Research on Monocular-Vision-Based Finger-Joint-Angle-Measurement System

Abstract

The quantitative measurement of finger-joint range of motion plays an important role in assessing the level of hand disability and intervening in the treatment of patients. An industrial monocular-vision-based knuckle-joint-activity-measurement system is proposed with short measurement time and the simultaneous measurement of multiple joints. In terms of hardware, the system can adjust the light-irradiation angle and the light-irradiation intensity of the marker by actively adjusting the height of the light source to enhance the difference between the marker and the background and reduce the difficulty of segmenting the target marker and the background. In terms of algorithms, a combination of multiple-vision algorithms is used to compare the image-threshold segmentation and Hough outer- and inner linear detection as the knuckle-activity-range detection method of the system. To verify the accuracy of the visual-detection method, nine healthy volunteers were recruited for experimental validation, and the experimental results showed that the average angular deviation in the flexion/extension of the knuckle was 0.43° at the minimum and 0.59° at the maximum, and the average angular deviation in the adduction/abduction of the knuckle was 0.30° at the minimum and 0.81° at the maximum, which were all less than 1°. In the multi-angle velocimetry experiment, the time taken by the system was much less than that taken by the conventional method.

Advanced Intelligent Control in Robots

“…“Research on Monocular-Vision-Based Finger-Joint-Angle-Measurement” [ 11 ] considers an industrial monocular-vision-based knuckle-joint-activity-measurement system, with a short measurement time and the simultaneous measurement of multiple joints, applied to an existing computer-vision detection system. An Experimental Platform is designed to acquire high-quality multi-angle light-source-irradiated multivariate images.…”

Stretchable glove for accurate and robust hand pose reconstruction based on comprehensive motion data

“…This differentiates our system from the previous studies that evaluated their systems only for limited experimental conditions and users. For example, the strain-based tracking system was evaluated with the data obtained from the static motions of a hand replica 9 , and the vision-based system was tested only for restricted hand motions confined to a customized stage 37 . Another approach with vision used datasets of fingertip positions, highly dependent on the specific kinematic structure, and thus may not be universally applicable to all hand configurations 38 .…”