Utilizing Electromyographic Video Games Controllers to Improve Outcomes for Prosthesis Users.

Biofeedback Prosthetic Serious gaming Surface electromyography Upper limb

Journal

Applied psychophysiology and biofeedback
ISSN: 1573-3270
Titre abrégé: Appl Psychophysiol Biofeedback
Pays: Germany
ID NLM: 9712383

Informations de publication

Date de publication:
01 Aug 2023
Historique:
accepted: 12 07 2023
medline: 1 8 2023
pubmed: 1 8 2023
entrez: 1 8 2023
Statut: aheadofprint

Résumé

A study was developed for a limb-different accessible video game controller that utilizes an electromyographic sensor to control gameplay actions. Data was collected from 50 college-aged student participants. This biofeedback-based serious game trains users in a virtual capacity, through the visualization of muscle contraction, via the movement of the video game character. The training platform has been developed to accompany the corresponding electromyographic actuated prosthetic arm device, leveraging the same control scheme to enable the translation of hand gesture states. This study evaluated the controller, user interface, and gameplay to identify training improvement outcomes and user satisfaction. Study participants were divided into two cohorts that differed in their intervention between the pre-test and post-test challenge course. Cohort one had a free play environment that encouraged learning through algorithmically generated track patterns and the use of powerups. In contrast, cohort two repeated the challenge mode, which was made up of a course of rings to jump through and focused on targeted muscle discretization via character jump heights correlated to muscle output. Data were collected to develop and validate training methods and identify overall game satisfaction and usability. The results of this study indicated an increase in the user's ability to be successful based on time on task with the intervention. The study also evaluated the usability and participant experience with the intervention.

Identifiants

pubmed: 37526785
doi: 10.1007/s10484-023-09598-y
pii: 10.1007/s10484-023-09598-y
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2023. The Author(s).

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Auteurs

Shea McLinden (S)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA.

Peter Smith (P)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA. Peter.Smith@UCF.edu.

Matt Dombrowski (M)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA.

Calvin MacDonald (C)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA.

Devon Lynn (D)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA.

Katherine Tran (K)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA.

Kelsey Robinson (K)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA.

Dominique Courbin (D)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA.

John Sparkman (J)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA.

Albert Manero (A)

Limbitless Solutions, University of Central Florida, 12703 Research Pkwy Suite 100, Orlando, FL, 32826, USA. albert@limbitless-solutions.org.

Classifications MeSH