Iot-Healthcare Monitoring System With Capability To Detect Ecg, Blood Pressure And Temperature

• Main Author: Lim, Sheng Keong
• Format: Monograph
• Language: English
• Published: Universiti Sains Malaysia 2017
• Subjects: T Technology; TK Electrical Engineering. Electronics. Nuclear Engineering
• Online Access: http://eprints.usm.my/53073/1/Iot-Healthcare%20Monitoring%20System%20With%20Capability%20To%20Detect%20Ecg%2C%20Blood%20Pressure%20And%20Temperature_Lim%20Sheng%20Keong_E3_2017.pdf; http://eprints.usm.my/53073/
• Institution: Universiti Sains Malaysia

Life expectancy at birth increases compared to the previous year. Aging population has become a challenge to developing a low cost and efficiency healthcare system since there are limited medical resources. Besides, the healthcare systems on the market do not provide two way communication feature for doctor and patient. IoT-healthcare monitoring system is proposed to overcome these problems. In this study, a system consists of the prototyping of an embedded healthcare monitoring system which is capable to measure ECG, blood pressure, pulse rate, body temperature is proposed on DE1-SoC platform. The IoT-framework is included where the real-time data are stored at IBM Bluemix cloud platform through the Node-RED. Web GUI is created using http GET and POST to display the measurements and advice from doctor through Internet. The accuracy of the sensors for developed system are evaluated through comparing the measurement with the commercial medical devices. The average accuracy for each sensors to measure the health parameter are 99.21% for temperature measurement, 99.26% for pulse rate measurement, 99.17% for Systolic pressure and 98.72% for diastolic pressure. An analysis is carried on the measurements to predict potential disease and results are displayed on local web page. The time required for a sample data to successfully stored in cloud is 1.5 millisecond using 100Mbps speed Internet. Ten volunteers are invited to test the functionality of the system. Generally the measurements from the system have accuracy over 90%. As a conclusion, the functionality of the healthcare system in the study is proven and it is able to provide better healthcare service to patients.