Measurement Of Fine Motor Movements Of Hands In Aid Of Fine Motor Skills Development - Justin, Yip Yuen Kit (2020)
Providing the most suitable or customised rehabilitation therapy for individual stroke patient is a common challenge to therapists. Most therapies focus on overall gross movements which is not specific enough to aid in full functional recovery of fine motor movements in hands. With the present difficulty, the aim this project is to design and develop a non-invasive wearable device (MSR glove) which can detect electromyography (EMG) signals from hand movements. This was achieved using a wearable device with the presence of electronics such as MyoWare Muscle Sensor, programmable Arduino UNO microcontroller, a Bluetooth module and a mobile app. The placement of sensors was performed on different muscle locations to observe the threshold of signals generated. Data generated was portrayed in the form of EMG can be easily accessed and monitored by the users via PC, laptop or smartphone. The device developed is also able to provide real-time measurements of other parameters such as body temperature, room temperature, skin humidity and muscle movement. Testing performance indicated that this development could provide reliable data on muscle action potential generated by individual finger motions. Subsequently, therapist may use these data as a reference to device treatment plan that targets specific inactive or weak muscles which is responsible for fine motor movements of patients that have been affected neurologically therefore aiding in fine motor skills development.