吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (4): 1140-1146.doi: 10.13229/j.cnki.jdxbgxb20180043

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Dynamic analysis of sit-to-stand human motion based on in vitro-sensor detection

LIU Kun, LIU Yong, YAN Jian-chao, JI Shuo, SUN Zhen-yuan, XU Hong-wei   

  1. School of Mechanical Science and Engineering, Jilin University, Changchun 130022, China
  • Received:2018-01-15 Online:2018-07-01 Published:2018-07-01

Abstract: A non-invasive estimation and analysis system for lower limb joint moments was developed based on a piecewise three segment Sit-to-Stand (STS) biomechanical model and a double-sensor difference based algorithm. The wearable sensor system, composed of force sensors, customized accelerometer and gyroscope, worked with vitro implanted sensors. Compared with conventional approach, the number and variety of sensors were reduced in this sensor system. Compared with the results from reference camera system, the developed wearable inertial sensor system is available to analyze the lower limb biomechanics of patient during the rehabilitation training with high degree of accuracy. In the future, the system could be applied for the detection and estimation system of human STS rehabilitation training and to the control of exoskeleton rehabilitation robot.

Key words: mechanical design, biomedical engineering, non-invasive vitro detection, sit-to-stand(STS) rehabilitation training, wearable sensor system

CLC Number: 

  • TH122
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