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  • Title: Noninvasive Estimation of Joint Moments with Inertial Sensor System for Analysis of STS Rehabilitation Training.
    Author: Liu K, Yan J, Liu Y, Ye M.
    Journal: J Healthc Eng; 2018; 2018():6570617. PubMed ID: 29610656.
    Abstract:
    An original approach for noninvasive estimation of lower limb joint moments for analysis of STS rehabilitation training with only inertial measurement units was presented based on a piecewise three-segment STS biomechanical model and a double-sensor difference based algorithm. Joint kinematic and kinetic analysis using a customized wearable sensor system composed of accelerometers and gyroscopes were presented and evaluated compared with a referenced camera system by five healthy subjects and five patients in rehabilitation. Since there is no integration of angular acceleration or angular velocity, the result is not distorted without offset and drift. Besides, since there are no physical sensors implanted in the lower limb joints based on the algorithm, it is feasible to noninvasively analyze STS kinematics and kinetics with less numbers and types of inertial sensors than those mentioned in other methods. Compared with the results from the reference system, the developed wearable sensor system is available to do spatiotemporal analysis of STS task with fewer sensors and high degree of accuracy, to apply guidance and reference for rehabilitation training or desired feedback for the control of powered exoskeleton system.
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