Synchronization of Neurophysiological and Biomechanical Data in a Real-Time Virtual Gait Analysis System (GRAIL): A Proof-of-Principle Study

The investigation of gait and its neuronal correlates under more ecologically valid conditions as well as real-time feedback visualization is becoming increasingly important in neuro-motor rehabilitation research. The Gait Real-time Analysis Interactive Lab (GRAIL) offers advanced opportunities for...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2024-06, Vol.24 (12), p.3779
Main Authors: Maas, Stefan A, Göcking, Tim, Stojan, Robert, Voelcker-Rehage, Claudia, Kutz, Dieter F
Format: Article
Language:English
Subjects:
Adult
Biomechanical Phenomena - physiology
Brain - physiology
Brain research
ecological validity
Electroencephalography
Electroencephalography - methods
Electromyography
Experiments
Female
Fitness equipment
Gait
Gait - physiology
Gait Analysis - methods
Humans
Infrared spectroscopy
instrumented treadmill
Kinematics
Laboratories
Male
Measuring instruments
Medical research
Motion capture
neuroergonomics
neuroimaging
Neurophysiology
neurorehabilitation
Proof of Concept Study
Rehabilitation
Spectroscopy, Near-Infrared - methods
Virtual Reality
Walking - physiology
Young Adult
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Summary:The investigation of gait and its neuronal correlates under more ecologically valid conditions as well as real-time feedback visualization is becoming increasingly important in neuro-motor rehabilitation research. The Gait Real-time Analysis Interactive Lab (GRAIL) offers advanced opportunities for gait and gait-related research by creating more naturalistic yet controlled environments through immersive virtual reality. Investigating the neuronal aspects of gait requires parallel recording of brain activity, such as through mobile electroencephalography (EEG) and/or mobile functional near-infrared spectroscopy (fNIRS), which must be synchronized with the kinetic and /or kinematic data recorded while walking. This proof-of-concept study outlines the required setup by use of the lab streaming layer (LSL) ecosystem for real-time, simultaneous data collection of two independently operating multi-channel EEG and fNIRS measurement devices and gait kinetics. In this context, a customized approach using a photodiode to synchronize the systems is described. This study demonstrates the achievable temporal accuracy of synchronous data acquisition of neurophysiological and kinematic and kinetic data collection in the GRAIL. By using event-related cerebral hemodynamic activity and visually evoked potentials during a start-to-go task and a checkerboard test, we were able to confirm that our measurement system can replicate known physiological phenomena with latencies in the millisecond range and relate neurophysiological and kinetic data to each other with sufficient accuracy.
ISSN:1424-8220
1424-8220
DOI:10.3390/s24123779