Developing a User-friendly System for Home-based Monitoring of Arm Use after Stroke

Stroke rehabilitation faces challenges in providing real-time care outside clinical settings, as they require in-person supervision and lack personalized monitoring of continuous progression in stroke rehabilitation. Recent advances in wearable sensors (e.g., inertial measurement unit (IMU), electromyography (EMG)) offer avenues to longitudinally track arm use in the real-world setting, e.g. during activities of daily living at home. However, challenges remain in translating such technology mainly due to practical barriers in transferring the technical knowledge and skills required for operating the sensor/device to acquire data. The main objective of this project was to develop a user-friendly system that consists of: 1) “easy-to-don and-doff” wearable sensors, 2) “easy-to-use” graphical user interface (GUI) for data acquisition, and 3) “on-the-go” receiver unit for reliable wireless connection. To this end, we used Myo Armband (Thalmic Labs, CANADA), which is a consumer-grade bracelet sensor capable of capturing IMU data and EMG signals to assess movement and muscle activity that communicates via bluetooth. We developed a Python-based GUI that collects and displays real-time data visualization for the two Myo Armbands on the upper arm and forearm. This system has enabled real-time monitoring, reliable tracking, and scalable rehabilitation, enhancing accessibility, engagement, and recovery outcome.