# Research on Monocular-Vision-Based Finger-Joint-Angle-Measurement System
## 6 Conclusions  
To solve the problems that the joint-angle measuring instrument takes more time to measure the angle of single joints in clinical medicine, and cannot measure the angles of multiple joints at the same time, a vision-based finger-joint-angle-measuring system was designed on the basis of the original visual-inspection system. The system consists of a hardware system, a control system, and a vision system. The active multi-angle-light-source-detection system composed of a control system and a hardware system can simplify the recognition process of visual markers by adjusting the height of the light source. The vision system is composed of an industrial camera and the knuckle-angle-detection method proposed in this paper. The knuckle-angle-detection method proposed in this paper is composed of finger-joint-marker pasting, image acquisition, visual-marker segmentation, visual-marker edge detection, and joint-angle calculation based on different finger-joint markers. In this study, each component of the method was analyzed and verified by experiments. These experiments proved that in the case of high angle illumination, the TS-HOMLDM should be adopted, and the visual marker with the scale of 1.5 mm was selected, since it had the highest measurement accuracy. The shortcomings of the current proposed MVBFJAMS are also very obvious. Firstly, the system requires a Basler ace camera, a TEC-V7X industrial lens, an R50-26-13 light source, and a computer, which makes it much more expensive than traditional knuckle-measurement methods and sensor-based methods; furthermore, the system can only achieve two-dimensional inspection at present.  
The system is still in the experimental stage and has high requirements for the detection environment for light sources. Considering the complexity of the clinical environment, in order to improve the anti-interference capability of the system, we intend to add an opaque housing to the exterior of the device in the future in order to maintain the stability of the testing environment. In the next phase, we intend to add another depth camera to this system and fuse the texture information from the normal camera with the depth-camera depth information to build a model of the detector's hand. Using this approach, three-dimensional detection can then be achieved to detect the angle of each finger joint of the hand. In the meantime, we will further validate the accuracy of the system through clinical trials, as well as the accuracy of the assessment of the level of handicap and the effectiveness of the intervention treatment.  
Conceptualization, Y.F. and M.Z.; methodology, Y.F.; software, Y.F.; validation, Y.F. and F.D.; the main content of this manuscript was created and written by [PERSON] and reviewed by all authors. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Natural Science Foundation of Zhejiang Province, grant number LQ21E050008; Educational Commission of Zhejiang Province, grant number Y201941335; Science and Technique Plans of Ningbo City, grant number 202002N3133; The Major Scientific and Technological Projects in Ningbo City, grant number 2020Z082; Research Fund Project of Ningbo University, grant number XYL19029; and the K. C. Wong Magna Fund of Ningbo University.  
The study was conducted according to the guidelines of theDeclaration of Helsinki, and approved by the Ethics Committee of Faculty of Mechanical Engineering & Mechanics, Ningbo University (protocol code [2022]LLSP(0315) and 2022.03.15).  
Informed Consent Statement:Informed consent was obtained from all subjects involved in the study.  
Data Availability Statement:Not applicable.  
Conflicts of Interest:The authors declare no conflict of interest.