Literature DB >> 30406430

A Novel Methodology for Extracting and Evaluating Therapeutic Movements in Game-Based Motion Capture Rehabilitation Systems.

Zhichao Yang1, Mohammad H Rafiei2,3,4, Alexis Hall2, Caroline Thomas2, Hali A Midtlien2, Alexander Hasselbach2, Hojjat Adeli5, Lynne V Gauthier2,4.   

Abstract

Virtual rehabilitation yields outcomes that are at least as good as traditional care for improving upper limb function and the capacity to carry out activities of daily living. Due to the advent of low-cost gaming systems and patient preference for game-based therapies, video game technology will likely be increasingly utilized in physical therapy practice in the coming years. Gaming systems that incorporate low-cost motion capture technology often generate large datasets of therapeutic movements performed over the course of rehabilitation. An infrastructure has yet to be established, however, to enable efficient processing of large quantities of movement data that are collected outside of a controlled laboratory setting. In this paper, a methodology is presented for extracting and evaluating therapeutic movements from game-based rehabilitation that occurs in uncontrolled and unmonitored settings. By overcoming these challenges, meaningful kinematic analysis of rehabilitation trajectory within an individual becomes feasible. Moreover, this methodological approach provides a vehicle for analyzing large datasets generated in uncontrolled clinical settings to enable better predictions of rehabilitation potential and dose-response relationships for personalized medicine.

Entities:  

Keywords:  Clustering algorithm; Hemiparesis; Kinect; Motion capture; Motor rehabilitation; Probability density function; Serious games; Signal processing; Stroke; Telerehabilitation

Mesh:

Year:  2018        PMID: 30406430      PMCID: PMC7183412          DOI: 10.1007/s10916-018-1113-4

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  20 in total

1.  Assessing Wolf motor function test as outcome measure for research in patients after stroke.

Authors:  S L Wolf; P A Catlin; M Ellis; A L Archer; B Morgan; A Piacentino
Journal:  Stroke       Date:  2001-07       Impact factor: 7.914

2.  A New Neural Dynamic Classification Algorithm.

Authors:  Mohammad Hossein Rafiei; Hojjat Adeli
Journal:  IEEE Trans Neural Netw Learn Syst       Date:  2017-07-25       Impact factor: 10.451

3.  Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification.

Authors:  Yu Zhang; Yu Wang; Jing Jin; Xingyu Wang
Journal:  Int J Neural Syst       Date:  2016-04-11       Impact factor: 5.866

4.  The Motor Activity Log-28: assessing daily use of the hemiparetic arm after stroke.

Authors:  G Uswatte; E Taub; D Morris; K Light; P A Thompson
Journal:  Neurology       Date:  2006-10-10       Impact factor: 9.910

5.  A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

Authors:  Lilin Guo; Zhenzhong Wang; Mercedes Cabrerizo; Malek Adjouadi
Journal:  Int J Neural Syst       Date:  2016-09-01       Impact factor: 5.866

6.  Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial.

Authors:  Steven L Wolf; Carolee J Winstein; J Philip Miller; Edward Taub; Gitendra Uswatte; David Morris; Carol Giuliani; Kathye E Light; Deborah Nichols-Larsen
Journal:  JAMA       Date:  2006-11-01       Impact factor: 56.272

7.  Method for enhancing real-world use of a more affected arm in chronic stroke: transfer package of constraint-induced movement therapy.

Authors:  Edward Taub; Gitendra Uswatte; Victor W Mark; David M Morris; Joydip Barman; Mary H Bowman; Camille Bryson; Adriana Delgado; Staci Bishop-McKay
Journal:  Stroke       Date:  2013-03-21       Impact factor: 7.914

8.  Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly.

Authors:  Bijan Najafi; Kamiar Aminian; Anisoara Paraschiv-Ionescu; François Loew; Christophe J Büla; Philippe Robert
Journal:  IEEE Trans Biomed Eng       Date:  2003-06       Impact factor: 4.538

9.  Reaching in reality and virtual reality: a comparison of movement kinematics in healthy subjects and in adults with hemiparesis.

Authors:  Antonin Viau; Anatol G Feldman; Bradford J McFadyen; Mindy F Levin
Journal:  J Neuroeng Rehabil       Date:  2004-12-14       Impact factor: 4.262

10.  Video Game Rehabilitation for Outpatient Stroke (VIGoROUS): protocol for a multi-center comparative effectiveness trial of in-home gamified constraint-induced movement therapy for rehabilitation of chronic upper extremity hemiparesis.

Authors:  Lynne V Gauthier; Chelsea Kane; Alexandra Borstad; Nancy Strahl; Gitendra Uswatte; Edward Taub; David Morris; Alli Hall; Melissa Arakelian; Victor Mark
Journal:  BMC Neurol       Date:  2017-06-08       Impact factor: 2.474

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  3 in total

1.  Palliative care and infection management at end of life in nursing homes: A descriptive survey.

Authors:  Aluem Tark; Leah V Estrada; Mary E Tresgallo; Denise D Quigley; Patricia W Stone; Mansi Agarwal
Journal:  Palliat Med       Date:  2020-03-10       Impact factor: 4.762

2.  Video game rehabilitation for outpatient stroke (VIGoROUS): A multi-site randomized controlled trial of in-home, self-managed, upper-extremity therapy.

Authors:  Lynne V Gauthier; Deborah S Nichols-Larsen; Gitendra Uswatte; Nancy Strahl; Marie Simeo; Rachel Proffitt; Kristina Kelly; Roger Crawfis; Edward Taub; David Morris; Linda Pax Lowes; Victor Mark; Alexandra Borstad
Journal:  EClinicalMedicine       Date:  2021-12-17

Review 3.  Upper Limb Physical Rehabilitation Using Serious Videogames and Motion Capture Systems: A Systematic Review.

Authors:  Andrea Catherine Alarcón-Aldana; Mauro Callejas-Cuervo; Antonio Padilha Lanari Bo
Journal:  Sensors (Basel)       Date:  2020-10-22       Impact factor: 3.576

  3 in total

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