Literature DB >> 26065332

Gait assessment using the Microsoft Xbox One Kinect: Concurrent validity and inter-day reliability of spatiotemporal and kinematic variables.

Benjamin F Mentiplay1, Luke G Perraton1, Kelly J Bower1, Yong-Hao Pua2, Rebekah McGaw1, Sophie Heywood1, Ross A Clark3.   

Abstract

The revised Xbox One Kinect, also known as the Microsoft Kinect V2 for Windows, includes enhanced hardware which may improve its utility as a gait assessment tool. This study examined the concurrent validity and inter-day reliability of spatiotemporal and kinematic gait parameters estimated using the Kinect V2 automated body tracking system and a criterion reference three-dimensional motion analysis (3DMA) marker-based camera system. Thirty healthy adults performed two testing sessions consisting of comfortable and fast paced walking trials. Spatiotemporal outcome measures related to gait speed, speed variability, step length, width and time, foot swing velocity and medial-lateral and vertical pelvis displacement were examined. Kinematic outcome measures including ankle flexion, knee flexion and adduction and hip flexion were examined. To assess the agreement between Kinect and 3DMA systems, Bland-Altman plots, relative agreement (Pearson's correlation) and overall agreement (concordance correlation coefficients) were determined. Reliability was assessed using intraclass correlation coefficients, Cronbach's alpha and standard error of measurement. The spatiotemporal measurements had consistently excellent (r≥0.75) concurrent validity, with the exception of modest validity for medial-lateral pelvis sway (r=0.45-0.46) and fast paced gait speed variability (r=0.73). In contrast kinematic validity was consistently poor to modest, with all associations between the systems weak (r<0.50). In those measures with acceptable validity, the inter-day reliability was similar between systems. In conclusion, while the Kinect V2 body tracking may not accurately obtain lower body kinematic data, it shows great potential as a tool for measuring spatiotemporal aspects of gait.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Keywords:  Biomechanics; Gaming; Kinect V2; Kinect for Windows; Low-cost technology; Physical function; Walking

Mesh:

Year:  2015        PMID: 26065332     DOI: 10.1016/j.jbiomech.2015.05.021

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  44 in total

1.  Effects of narrow-base walking and dual tasking on gait spatiotemporal characteristics in anterior cruciate ligament-injured adults compared to healthy adults.

Authors:  Masood Mazaheri; Hossein Negahban; Maryam Soltani; Mohammad Mehravar; Shirin Tajali; Masumeh Hessam; Mahyar Salavati; Idsart Kingma
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2016-02-09       Impact factor: 4.342

2.  Consensus Paper: Ataxic Gait.

Authors:  Pierre Cabaraux; Sunil K Agrawal; Huaying Cai; Rocco Salvatore Calabro; Carlo Casali; Loic Damm; Sarah Doss; Christophe Habas; Anja K E Horn; Winfried Ilg; Elan D Louis; Hiroshi Mitoma; Vito Monaco; Maria Petracca; Alberto Ranavolo; Ashwini K Rao; Serena Ruggieri; Tommaso Schirinzi; Mariano Serrao; Susanna Summa; Michael Strupp; Olivia Surgent; Matthis Synofzik; Shuai Tao; Hiroo Terasi; Diego Torres-Russotto; Brittany Travers; Jaimie A Roper; Mario Manto
Journal:  Cerebellum       Date:  2022-04-12       Impact factor: 3.847

3.  Feasibility of Markerless Motion Capture for Three-Dimensional Gait Assessment in Community Settings.

Authors:  Theresa E McGuirk; Elliott S Perry; Wandasun B Sihanath; Sherveen Riazati; Carolynn Patten
Journal:  Front Hum Neurosci       Date:  2022-06-09       Impact factor: 3.473

4.  Evaluation of lower extremity gait analysis using Kinect V2® tracking system.

Authors:  Takuya Usami; Kazuki Nishida; Hirotaka Iguchi; Taro Okumura; Hiroaki Sakai; Ruido Ida; Mitsuya Horiba; Shuuto Kashima; Kento Sahashi; Hayato Asai; Yuko Nagaya; Hideki Murakami; Yoshino Ueki; Gen Kuroyanagi
Journal:  SICOT J       Date:  2022-06-24

5.  Autonomous modeling of repetitive movement for rehabilitation exercise monitoring.

Authors:  Prayook Jatesiktat; Guan Ming Lim; Christopher Wee Keong Kuah; Dollaporn Anopas; Wei Tech Ang
Journal:  BMC Med Inform Decis Mak       Date:  2022-07-03       Impact factor: 3.298

6.  Verification of gait analysis method fusing camera-based pose estimation and an IMU sensor in various gait conditions.

Authors:  Masataka Yamamoto; Koji Shimatani; Yuto Ishige; Hiroshi Takemura
Journal:  Sci Rep       Date:  2022-10-21       Impact factor: 4.996

7.  INTER- AND INTRA-RATER RELIABILITY OF PERFORMANCE MEASURES COLLECTED WITH A SINGLE-CAMERA MOTION ANALYSIS SYSTEM.

Authors:  Nathanial A Bates; April L McPherson; John D Berry; Timothy E Hewett
Journal:  Int J Sports Phys Ther       Date:  2017-08

8.  A Video-Based Classification System for Assessing Locomotor Skills in Children.

Authors:  Daniel H K Chow; Wilson H W Cheng; Simone S M Tam
Journal:  J Sports Sci Med       Date:  2020-08-13       Impact factor: 2.988

9.  Walking speed measurement technology: A review.

Authors:  Yohanna MejiaCruz; Jean Franco; Garret Hainline; Stacy Fritz; Zhaoshuo Jiang; Juan M Caicedo; Benjamin Davis; Victor Hirth
Journal:  Curr Geriatr Rep       Date:  2021-01-20

Review 10.  Validity of the Kinect for Gait Assessment: A Focused Review.

Authors:  Shmuel Springer; Galit Yogev Seligmann
Journal:  Sensors (Basel)       Date:  2016-02-04       Impact factor: 3.576

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