Discover datasets

This mobile brain-body imaging (MoBI) study investigates electrocortical correlates of locomotor adaptation during split-belt treadmill walking. Thirty participants performed both abrupt and gradual split-belt walking protocols with a 2:1 belt speed ratio while mobile EEG was recorded. The dataset provides insights into neural mechanisms underlying gait adaptation and motor learning in dynamic walking conditions.

Citations

29

Size

113 GB

Updated

Jun 18, 2026

…signal is captured with EEG001 Movement trigger is captured with UPPT001 Dipole…

Citations

36

Size

20.1 GB

Updated

Jun 21, 2026

Participants

17

…Participants responded whether the target word was semantically related or unrelated to…

Citations

2

Size

17.5 GB

Updated

May 18, 2026

…to EDF format Original and related datasets ----------------------------- This dataset was reformatted into…

Citations

78

Size

152 MB

Updated

May 16, 2026

This mobile brain body imaging (MoBI) dataset comprises EEG recordings from 18 subjects performing a gait adaptation task on a treadmill. Participants were instructed to synchronize their stepping with an auditory pacing stimulus and adapt their gait parameters (step length and rate) in response to tempo shifts. The dataset provides multimodal neurophysiological data during dynamic motor behavior, enabling investigation of neural mechanisms underlying auditory-motor coupling and gait adaptation.

Size

32.0 GB

Updated

Jun 20, 2026

…upper limb movements, EEG, motor imagery, movement execution, low-frequency, time-domain…

Citations

95

Size

8.54 GB

Updated

May 18, 2026

Participants

166

…electroencephalogram, EEG, event-related desynchronization, feature combination, movement related potential, multiclass, single…

Citations

86

Size

493 MB

Updated

Jun 19, 2026

This BIDS-formatted derivative dataset comprises EEG recordings from 15 healthy participants performing a visual P300 oddball task during treadmill walking at 1.6 m/s. The study includes simultaneous scalp-EEG (46 channels), ear-EEG (14 channels), electrooculography (4 channels), and inertial measurement unit recordings (6 channels) sampled at 100 Hz. Data were collected as part of BCI Competition 2020 Track 5 to evaluate brain-computer interface performance under ambulatory conditions. Trials are temporally divided into training, validation, and test sets.

Size

79.7 MB

Updated

Jun 23, 2026