Automatic Motion Classification in Virtual Reality for Telerehabilitation

Can gamified tasks performed in an attractive setting aid telerehabilitation efforts?

Patients are often required to perform repetitive physical tasks during their telerehabilitation process. This monotony may induce a lack of motivation and continuous engagement.

In their newly published study, Profs. Maurizio Porfiri, Oded Nov, Manuel Ruiz Marín, and Preeti Raghavan, postdoctoral researcher Roni Barak Ventura and Undergraduate Student Kora Stewart Hughes propose a citizen science–based approach in which patients perform simple physical tasks by using interactive interfaces in an immersive Virtual Reality environment. In addition to increasing the engagement through a gamified experience, one benefit of this platform is helping to advance scientific causes, thus increasing patients’ motivation.
A new approach is used to facilitate the remote identification and classification of human movements for the automatic assessment of motor performance in telerehabilitation. The team’s findings may help develop motion analysis algorithms in VR-mediated telerehabilitation.

Read the full paper “Data-Driven Classification of Human Movements in Virtual Reality–Based Serious Games: Preclinical Rehabilitation Study in Citizen Science” in Journal of Medical Internet Research Serious Games here.
 

Image credit: Roni Barak Ventura, Anna Sawulska, and Mohammad Tuqan.

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