Numerous types of research on healthcare monitoring systems have been conducted for calculating heart rate,ECG,nasal/oral airflow,temperature,light sensor,and fall detection sensor.Different researchers have done diff...Numerous types of research on healthcare monitoring systems have been conducted for calculating heart rate,ECG,nasal/oral airflow,temperature,light sensor,and fall detection sensor.Different researchers have done different work in the field of health monitoring with sensor networks.Different researchers used built-in apps,such as some used a small number of parameters,while some other studies used more than one microcontroller and used senders and receivers among the microcontrollers to communicate,and outdated tools for study development.While no efficient,cheap,and updated work is proposed in the field of sensor-based health monitoring systems.Therefore,this study developed an android-based mobile system that can remotely monitor electrocardiograms(ECGs),pulse oximetry,heart rate,and body temperature.The microcontroller’s Wi-Fi device is used to manage wireless data transport.The findings of the patient are saved on the Firebase server for further usage in the mobile app.The performance of the proposed device is tested on ten numbers of different patients age-wise in terms of beats per minute(BPM),ECG,Temperature,and SpO2.This system uses temperature,pulse,ECG,blood pressure,and eye blink sensors.This device makes the usage of a tiny pulse sensor that has been designed to provide an accurate and optimal readout of the pulse rate and a temperature sensor is also included.With the help of an MCU,our system measures the pulse rate in beats per minute(bpm),blood oxygen level temperature measurements,and ECG readings and communicates this information to the Firebase server.To check the performance of the proposed system first,the BPM parameter was checked on the cardiac monitor.Then,the proposed model is tested on different patients age-wise.The simulation result shows that the BPM reading is not much different than the BPM of the cardiac monitor.According to the simulation findings,the proposed model achieved the best performance as compared to commercially available devices.展开更多
基金Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number 223202.
文摘Numerous types of research on healthcare monitoring systems have been conducted for calculating heart rate,ECG,nasal/oral airflow,temperature,light sensor,and fall detection sensor.Different researchers have done different work in the field of health monitoring with sensor networks.Different researchers used built-in apps,such as some used a small number of parameters,while some other studies used more than one microcontroller and used senders and receivers among the microcontrollers to communicate,and outdated tools for study development.While no efficient,cheap,and updated work is proposed in the field of sensor-based health monitoring systems.Therefore,this study developed an android-based mobile system that can remotely monitor electrocardiograms(ECGs),pulse oximetry,heart rate,and body temperature.The microcontroller’s Wi-Fi device is used to manage wireless data transport.The findings of the patient are saved on the Firebase server for further usage in the mobile app.The performance of the proposed device is tested on ten numbers of different patients age-wise in terms of beats per minute(BPM),ECG,Temperature,and SpO2.This system uses temperature,pulse,ECG,blood pressure,and eye blink sensors.This device makes the usage of a tiny pulse sensor that has been designed to provide an accurate and optimal readout of the pulse rate and a temperature sensor is also included.With the help of an MCU,our system measures the pulse rate in beats per minute(bpm),blood oxygen level temperature measurements,and ECG readings and communicates this information to the Firebase server.To check the performance of the proposed system first,the BPM parameter was checked on the cardiac monitor.Then,the proposed model is tested on different patients age-wise.The simulation result shows that the BPM reading is not much different than the BPM of the cardiac monitor.According to the simulation findings,the proposed model achieved the best performance as compared to commercially available devices.
