Authors : Suryakant Shashikant Misal; Omkar Nandkumar Patil; Mahamadsaalim Usmanalli Bargir

Volume/Issue : Volume 11 - 2026, Issue 6 - June

Google Scholar : https://tinyurl.com/3uxe34mm

Scribd : https://tinyurl.com/nhjkhsn

DOI : https://doi.org/10.38124/ijisrt/26jun446

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The latest advances in wearable sensors and cloud computing are making biomedical assessments more automated and precise. Home-based tele-rehabilitation is becoming an increasingly important topic nowadays since it can provide patients with methods that make clinical tracking easier and improve their overall quality of recovery. This system aims to increase the recovery accuracy for palm and finger injuries by tracking functional joint degradation caused by fractures or soft-tissue crush trauma. It achieves this by using an array of resistive flex sensors and force-sensitive resistors (FSRs) that analyze finger articulation angles and active grip pressure whenever a therapeutic exercise is initiated. If the movement thresholds are achieved during a targeted 30-second automated routing, the system logs the session data locally. Concurrently, any abnormal or highly restricted performance limits will lead the system to update progress metrics and flag risk levels via an interactive remote cloud platform. The system also allows wireless cloud tracking by providing data synchronization through an integrated mobile application. Moreover, the application displays data matrices retrieved from an MPU6050 Inertial Measurement Unit (IMU) to monitor wrist stability and range of motion parameters. To maximize utility, the device consists of three operational exercise modes—Ball Squeeze, Finger Flexion, and Wrist Rotation—controlling evaluation metrics dynamically based on peak physical data captured.

Keywords : Flex Sensor, FSR Pressure Sensor, MPU6050, ESP32, Blynk IoT, Tele-Rehabilitation.

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