/2, April 2018
25
Figure 4.1:Model Monitoring Physical Exercise Heart Rate Using Internet of Things (MMPEH-IOT)
The sequence diagram portrayed on Figure 4.1 utilizing six main objects: SmartHeart, WNEt,
SoftAPP, Knowledgebase, Server and User interface, in achieving heart rate monitoring. The
Smartheart as integral object collect patient heart rate data which is wireless transmitted to the
Wnet as an object. This information is used by the SoftApp as an object, which evaluate and
analysis the data with the help of the Knowledgebase. The Server receives and transmit user
request through theuserInterface object
5. DISCUSSION
The Model Monitoring Physical Exercise Heart Rate Using Internet of Things (MMPEH-IOT)
was designed with the aim to monitoring and evaluates the heart rate of each client engaging in
meaningful of vigorous exercise. The following issues are addressed with this model:
a. Prevent Associated Health risk with vigorous exercise.
b. Determine healthy patient
c. Prevent untimely death through cardiac arrest
d. Promote healthy life
These benefits those not holistic inspire the implementation of this research paper.
6. International Journal of Advanced Information Technology (IJAIT) Vol. 8, No.1/2, April 2018
26
6. CONCLUSIONS
A novel model monitoring heart rate during physical exercise was prosed using Internet of Things
(IoT). The model integral six main components: SmartHeart, WNEt, SoftAPP, Knowledgebase,
Server and User interface. These components holistically formed the functionalities of the model
addressing the fundamental issues of health care monitoring using smart devices and Internet of
Things (IoT)
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