Discover datasets

STRUM is a dyadic neuroergonomics dataset in which pairs of participants perform a collaborative urban-reconnaissance task while a time-synchronized multimodal sensor suite records both members simultaneously via Lab Streaming Layer. It covers 33 sessions and 66 participants, with high-density EEG, EMG, ECG/EOG, motion capture, eye-tracking, force plate and controller behavior. Each participant has their own subject directory, and the pairing is encoded in participants.tsv so that analyses can split by pair.

Participants

66

Channels

207 (biosemi)

HED

v8.4.0

Size

512 GB

Version

v1.0.1

Updated

Sep 28, 2026

A longitudinal brain-machine interface dataset from seven healthy adults who controlled a Rex Bionics lower-limb exoskeleton through motor imagery (walk/stop). Each participant completed nine sessions, each with an open-loop calibration training phase followed by twelve closed-loop control trials and extended 6-minute walk and stop imagery tasks. The dataset includes 60-channel EEG, EOG, IMU motion data from the head and exoskeleton, and exoskeleton control and feedback signals.

Participants

7

Channels

60

Size

3.62 GB

Version

v1.0.0

Updated

Jun 30, 2026

A mobile brain/body imaging (MoBI) dataset combining 157-channel EEG and full-body motion capture from 20 healthy adults performing a spatial heading-change task. Participants followed a moving sphere and returned to their initial heading either by physically rotating on the spot or by using a joystick with a 2D desktop display. The dataset supports investigation of human cortical dynamics during full-body rotation and is formatted according to BIDS.

Participants

20

Channels

160 (other)

Citations

37

Size

61.4 GB

Version

v1.0.0

Updated

Jun 24, 2026

EEG and motion-capture dataset from 19 participants performing a haptic interaction task in virtual reality, in which participants touched virtual objects while visual, vibrotactile, and electrical muscle stimulation feedback was varied. Some trials were designed as oddball conflicts to elicit prediction error responses. The recordings support research on the neural correlates of prediction errors and on detecting unrealistic interactions in cyber-physical systems.

Participants

19

Channels

63 (10-10)

Citations

55

Size

11.4 GB

Version

v1.0.0

Updated

Jun 22, 2026