Electrophysiological Insights in Exergaming-Electroencephalography Data Recording and Movement Artifact Detection:
Carolina Rico-Olarte1,2, Diego M Lopez1, Bjoern M Eskofier2
1Telematics Department, Universidad del Cauca, Popayán, Colombia.
JMIR Serious Games
|April 7, 2025
Summary
This review explores using electroencephalography (EEG) with exergames for cognitive rehabilitation. It highlights challenges with motion artifacts and calls for better methods to improve data reliability.
Area of Science:
- Neuroscience
- Rehabilitation Technology
- Human-Computer Interaction
Background:
- Exergames combine physical activity with interactive technology for learning and rehabilitation.
- Assessing cognitive rehabilitation progress via brain activity (EEG) is valuable but challenged by motion artifacts.
- A comprehensive guide for artifact removal in exergaming EEG is lacking.
Purpose of the Study:
- To identify studies using EEG during exergaming.
- To analyze data handling and analysis methods, focusing on movement artifact mitigation.
- To synthesize current practices and identify research gaps.
Main Methods:
- Systematic review of 5 databases across multiple time points.
- Inclusion criteria: human participants, exergame interaction, EEG for brain activity.
- Methodological quality assessed using a standardized tool; data synthesized quantitatively.
Main Results:
- 17 studies included, all using EEG during exergames, primarily for attention/concentration assessment.
- Alpha wave was the most analyzed EEG band.
- Common artifact removal: visual inspection, independent component analysis; significant bias risk identified (most studies rated fair/poor).
Conclusions:
- Recording brain activity via EEG during exergaming is feasible.
- Current methodologies and reporting standards for motion artifact removal need improvement for reliable cognitive rehabilitation.
- Further research is recommended to enhance EEG-based exergaming interventions.
