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Analysis of Human Motion Data Captured by SlimeVR and Validation of Its Reliability

Accurate acquisition of human motion data is important for research in fields such as robotics and bionics. In this paper, based on the SlimeVR motion capture system, two common motion postures: walking, walking up and downstairs, were designed to capture. Recording data include the pitch, yaw and roll angles of the waist, knee and ankle joints. Afterwards use MATLAB to generate the angle change curves of the corresponding joints to analyze the characteristics of the angle changes of the three joints under different experiments. At the same time, the obtained data were animated and reproduced using Blender to verify the accuracy of the data acquisition. Also the ankle joint motion data in the existing database were similarly processed and used MATLAB to compare with the data obtained by SlimeVR. The results showed that SlimeVR can accurately record kinematic data at low to medium speeds. Meanwhile, the most significant fluctuations in the generated kinematic curves were in the knee data and a significant angular change process can be observed. The waist and ankle joints have less angular change during both experiments. There are no significant deviations in the Blender reproduction animations and the measured data have several similar characteristics when compared to the existing data.