Literature DB >> 23786360

Accuracy of Kinect's skeleton tracking for upper body rehabilitation applications.

Amir Mobini1, Saeed Behzadipour, Mahmoud Saadat Foumani.   

Abstract

UNLABELLED: Games and their use in rehabilitation have formed a new and rapidly growing area of research. A critical hardware component of rehabilitation programs is the input device that measures the patients' movements. After Microsoft released Kinect, extensive research has been initiated on its applications as an input device for rehabilitation. However, since most of the works in this area rely on a qualitative determination of the joints' movements rather than an accurate quantitative one, detailed analysis of patients' movements is hindered. The aim of this article is to determine the accuracy of the Kinect's joint tracking. To fulfill this task, a model of upper body was fabricated. The displacements of the joint centers were estimated by Kinect at different positions and were then compared with the actual ones from measurement. Moreover, the dependency of Kinect's error on distance and joint type was measured and analyzed. IMPLICATIONS FOR REHABILITATION: It measures and reports the accuracy of a sensor that can be directly used for monitoring physical therapy exercises. Using this sensor facilitates remote rehabilitation.

Entities:  

Keywords:  Accuracy; Kinect; rehabilitation; skeleton tracking

Mesh:

Year:  2013        PMID: 23786360     DOI: 10.3109/17483107.2013.805825

Source DB:  PubMed          Journal:  Disabil Rehabil Assist Technol        ISSN: 1748-3107


  12 in total

1.  Using motion capture to assess colonoscopy experience level.

Authors:  Morten Bo Svendsen; Louise Preisler; Jens Georg Hillingsoe; Lars Bo Svendsen; Lars Konge
Journal:  World J Gastrointest Endosc       Date:  2014-05-16

2.  Modifying Kinect placement to improve upper limb joint angle measurement accuracy.

Authors:  Na Jin Seo; Mojtaba F Fathi; Pilwon Hur; Vincent Crocher
Journal:  J Hand Ther       Date:  2016-10-18       Impact factor: 1.950

3.  Attentional Demand of a Virtual Reality-Based Reaching Task in Nondisabled Older Adults.

Authors:  Yi-An Chen; Yu-Chen Chung; Rachel Proffitt; Eric Wade; Carolee Winstein
Journal:  J Mot Learn Dev       Date:  2015-12

Review 4.  Engineering Aspects of Incidence, Prevalence, and Management of Osteoarthritis: A Review.

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Journal:  Ann Biomed Eng       Date:  2022-01-21       Impact factor: 3.934

Review 5.  Monitoring Methods of Human Body Joints: State-of-the-Art and Research Challenges.

Authors:  Abu Ilius Faisal; Sumit Majumder; Tapas Mondal; David Cowan; Sasan Naseh; M Jamal Deen
Journal:  Sensors (Basel)       Date:  2019-06-10       Impact factor: 3.576

6.  Test-retest reliability of Kinect's measurements for the evaluation of upper body recovery of stroke patients.

Authors:  A Mobini; S Behzadipour; M Saadat
Journal:  Biomed Eng Online       Date:  2015-08-04       Impact factor: 2.819

7.  A Framework to Automate Assessment of Upper-Limb Motor Function Impairment: A Feasibility Study.

Authors:  Paul Otten; Jonghyun Kim; Sang Hyuk Son
Journal:  Sensors (Basel)       Date:  2015-08-14       Impact factor: 3.576

8.  Using perceptive computing in multiple sclerosis - the Short Maximum Speed Walk test.

Authors:  Janina Behrens; Caspar Pfüller; Sebastian Mansow-Model; Karen Otte; Friedemann Paul; Alexander U Brandt
Journal:  J Neuroeng Rehabil       Date:  2014-05-27       Impact factor: 4.262

Review 9.  A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation.

Authors:  Hossein Mousavi Hondori; Maryam Khademi
Journal:  J Med Eng       Date:  2014-12-10

10.  The use of Xbox Kinect™ in a Paediatric Burns Unit.

Authors:  Eleonora I Lozano; Joanne L Potterton
Journal:  S Afr J Physiother       Date:  2018-04-09
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