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Heart and Muscle Performance Monitoring System

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In recent years, healthcare systems have been facing difficulties due to maturing population and increase in long term illness. As a result, there is more demand for hospital resources [1]. Internet of Things (IoT) seem to have the potential to lower the overall health system cost and workload on doctors and nurses [2]. According to [3], “Wearable health monitoring systems are systems that can be carried by patients, collect physiological data from them, and broadcast it to some form of data collection for further analysis, are considered as a way of cost reduction by reducing medical visits and earlier detection of illnesses”. In this paper, we are planning to provide a solution that would collect patient’s heart and muscle data and output an insight accordingly.

Methodology – Our target is to implement an android application that will utilize Shimmer sensors to collect ECG (Electrocardiograph) and EMG (Electromyograph) data. Through the heart muscle the pathway of electrical impulses are recorded to monitor Electrocardiogram. On the other hand, EMG is a medical procedure to measure the health of muscles and nerve cells which control the motor neurons. The application will be built on the API provided by Shimmer to handle that data and we will set a threshold to find the level of emergency health condition based on standard medical emergency condition level. I plan to work on the android implementation aspect of the project and also integrate location services using the GPS sensor.. We have taken six Shimmer sensors from the department; they are ECG, EMG, Bio Physical, Bio Physical, Kinematics, GPS. Our goal is to use these sensors, collect relevant data onto our custom android application and send alert for values crossing threshold points.

Related Work – At present, the rate at which technology is advancing, mobile healthcare applications are no more improbable. Applications of this sort will enable individuals to be aware of their health and also deliver useful data to doctors and nurses [4]. In [4], wearable devices like Zephyr Bioharness BH3 to monitor heart rate and A&D Medical UA-767PBT-C blood pressure monitor were used to acquire data via Bluetooth protocol. The data collected were then analysed on a mobile device; prepared for visualization and lastly sent to medical servers for further investigation.

Another approach was suggested by [5] where they used PPG (Photoplethysmography) sensor to measure heart rate; passed physiological data to a PC via wired connection and final stage was to store this data on a remote server. Rajkumar and Srikanth [6] have developed a system which makes use of Raspberry pi along with DS18B20 temperature sensor and Fitbit to measure heart rate. Any abnormal value will alert the doctor and store that value in the server. They claim Raspberry pi provides an efficient solution in this use case because it consumes low power and has an ability to multitask. In [2], plug and play pulse sensor with arduino were used to monitor heart rate. They had to use HC-05 Bluetooth Shield to transmit sensor data to phone. In addition, they utilized smart phone’s built in location service to transmit geolocation data.

Only one physiological signal was included in their proposal. In another paper Singh, Chaturvedi and Ramesha [7] worked with Photoplethysmogram (PPG) data which provides detailed report of heartbeats and not just heart rate. They used Pulse Oximetry to acquire the data and on it implemented a hardware using Arduino board (Uno) along with other components. MATLAB was then used for data processing. A PPG signal can give a lot of other information like blood pressure, blood glucose, arterial stiffness, etc. Conclusion – I am working in a group of four; in consultation with our instructor, we have decided to use Shimmer sensors to transmit data on an android application. These sensors are self sufficient unlike the plug-and-play pulse sensor that was suggested in [2] which require additional technology to transmit data via Bluetooth.

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Heart and muscle performance monitoring system. (2019, March 27). GradesFixer. Retrieved May 26, 2022, from
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