Development and Preliminary Testing of a System for the Multimodal Analysis of Gait Training in a Virtual Reality Environment

Gait training in a virtual reality (VR) environment is promising for children affected by different disorders. However, the efficacy of VR therapy is still under debate, and more research is needed to clarify its effects on clinical conditions. The combination of VR with neuroimaging methods, such a...

Full description

Saved in:
Bibliographic Details
Published in:Electronics (Basel) 2021-11, Vol.10 (22), p.2838
Main Authors: Piazza, Caterina, Pirovano, Ileana, Mastropietro, Alfonso, Genova, Chiara, Gagliardi, Chiara, Turconi, Anna Carla, Malerba, Giorgia, Panzeri, Daniele, Maghini, Cristina, Reni, Gianluigi, Rizzo, Giovanna, Biffi, Emilia
Format: Article
Language:English
Subjects:
Cerebral palsy
Electroencephalography
Electromyography
Fitness equipment
Gait
Kinematics
Medical imaging
Parameters
Patients
Pediatrics
Physiology
Rehabilitation
Sensors
Software
Synchronism
Training
Virtual reality
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Gait training in a virtual reality (VR) environment is promising for children affected by different disorders. However, the efficacy of VR therapy is still under debate, and more research is needed to clarify its effects on clinical conditions. The combination of VR with neuroimaging methods, such as the electroencephalography (EEG), might help in answering this need. The aim of the present work was to set up and test a system for the multimodal analysis of the gait pattern during VR gait training of pediatric populations by analyzing the EEG correlates as well as the kinematic and kinetic parameters of the gait. An EEG system was integrated with the Gait Real-time Analysis Interactive Lab (GRAIL). We developed and validated, with healthy adults (n = 5) and children (n = 4, healthy or affected by cerebral palsy (CP)), the hardware and software integration of the two systems, which allowed the synchronization of the acquired signals and a reliable identification of the initial contact (IC) of each gait cycle, showing good sensitivity and critical success index values. Moreover, we tested the multimodal acquisition by successfully analyzing EEG data and kinematic and kinetic parameters of one healthy child and one child with CP. This system gives the possibility of monitoring the effect of the VR therapy and studying the neural correlates of gait.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics10222838