IMU sensor-based data glove for finger joint measurement - Muhammad Ajwad Wa’ie Hazman; Ili Najaa Aimi Mohd Nordin; Faridah Hanim Mohd Noh; Nurulaqilla Khamis; M. R. M. Razif; Ahmad Athif Faudzi; Asyikin Sasha Mohd Hanif (Indonesian Journal of Electrical Engineering and Computer Science, 2020)
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 an inertial measurement unit 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, MPU-6050 and two flexible bend sensors which are capable to detect angle displacement were attached to the distal interphalangeal, proximal interphalangeal and metacarpophalangeal finger joint points on the glove. The data taken from inertial measurement unit sensors and flexible bend sensors were acquired using Arduino and MATLAB software interface. The data obtained were compared with the reference data measured from goniometer to allow for accurate comparative measurement. The percentage of error resulted from MPU-6050 sensor unit were ranged from 0.81 % to 5.41 % were very low which indicates high accuracy when compared with the measurements obtained using goniometer. On the other hand, flexible bend sensor shows low accuracy (11.11 % to 19.35 % error). In conclusion, the inertial measurement unit sensor-based data glove using MPU-6050 sensors 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.