Rehabilitation Monitoring System with IoT Application

Abstract

The rehabilitation process is one of the crucial elements to a quicker recovery, particularly for stroke and sports injury patients who require ongoing rehabilitation. This study proposes a web-based, multimodal leg rehabilitation monitoring system for use in the home. While there have been many studies conducted on leg performance and home-based rehabilitation techniques, there are still limitations in the field of leg rehabilitation. One of these limitations is the complexity and cost of current rehabilitation equipment, which require supervision by trained therapists. Additionally, it takes a long time for doctors to receive data from these devices for monitoring purposes. In order to address these issues, it is important for leg rehabilitation exercises to be continually assessed by professionals with the knowledge to identify leg dysfunction and conditions such as stroke early on. This system is designed to aid in the rehabilitation of stroke and sport injury patients by tracking leg movement and pressure during therapy. This study presents a three-stage data acquisition, processing, and logging system for leg rehabilitation that uses flex sensors, force-sensitive resistors, and an accelerometer. The system employs an Arduino Mega Controller and ESP Wi-Fi shield to establish an IoT system named ThingSpeak, allowing doctors to remotely monitor and diagnose patient recovery progress. Data were collected for five subjects, as each subject performed six exercises. The graph showed the difference between the different subjects, as the readings were close to the same patient diagnosis. The system is portable, user-friendly, and has low power consumption, providing an efficient and cost-effective solution for leg rehabilitation.