Literature DB >> 27331305

Feasibility study of using a Microsoft Kinect for virtual coaching of wheelchair transfer techniques.

Seonhong Hwang1, Chung-Ying Tsai1, Alicia M Koontz1.   

Abstract

The purpose of this study was to test the concurrent validity and test-retest reliability of the Kinect skeleton tracking algorithm for measurement of trunk, shoulder, and elbow joint angle measurement during a wheelchair transfer task. Eight wheelchair users were recruited for this study. Joint positions were recorded simultaneously by the Kinect and Vicon motion capture systems while subjects transferred from their wheelchairs to a level bench. Shoulder, elbow, and trunk angles recorded with the Kinect system followed a similar trajectory as the angles recorded with the Vicon system with correlation coefficients that are larger than 0.71 on both sides (leading arm and trailing arm). The root mean square errors (RMSEs) ranged from 5.18 to 22.46 for the shoulder, elbow, and trunk angles. The 95% limits of agreement (LOA) for the discrepancy between the two systems exceeded the clinical significant level of 5°. For the trunk, shoulder, and elbow angles, the Kinect had very good relative reliability for the measurement of sagittal, frontal and horizontal trunk angles, as indicated by the high intraclass correlation coefficient (ICC) values (>0.90). Small standard error of the measure (SEM) values, indicating good absolute reliability, were observed for all joints except for the leading arm's shoulder joint. Relatively large minimal detectable changes (MDCs) were observed in all joint angles. The Kinect motion tracking has promising performance levels for some upper limb joints. However, more accurate measurement of the joint angles may be required. Therefore, understanding the limitations in precision and accuracy of Kinect is imperative before utilization of Kinect.

Entities:  

Keywords:  Kinect; concurrent validity; joint angle; test-retest reliability; wheelchair transfer

Mesh:

Year:  2017        PMID: 27331305     DOI: 10.1515/bmt-2015-0206

Source DB:  PubMed          Journal:  Biomed Tech (Berl)        ISSN: 0013-5585            Impact factor:   1.411


  6 in total

1.  Experimental Validation of Depth Cameras for the Parameterization of Functional Balance of Patients in Clinical Tests.

Authors:  Francisco-Ángel Moreno; José Antonio Merchán-Baeza; Manuel González-Sánchez; Javier González-Jiménez; Antonio I Cuesta-Vargas
Journal:  Sensors (Basel)       Date:  2017-02-22       Impact factor: 3.576

2.  The Reliability and Validity of Wearable Inertial Sensors Coupled with the Microsoft Kinect to Measure Shoulder Range-of-Motion.

Authors:  Peter Beshara; Judy F Chen; Andrew C Read; Pierre Lagadec; Tian Wang; William Robert Walsh
Journal:  Sensors (Basel)       Date:  2020-12-17       Impact factor: 3.576

Review 3.  The Reliability of the Microsoft Kinect and Ambulatory Sensor-Based Motion Tracking Devices to Measure Shoulder Range-of-Motion: A Systematic Review and Meta-Analysis.

Authors:  Peter Beshara; David B Anderson; Matthew Pelletier; William R Walsh
Journal:  Sensors (Basel)       Date:  2021-12-08       Impact factor: 3.576

4.  A Simple Method to Optimally Select Upper-Limb Joint Angle Trajectories from Two Kinect Sensors during the Twisting Task for Posture Analysis.

Authors:  Pin-Ling Liu; Chien-Chi Chang; Li Li; Xu Xu
Journal:  Sensors (Basel)       Date:  2022-10-09       Impact factor: 3.847

5.  Automated functional upper limb evaluation of patients with Friedreich ataxia using serious games rehabilitation exercises.

Authors:  Bruno Bonnechère; Bart Jansen; Inès Haack; Lubos Omelina; Véronique Feipel; Serge Van Sint Jan; Massimo Pandolfo
Journal:  J Neuroeng Rehabil       Date:  2018-10-04       Impact factor: 4.262

6.  Kinect v2-Assisted Semi-Automated Method to Assess Upper Limb Motor Performance in Children.

Authors:  Celia Francisco-Martínez; José A Padilla-Medina; Juan Prado-Olivarez; Francisco J Pérez-Pinal; Alejandro I Barranco-Gutiérrez; Juan J Martínez-Nolasco
Journal:  Sensors (Basel)       Date:  2022-03-15       Impact factor: 3.576

  6 in total

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