A wearable motion capture device able to detect dynamic motion of human limbs

Shiqiang Liu, Junchang Zhang, Yuzhong Zhang and Rong Zhu ()
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Shiqiang Liu: Tsinghua University
Junchang Zhang: Tsinghua University
Yuzhong Zhang: Tsinghua University
Rong Zhu: Tsinghua University

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract Limb motion capture is essential in human motion-recognition, motor-function assessment and dexterous human-robot interaction for assistive robots. Due to highly dynamic nature of limb activities, conventional inertial methods of limb motion capture suffer from serious drift and instability problems. Here, a motion capture method with integral-free velocity detection is proposed and a wearable device is developed by incorporating micro tri-axis flow sensors with micro tri-axis inertial sensors. The device allows accurate measurement of three-dimensional motion velocity, acceleration, and attitude angle of human limbs in daily activities, strenuous, and prolonged exercises. Additionally, we verify an intra-limb coordination relationship exists between thigh and shank in human walking and running, and establish a neural network model for it. Using the intra-limb coordination model, dynamic motion capture of human lower limbs including thigh and shank is tactfully implemented by a single shank-worn device, which simplifies the capture device and reduces cost. Experiments in strenuous activities and long-time running validate excellent performance and robustness of the wearable device in dynamic motion recognition and reconstruction of human limbs.

Date: 2020
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DOI: 10.1038/s41467-020-19424-2

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