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A Novel Simplified System to Estimate Lower-Limb Joint Moments during Sit-to-Stand

Title
A Novel Simplified System to Estimate Lower-Limb Joint Moments during Sit-to-Stand
Author(s)
Hwang, SeoyoonChoi, SeoyoungLee, Yang-SooKim, Jonghyun
Issued Date
2021-01
Type
Article
Article Type
Article
Author Keywords
Asymmetric weight-bearing motionInertial sensorJoint momentKinematic modelSegment angleSit-to-stand
Keywords
Inertial navigation systemsKinematicsMean square errorConventional systemsCorrelation coefficientHealthy peopleInertial sensorKinematic modelRoot mean square errorsSit-to-standWeight bearingJoints (anatomy)
ISSN
1424-8220
Abstract
To provide effective diagnosis and rehabilitation, the evaluation of joint moments during sit-to-stand is essential. The conventional systems for the evaluation, which use motion capture cameras, are quite accurate. However, the systems are not widely used in clinics due to their high cost, inconvenience, and the fact they require lots of space. To solve these problems, some studies have attempted to use inertial sensors only, but they were still inconvenient and inaccurate with asymmetric weight-bearing. We propose a novel joint moment estimation system that can evaluate both symmetric and asymmetric sit-to-stands. To make a simplified system, the proposal is based on a kinematic model that estimates segment angles using a single inertial sensor attached to the shank and a force plate. The system was evaluated with 16 healthy people through symmetric and asymmetric weight-bearing sit-to-stand. The results showed that the proposed system (1) has good accuracy in estimating joint moments (root mean square error < 0.110 Nm/kg) with high correlation (correlation coefficient > 0.99) and (2) is clinically relevant due to its simplicity and applicability of asymmetric sit-to-stand. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
URI
http://hdl.handle.net/20.500.11750/12979
DOI
10.3390/s21020521
Publisher
MDPI AG
Files in This Item:
000611699900001.pdf

000611699900001.pdf

기타 데이터 / 2.71 MB / Adobe PDF download
Appears in Collections:
ETC 1. Journal Articles

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