Literature DB >> 26138411

Choice of Human-Computer Interaction Mode in Stroke Rehabilitation.

Hossein Mousavi Hondori1, Maryam Khademi1, Lucy Dodakian1, Alison McKenzie2, Cristina V Lopes1, Steven C Cramer3.   

Abstract

BACKGROUND AND
OBJECTIVE: Advances in technology are providing new forms of human-computer interaction. The current study examined one form of human-computer interaction, augmented reality (AR), whereby subjects train in the real-world workspace with virtual objects projected by the computer. Motor performances were compared with those obtained while subjects used a traditional human-computer interaction, that is, a personal computer (PC) with a mouse.
METHODS: Patients used goal-directed arm movements to play AR and PC versions of the Fruit Ninja video game. The 2 versions required the same arm movements to control the game but had different cognitive demands. With AR, the game was projected onto the desktop, where subjects viewed the game plus their arm movements simultaneously, in the same visual coordinate space. In the PC version, subjects used the same arm movements but viewed the game by looking up at a computer monitor.
RESULTS: Among 18 patients with chronic hemiparesis after stroke, the AR game was associated with 21% higher game scores (P = .0001), 19% faster reaching times (P = .0001), and 15% less movement variability (P = .0068), as compared to the PC game. Correlations between game score and arm motor status were stronger with the AR version.
CONCLUSIONS: Motor performances during the AR game were superior to those during the PC game. This result is due in part to the greater cognitive demands imposed by the PC game, a feature problematic for some patients but clinically useful for others. Mode of human-computer interface influences rehabilitation therapy demands and can be individualized for patients.
© The Author(s) 2015.

Entities:  

Keywords:  augmented reality; direct interaction; indirect interaction; recovery; stroke

Mesh:

Year:  2015        PMID: 26138411      PMCID: PMC4698231          DOI: 10.1177/1545968315593805

Source DB:  PubMed          Journal:  Neurorehabil Neural Repair        ISSN: 1545-9683            Impact factor:   3.919


  29 in total

1.  S-R compatibility: spatial characteristics of stimulus and response codes.

Authors:  P M FITTS; C M SEEGER
Journal:  J Exp Psychol       Date:  1953-09

2.  Robot-based hand motor therapy after stroke.

Authors:  Craig D Takahashi; Lucy Der-Yeghiaian; Vu Le; Rehan R Motiwala; Steven C Cramer
Journal:  Brain       Date:  2007-12-20       Impact factor: 13.501

3.  Transformation from head- to shoulder-centered representation of target direction in arm movements.

Authors:  J F Soechting; S I Tillery; M Flanders
Journal:  J Cogn Neurosci       Date:  1990       Impact factor: 3.225

4.  A Spatial Augmented Reality rehab system for post-stroke hand rehabilitation.

Authors:  Hossein Mousavi Hondori; Maryam Khademi; Lucy Dodakian; Steven C Cramer; Cristina Videira Lopes
Journal:  Stud Health Technol Inform       Date:  2013

5.  Validation of the Box and Block Test as a measure of dexterity of elderly people: reliability, validity, and norms studies.

Authors:  J Desrosiers; G Bravo; R Hébert; E Dutil; L Mercier
Journal:  Arch Phys Med Rehabil       Date:  1994-07       Impact factor: 3.966

6.  Virtual Reality for Sensorimotor Rehabilitation Post-Stroke: The Promise and Current State of the Field.

Authors:  Gerard G Fluet; Judith E Deutsch
Journal:  Curr Phys Med Rehabil Rep       Date:  2013-03

7.  Kinematics of pointing movements made in a virtual versus a physical 3-dimensional environment in healthy and stroke subjects.

Authors:  Luiz A Knaut; Sandeep K Subramanian; Bradford J McFadyen; Daniel Bourbonnais; Mindy F Levin
Journal:  Arch Phys Med Rehabil       Date:  2009-05       Impact factor: 3.966

8.  Targeted engagement of a dorsal premotor circuit in the treatment of post-stroke paresis.

Authors:  Lucy Dodakian; Kelli G Sharp; Jill See; Neil S Abidi; Khoa Mai; Brett W Fling; Vu H Le; Steven C Cramer
Journal:  NeuroRehabilitation       Date:  2013       Impact factor: 2.138

9.  Multisensory integration during motor planning.

Authors:  Samuel J Sober; Philip N Sabes
Journal:  J Neurosci       Date:  2003-08-06       Impact factor: 6.167

10.  Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial.

Authors:  Andrea Turolla; Mauro Dam; Laura Ventura; Paolo Tonin; Michela Agostini; Carla Zucconi; Pawel Kiper; Annachiara Cagnin; Lamberto Piron
Journal:  J Neuroeng Rehabil       Date:  2013-08-01       Impact factor: 4.262

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  10 in total

1.  Efficacy and safety of non-immersive virtual reality exercising in stroke rehabilitation (EVREST): a randomised, multicentre, single-blind, controlled trial.

Authors:  Gustavo Saposnik; Leonardo G Cohen; Muhammad Mamdani; Sepideth Pooyania; Michelle Ploughman; Donna Cheung; Jennifer Shaw; Judith Hall; Peter Nord; Sean Dukelow; Yongchai Nilanont; Felipe De Los Rios; Lisandro Olmos; Mindy Levin; Robert Teasell; Ashley Cohen; Kevin Thorpe; Andreas Laupacis; Mark Bayley
Journal:  Lancet Neurol       Date:  2016-06-27       Impact factor: 44.182

2.  Effect of a mixed reality-based intervention on arm, hand, and finger function on chronic stroke.

Authors:  Carolina Colomer; Roberto Llorens; Enrique Noé; Mariano Alcañiz
Journal:  J Neuroeng Rehabil       Date:  2016-05-11       Impact factor: 4.262

Review 3.  The Clinical Utility of Virtual Reality in Neurorehabilitation: A Systematic Review.

Authors:  Thais Massetti; Talita Dias da Silva; Tânia Brusque Crocetta; Regiani Guarnieri; Bruna Leal de Freitas; Priscila Bianchi Lopes; Suzanna Watson; James Tonks; Carlos Bandeira de Mello Monteiro
Journal:  J Cent Nerv Syst Dis       Date:  2018-11-27

4.  ARMIA: A Sensorized Arm Wearable for Motor Rehabilitation.

Authors:  Gabriel J Garcia; Angel Alepuz; Guillermo Balastegui; Lluis Bernat; Jonathan Mortes; Sheila Sanchez; Esther Vera; Carlos A Jara; Vicente Morell; Jorge Pomares; Jose L Ramon; Andres Ubeda
Journal:  Biosensors (Basel)       Date:  2022-06-29

Review 5.  Examining the effectiveness of virtual, augmented, and mixed reality (VAMR) therapy for upper limb recovery and activities of daily living in stroke patients: a systematic review and meta-analysis.

Authors:  Sze Chit Leong; Yuk Ming Tang; Fong Mei Toh; Kenneth N K Fong
Journal:  J Neuroeng Rehabil       Date:  2022-08-24       Impact factor: 5.208

6.  Effects of virtual body-representation on motor skill learning.

Authors:  Yongmin Shin; Jaeseo Lim; Yonggwan Kim; Deog-Gyu Seo; Jungjoon Ihm
Journal:  Sci Rep       Date:  2022-09-10       Impact factor: 4.996

7.  Patient-Tailored Augmented Reality Games for Assessing Upper Extremity Motor Impairments in Parkinson's Disease and Stroke.

Authors:  Paulina J M Bank; Marina A Cidota; P Elma W Ouwehand; Stephan G Lukosch
Journal:  J Med Syst       Date:  2018-10-30       Impact factor: 4.460

8.  Predicting Gains With Visuospatial Training After Stroke Using an EEG Measure of Frontoparietal Circuit Function.

Authors:  Robert J Zhou; Hossein M Hondori; Maryam Khademi; Jessica M Cassidy; Katherine M Wu; Derek Z Yang; Nikhita Kathuria; Fareshte R Erani; Lucy Dodakian; Alison McKenzie; Cristina V Lopes; Walt Scacchi; Ramesh Srinivasan; Steven C Cramer
Journal:  Front Neurol       Date:  2018-07-24       Impact factor: 4.003

9.  Exoskeletons With Virtual Reality, Augmented Reality, and Gamification for Stroke Patients' Rehabilitation: Systematic Review.

Authors:  Omar Mubin; Fady Alnajjar; Nalini Jishtu; Belal Alsinglawi; Abdullah Al Mahmud
Journal:  JMIR Rehabil Assist Technol       Date:  2019-09-08

Review 10.  Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges.

Authors:  Kostas Nizamis; Alkinoos Athanasiou; Sofia Almpani; Christos Dimitrousis; Alexander Astaras
Journal:  Sensors (Basel)       Date:  2021-03-16       Impact factor: 3.576

  10 in total

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