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

Abstract

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.

A Narrative Review on Multi-Domain Instrumental Approaches to Evaluate Neuromotor Function in Rehabilitation

“…EEG biomarkers, such as the ratio of slow (delta/theta) to fast (alpha/beta) waves, can predict motor outcomes in stroke patients, as they indicate the level of arousal and alertness of the brain [ 60 , 61 ]. EEG can also investigate other neurological disorders that affect motor function, such as PD, which is characterized by reduced motor-evoked potentials and altered EEG microstates [ 62 ]; CP, which shows abnormal EEG patterns and connectivity [ 63 , 64 ]; SCI, which affects the cortico-spinal communication and motor control [ 65 ]; and TBI, which disrupts the functional network organization and integration [ 66 , 67 ].…”

Context expectation influences the gait pattern biomechanics

“…An additional limitation may concern the absence of signals to be coupled with the motion analysis. For example, the presence of wearable electroencephalography (EEG) system recording brain rhythms during walking may provide further insights on the predictive processing via neural decoding of gait phases 65,68 . Its absence in our study does not permit to directly demonstrate anything at the neural level.…”