Abstract
A brain stroke is a neurological condition that causes a significant reduction in cerebral blood flow in the specific area of the brain caused by the blockage of a primary brain artery, which leads to disability in affected person. Rehabilitation is essential for individuals to recover from disability, as it is a prolonged and challenging process. The proposed study presents an efficient approach to improve and expedite hand motor skill recovery after brain stroke, which has significance for routine tasks and prolonged process compare to other part of body, with the help of Internet of Things (IoT) technology. The proposed IoT-enabled smart glove for brain stroke rehabilitation system comprises of five Flexi-Force sensors, five flex sensors, a Max30100 sensor, OLED display, Li-po battery, and a ESP32 microcontroller board. It facilitates monitoring of fingers bending angle and grip strength in real-time. A cloud-based platform, ThingsBoard, collects the real-time data generated by the sensors and keeping record for further analysis. The performance of system is evaluated on the basis of correctness of collected data from sensors through calibration and error analysis. The calibration of the flex sensors is also performed by the National Accreditation Board for Testing and Calibration Laboratories-accredited laboratory, which certified high precision with an accuracy of ±2 and an uncertainty of ±0.7, respectively. The system provides a precise, accurate, and economical solution with features like measuring muscle strength, gripping strength, oxygen level, and heart rate and storing data to cloud for further analysis by report generation. which makes it better than the solution found in the existing literature.