Literature DB >> 28131678

Digital data acquisition of shoulder range of motion and arm motion smoothness using Kinect v2.

Rizki Fajar Zulkarnain1, Ga-Yeong Kim1, Arnold Adikrishna1, Han Pyo Hong1, Yoon Jeong Kim1, In-Ho Jeon2.   

Abstract

BACKGROUND: Range of motion (ROM) is a clinically important parameter in evaluating joint function. However, dynamic evaluation to determine the quality of the arm motion using digitized measurement is often overlooked during clinical assessment. We evaluated the accuracy of Kinect v2 (Microsoft, Redmond, WA, USA) as a digital tool for measuring shoulder ROM objectively and proposed a concept of motion smoothness reflecting the quality of arm motion.
METHODS: Ten male participants were included in a 2-stage experiment. First, shoulder ROM was measured in 4 static poses (flexion, abduction, external rotation, and internal rotation) with Kinect v2, a 3-dimensional (3D) motion analysis system, and goniometry. Second, participants performed a point-to-point arm motion as naturally as possible. Kinematic data were collected with Kinect v2 and the 3D motion analysis system and then postprocessed to acquire parameters related to motion smoothness, including peak to mean velocity ratio, acceleration to movement time ratio, and number of peaks.
RESULTS: Kinect v2 resulted in very good agreement of ROM measurement (r > 0.9) with the 3D motion analysis (95% limits of agreement < ±8°) compared with goniometry (95% limits of agreement < ±10°). Kinect v2 also showed a good correlation and agreement of measurement of motion quality parameters compared with the 3D motion analysis (peak to mean velocity ratio, acceleration to movement time ratio, and number of peaks: r = 0.769, discrepancy = ±0.1; r = 0.922, discrepancy = ±5%; and mean = 1 ± 0, respectively).
CONCLUSIONS: We show that Kinect v2 can be used as a reliable tool to measure shoulder ROM and arm motion smoothness.
Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Kinect; Shoulder; goniometry; motion analysis; motion smoothness; range of motion

Mesh:

Year:  2017        PMID: 28131678     DOI: 10.1016/j.jse.2016.10.026

Source DB:  PubMed          Journal:  J Shoulder Elbow Surg        ISSN: 1058-2746            Impact factor:   3.019


  8 in total

1.  The contribution of the scapula to active shoulder motion and self-assessed function in three hundred and fifty two patients prior to elective shoulder surgery.

Authors:  Jason E Hsu; David Andrew Hulet; Chris McDonald; Anastasia Whitson; Stacy M Russ; Frederick A Matsen
Journal:  Int Orthop       Date:  2018-07-09       Impact factor: 3.075

2.  The Elbow Physical Examination for Telemedicine Encounters.

Authors:  Cort D Lawton; Stephanie Swensen-Buza; Jakob F Awender; Sridhar Pinnamaneni; Joseph D Lamplot; Warren K Young; Scott A Rodeo; Danyal H Nawabi; Samuel A Taylor; Joshua S Dines
Journal:  HSS J       Date:  2021-02-21

3.  Kinect-based assessment of proximal arm non-use after a stroke.

Authors:  K K A Bakhti; I Laffont; M Muthalib; J Froger; D Mottet
Journal:  J Neuroeng Rehabil       Date:  2018-11-14       Impact factor: 4.262

4.  The Virtual Shoulder Physical Exam.

Authors:  Sridhar Pinnamaneni; Joseph D Lamplot; Scott A Rodeo; Stephanie Swensen-Buza; Cort D Lawton; Joshua S Dines; Warren K Young; Samuel A Taylor
Journal:  HSS J       Date:  2021-02-21

5.  Validity and Reliability of Kinect v2 for Quantifying Upper Body Kinematics during Seated Reaching.

Authors:  Germain Faity; Denis Mottet; Jérôme Froger
Journal:  Sensors (Basel)       Date:  2022-04-02       Impact factor: 3.576

6.  Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry.

Authors:  Jingyuan Fan; Fanbin Gu; Lulu Lv; Zhejin Zhang; Changbing Zhu; Jian Qi; Honggang Wang; Xiaolin Liu; Jiantao Yang; Qingtang Zhu
Journal:  BMC Musculoskelet Disord       Date:  2022-09-21       Impact factor: 2.562

7.  3D Analysis of Upper Limbs Motion during Rehabilitation Exercises Using the KinectTM Sensor: Development, Laboratory Validation and Clinical Application.

Authors:  Bruno Bonnechère; Victor Sholukha; Lubos Omelina; Serge Van Sint Jan; Bart Jansen
Journal:  Sensors (Basel)       Date:  2018-07-10       Impact factor: 3.576

8.  Stability of Kinect for range of motion analysis in static stretching exercises.

Authors:  Fatemeh Mortazavi; Ali Nadian-Ghomsheh
Journal:  PLoS One       Date:  2018-07-24       Impact factor: 3.240

  8 in total

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