Paper Title
MyoTracker: A Mobile Application to Monitor and Determine Muscles Strength

Abstract
The use of wearable sensors in clinical settings has gained much attention in recent times. Muscular disorders have become quite common in cases such as muscular atrophy and myopathy which are seen as a lifestyle and genetic diseases. An electromyography (EMG) sensor is widely used in clinical settings to diagnose neuromuscular disease. Existing EMG sensors in the open market are expensive and may not be easily available for individual use at homes. Other low-cost EMG sensors designed from previous research were not coupled with a standalone application to monitor and determine the strength of a muscle. In this study, we propose MyoTracker, a microcontroller-based EMG system based on an android app, to monitor and display the strength of a muscle. This is a simple and inexpensive EMG sensor that allows users to measure a muscle and view the strength of the muscle on their smartphones. The designed app remotely connects to the microcontroller-based EMG sensor via HC-05 Bluetooth module. The strength of a muscle is computed by the integrated EMG signal and the root mean square (rms) of the enveloped signal in the time domain. This is used to categorize the strength of a muscle recorded into two parts namely, weak muscle or strong muscle. Our designed MyoTracker is novel and maybe useful for elderly people living in care homes or patients undergoing rehabilitation. Keywords - EMG sensor, MyoTracker, Signal, Muscle,