Literature DB >> 27387901

Concurrent validity of the Microsoft Kinect for Windows v2 for measuring spatiotemporal gait parameters.

Elham Dolatabadi1, Babak Taati2, Alex Mihailidis2.   

Abstract

This paper presents a study to evaluate the concurrent validity of the Microsoft Kinect for Windows v2 for measuring the spatiotemporal parameters of gait. Twenty healthy adults performed several sequences of walks across a GAITRite mat under three different conditions: usual pace, fast pace, and dual task. Each walking sequence was simultaneously captured with two Kinect for Windows v2 and the GAITRite system. An automated algorithm was employed to extract various spatiotemporal features including stance time, step length, step time and gait velocity from the recorded Kinect v2 sequences. Accuracy in terms of reliability, concurrent validity and limits of agreement was examined for each gait feature under different walking conditions. The 95% Bland-Altman limits of agreement were narrow enough for the Kinect v2 to be a valid tool for measuring all reported spatiotemporal parameters of gait in all three conditions. An excellent intraclass correlation coefficient (ICC2, 1) ranging from 0.9 to 0.98 was observed for all gait measures across different walking conditions. The inter trial reliability of all gait parameters were shown to be strong for all walking types (ICC3, 1 > 0.73). The results of this study suggest that the Kinect for Windows v2 has the capacity to measure selected spatiotemporal gait parameters for healthy adults.
Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Keywords:  Concurrent validity; GAITRite; Gait; Kinect v2; Rehabilitation; Reliability; Spatiotemporal

Mesh:

Year:  2016        PMID: 27387901     DOI: 10.1016/j.medengphy.2016.06.015

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  26 in total

1.  Random forest-based classsification and analysis of hemiplegia gait using low-cost depth cameras.

Authors:  Guoliang Luo; Yean Zhu; Rui Wang; Yang Tong; Wei Lu; Haolun Wang
Journal:  Med Biol Eng Comput       Date:  2019-12-18       Impact factor: 2.602

2.  Concurrent Validity of Zeno Instrumented Walkway and Video-Based Gait Features in Adults With Parkinson's Disease.

Authors:  Andrea Sabo; Carolina Gorodetsky; Alfonso Fasano; Andrea Iaboni; Babak Taati
Journal:  IEEE J Transl Eng Health Med       Date:  2022-06-03

Review 3.  A review of computational approaches for evaluation of rehabilitation exercises.

Authors:  Yalin Liao; Aleksandar Vakanski; Min Xian; David Paul; Russell Baker
Journal:  Comput Biol Med       Date:  2020-03-04       Impact factor: 4.589

4.  Measuring Gait Variables Using Computer Vision to Assess Mobility and Fall Risk in Older Adults With Dementia.

Authors:  Kimberley-Dale Ng; Sina Mehdizadeh; Andrea Iaboni; Avril Mansfield; Alastair Flint; Babak Taati
Journal:  IEEE J Transl Eng Health Med       Date:  2020-05-28       Impact factor: 3.316

5.  Automatic Detection of Compensation During Robotic Stroke Rehabilitation Therapy.

Authors:  Ying Xuan Zhi; Michelle Lukasik; Michael H Li; Elham Dolatabadi; Rosalie H Wang; Babak Taati
Journal:  IEEE J Transl Eng Health Med       Date:  2017-12-15       Impact factor: 3.316

6.  Recognition of a Person Wearing Sport Shoes or High Heels through Gait Using Two Types of Sensors.

Authors:  Marcin Derlatka; Mariusz Bogdan
Journal:  Sensors (Basel)       Date:  2018-05-21       Impact factor: 3.576

7.  Kinect V2 Performance Assessment in Daily-Life Gestures: Cohort Study on Healthy Subjects for a Reference Database for Automated Instrumental Evaluations on Neurological Patients.

Authors:  Alessandro Scano; Andrea Chiavenna; Matteo Malosio; Lorenzo Molinari Tosatti
Journal:  Appl Bionics Biomech       Date:  2017-11-22       Impact factor: 1.781

8.  Assessment of Parkinsonian gait in older adults with dementia via human pose tracking in video data.

Authors:  Andrea Sabo; Sina Mehdizadeh; Kimberley-Dale Ng; Andrea Iaboni; Babak Taati
Journal:  J Neuroeng Rehabil       Date:  2020-07-14       Impact factor: 4.262

9.  Validation of Foot Placement Locations from Ankle Data of a Kinect v2 Sensor.

Authors:  Daphne Geerse; Bert Coolen; Detmar Kolijn; Melvyn Roerdink
Journal:  Sensors (Basel)       Date:  2017-10-10       Impact factor: 3.576

10.  Quantifying Spatiotemporal Gait Parameters with HoloLens in Healthy Adults and People with Parkinson's Disease: Test-Retest Reliability, Concurrent Validity, and Face Validity.

Authors:  Daphne J Geerse; Bert Coolen; Melvyn Roerdink
Journal:  Sensors (Basel)       Date:  2020-06-05       Impact factor: 3.576

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.