ArticleSensors (Basel, Switzerland)2024
Synchronization of Neurophysiological and Biomechanical Data in a Real-Time Virtual Gait Analysis System (GRAIL): A Proof-of-Principle Study.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Assessment of dynamic cerebral blood flow changes during cognitive tasks in patients with post-COVID-19 syndrome.Brain communications · 2026Article
- Freezing of gait and the effects of vibrotactile cueing in Parkinson's disease-a study protocol of a cross-sectional multimodal brain imaging approach in virtual walking scenarios.Frontiers in neuroscience · 2026Article
- Multimodal Motion Capture Toolbox for Enhanced Analysis of Intersegmental Coordination in Children with Cerebral Palsy and Typically Developing.Journal of visualized experiments : JoVE · 2025Article
- Article
- Advancing Gait Analysis: Integrating Multimodal Neuroimaging and Extended Reality Technologies.Bioengineering (Basel, Switzerland) · 2025Review
- A Spatio-Temporal Capsule Neural Network with Self-Correlation Routing for EEG Decoding of Semantic Concepts of Imagination and Perception Tasks.Sensors (Basel, Switzerland) · 2024Article
- Adaptive Detection in Real-Time Gait Analysis through the Dynamic Gait Event Identifier.Bioengineering (Basel, Switzerland) · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
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.
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Registered trials
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