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.
Highlights
Sit-to-stand (STS) movement is one of the most commonly performed functional activities [1, 2], which requires both relatively large joint moments and precise balance control [3, 4]
A piecewise biomechanical model for STS kinematic analysis was presented in our previous work [28] just for a control strategy research, but there was no kinetic analysis of STS
Comparing the same kinematic parameters (θ, α) derived from the developed inertial sensor measurement modules (IMUs) and the referenced optical motion capture system (RCS) curved by the same color but different lines in the same figure in Figure 4 and Figure 5, it was found that the corresponding parameters were basically the same except for a few subtle differences
Summary
Sit-to-stand (STS) movement is one of the most commonly performed functional activities [1, 2], which requires both relatively large joint moments and precise balance control [3, 4]. The ability to perform STS transfer in a reliable and safe manner with adequate joint moment [10] becomes a key element of movement rehabilitation in orthopedically or neurologically impaired individuals. Ambulatory estimation and analysis of STS movement with wearable sensors is a promising clinical tool to diagnose human motion. Various methods using inertial sensors were available for assessing 3D human posture in motion [12,13,14]; few papers proposed methods to estimate kinetics of lower limb joints using wearable inertia sensors and few detailed applications of inertia sensors for noninvasive analysis and diagnosis of STS rehabilitation training
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