IMU sensor-based data glove for finger joint measurement

Abstract

The methods used to quantify finger range of motion significantly influence how hand disability is reported. To date, the accuracy of sensors being utilized in data gloves from the literature has been ascertained yet need further analysis. This paper presents a sensor-based data glove for finger joint measurement developed for collecting a range of motion data of distal interphalangeal, proximal interphalangeal and metacarpophalangeal finger joints of an index finger. In this study, three inertial measurement sensors and two flexible bend sensors were attached to the finger joint points on the glove to detect angle displacement. The angle displacements were acquired using Arduino and MATLAB software interface. Goniometry was used to allow accurate comparative measurement. Low percentage of error resulted from inertial measurement unit ( 0.81 % to 5.41 % ), indicates high accuracy. On the other hand, flexible bend sensor shows low accuracy (11.11 % to 19.35 % error). In conclusion, the inertial measurement unit sensor, MPU-6050 can be a reliable solution for tracking the progress of finger rehabilitation exercises. In order to motivate patients to adhere to the therapy exercises, interactive rehabilitation game will be developed in the future incorporating MPU-6050 sensors on all five fingers.