Researchers can improve the ecological validity of brain research by studying humans moving in real-world settings. Recent work shows that dual-layer EEG can improve the fidelity of electrocortical recordings during gait, but it is unclear whether these positive results extrapolate to non-locomotor paradigms. For our study, we recorded brain activity with dual-layer EEG while participants played table tennis, a whole-body, responsive sport that could help investigate visuomotor feedback, object interception, and performance monitoring. We characterized artifacts with time-frequency analyses and correlated scalp and reference noise data to determine how well different sensors captured artifacts. As expected, individual scalp channels correlated more with noise-matched channel time series than with head and body acceleration. We then compared artifact removal methods with and without the use of the dual-layer noise electrodes. Independent Component Analysis separated channels into components, and we counted the number of high-quality brain components based on the fit of a dipole model and using an automated labeling algorithm. We found that using noise electrodes for data processing provided cleaner brain components. These results advance technological approaches for recording high fidelity brain dynamics in human behaviors requiring whole body movement, which will be useful for brain science research.
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This content will become publicly available on December 1, 2025
Mobile brain–body imaging data set of indoor treadmill walking and outdoor walking with a visual search task
To fully understand brain processes in the real world, it is necessary to record and quantitatively analyse brain processes during real world human experiences. Mobile electroencephalography (EEG) and physiological data sensors provide new opportunities for studying humans outside of the laboratory. The purpose of this study was to document data from high-density EEG and mobile physiological sensors while humans performed a visual search task both on a treadmill in a laboratory setting and overground in a natural outdoor setting. The data set includes 49 young, healthy participants on an outdoor arboretum path and on a treadmill in a laboratory with a large virtual reality screen. The data provide a valuable research tool for scientists interested in signal processing, electrocortical brain processes, mobile brain imaging, and brain-computer interfaces based on mobile EEG. Given the comparison data between laboratory and real world conditions, researchers can test the viability of new processing algorithms across conditions or investigate changes in electrocortical activity related to behavioural dynamics coded into the data.
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- Award ID(s):
- 1835317
- PAR ID:
- 10552048
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Data in Brief
- Volume:
- 57
- Issue:
- C
- ISSN:
- 2352-3409
- Page Range / eLocation ID:
- 110968
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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