Estimation of spatial-temporal hand motion parameters in rehabilitation using a low-cost noncontact measurement system
Hamid Reza Fazeli, Qingjin Peng · Medical Engineering & Physics · 2021
Data collection and analysis are commonly used in a rehabilitation process to measure performances of the treatment. There is a lack of studies on the rehabilitation process monitored by a user-friendly interface. A low-cost system is developed in this research to assist users and therapists to measure hand motions and analyse important data of hand joints. The system consists of modules of data capturing, data analysis, and user interface. A Leap Motion sensor is used to capture joint positions of hand motions. Signal processing and wavelet de-noising methods are developed to improve accuracy of the data analysis. The user interface is designed using the Unity software to show graphical information of joint positions and motion parameters. The system has features of noncontact measurements, interactive environment, analysing and recording temporal data of motion parameters of hands. The system is validated by a gold standard motion capturing system. Case studies show effectiveness of the proposed system.