Designing an immersive virtual reality environment for hand
rehabilitation purposes: A preliminary study.
Abstract
This study investigates the influence of immersive virtual reality
environments and gamification on the classification of imaginary motor
(MI) signals and the associated increase in energy in the motor cortex
region for neurorehabilitation purposes. Two immersive virtual
environments, indoor and outdoor, were selected, each with gamified and
non-gamified scenarios. Event-Related Desynchronization (ERD) data
underwent analyses to determine if there were significant differences in
ERD levels between distinct age groups and whether Fully Immersive
Virtual Reality (FIVR) environments induced notable energy increases.
The initial analysis found no significant energy changes between age
groups under constant environmental conditions. In the second analysis,
FIVR environments did not lead to a statistically significant increase
in cortical energy for the 21–24 age group (Group I). However, a
notable difference in cortical energy increase was identified between
gamified and non-gamified environments within the 32–43 age group
(Group II). The study also explored the impact of environmental factors
on MI signal classification using four deep learning algorithms. The
Recurrent Neural Network (RNN) classifier exhibited the highest
performance, with an average accuracy of 86.83%. Signals recorded
indoors showed higher average classification performance, with a
significant difference observed among age groups. Group I participants
performed better in non-gamified environments (88.8%), while Group II
achieved high performance indoors, especially in the gamified scenario
(93.6%). Overall, the research underscores the potential of immersive
virtual environments and gamification in enhancing MI signal
classification and cortical energy increase, with age and environmental
factors influencing the outcomes.