Literature DB >> 33348775

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

Peter Beshara1,2,3, Judy F Chen1,2, Andrew C Read1, Pierre Lagadec4, Tian Wang2,3, William Robert Walsh2,3.   

Abstract

BACKGROUND: Objective assessment of shoulder joint active range of motion (AROM) is critical to monitor patient progress after conservative or surgical intervention. Advancements in miniature devices have led researchers to validate inertial sensors to capture human movement. This study investigated the construct validity as well as intra- and inter-rater reliability of active shoulder mobility measurements using a coupled system of inertial sensors and the Microsoft Kinect (HumanTrak).
METHODS: 50 healthy participants with no history of shoulder pathology were tested bilaterally for fixed and free ROM: (1) shoulder flexion, and (2) abduction using HumanTrak and goniometry. The repeat testing of the standardised protocol was completed after seven days by two physiotherapists.
RESULTS: All HumanTrak shoulder movements demonstrated adequate reliability (intra-class correlation (ICC) ≥ 0.70). HumanTrak demonstrated higher intra-rater reliability (ICCs: 0.93 and 0.85) than goniometry (ICCs: 0.75 and 0.53) for measuring free shoulder flexion and abduction AROM, respectively. Similarly, HumanTrak demonstrated higher intra-rater reliability (ICCs: 0.81 and 0.94) than goniometry (ICCs: 0.70 and 0.93) for fixed flexion and abduction AROM, respectively. Construct validity between HumanTrak and goniometry was adequate except for free abduction. The differences between raters were predominately acceptable and below ±10°.
CONCLUSIONS: These results indicated that the HumanTrak system is an objective, valid and reliable way to assess and track shoulder ROM.

Entities:  

Keywords:  Kinect; goniometry; measurement; range of motion; sensor; shoulder

Mesh:

Year:  2020        PMID: 33348775      PMCID: PMC7766751          DOI: 10.3390/s20247238

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  56 in total

1.  Use of multiple wearable inertial sensors in upper limb motion tracking.

Authors:  Huiyu Zhou; Thomas Stone; Huosheng Hu; Nigel Harris
Journal:  Med Eng Phys       Date:  2007-01-23       Impact factor: 2.242

2.  Reliability and validity analyzes of Kinect V2 based measurement system for shoulder motions.

Authors:  Burakhan Çubukçu; Uğur Yüzgeç; Raif Zileli; Ahu Zileli
Journal:  Med Eng Phys       Date:  2019-12-25       Impact factor: 2.242

3.  Validity and reliability of Kinect skeleton for measuring shoulder joint angles: a feasibility study.

Authors:  M E Huber; A L Seitz; M Leeser; D Sternad
Journal:  Physiotherapy       Date:  2015-04-09       Impact factor: 3.358

4.  A technical support tool for joint range of motion determination in functional diagnostics - an inter-rater study.

Authors:  Christoph Schiefer; Thomas Kraus; Rolf P Ellegast; Elke Ochsmann
Journal:  J Occup Med Toxicol       Date:  2015-04-29       Impact factor: 2.646

5.  Inter- and intrarater reliability of goniometry and hand held dynamometry for patients with subacromial impingement syndrome.

Authors:  Georg Fieseler; Kevin G Laudner; Lars Irlenbusch; Henrike Meyer; Stephan Schulze; Karl-Stefan Delank; Souhail Hermassi; Thomas Bartels; René Schwesig
Journal:  J Exerc Rehabil       Date:  2017-12-27

6.  The Validity and Reliability of a Kinect v2-Based Gait Analysis System for Children with Cerebral Palsy.

Authors:  Yunru Ma; Kumar Mithraratne; Nichola C Wilson; Xiangbin Wang; Ye Ma; Yanxin Zhang
Journal:  Sensors (Basel)       Date:  2019-04-07       Impact factor: 3.576

7.  Validity and Reliability of Upper Limb Functional Assessment Using the Microsoft Kinect V2 Sensor.

Authors:  Laisi Cai; Ye Ma; Shuping Xiong; Yanxin Zhang
Journal:  Appl Bionics Biomech       Date:  2019-02-11       Impact factor: 1.781

8.  Assessment of Shoulder Range of Motion Using a Wireless Inertial Motion Capture Device-A Validation Study.

Authors:  Michael Rigoni; Stephen Gill; Sina Babazadeh; Osama Elsewaisy; Hugh Gillies; Nhan Nguyen; Pubudu N Pathirana; Richard Page
Journal:  Sensors (Basel)       Date:  2019-04-13       Impact factor: 3.576

9.  Bilateral Tactile Feedback-Enabled Training for Stroke Survivors Using Microsoft KinectTM.

Authors:  Abbas Orand; Eren Erdal Aksoy; Hiroyuki Miyasaka; Carolyn Weeks Levy; Xin Zhang; Carlo Menon
Journal:  Sensors (Basel)       Date:  2019-08-08       Impact factor: 3.576

10.  Statistical Validation for Clinical Measures: Repeatability and Agreement of Kinect™-Based Software.

Authors:  Natalia Lopez; Elisa Perez; Emanuel Tello; Alejandro Rodrigo; Max E Valentinuzzi
Journal:  Biomed Res Int       Date:  2018-03-20       Impact factor: 3.411

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  3 in total

1.  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

2.  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

3.  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

  3 in total

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