Discover datasets

This dataset contains scalp EEG recordings from 28 participants performing or imagining upper-limb rehabilitation exercises under a multi-paradigm protocol. It was designed to support research on motor-imagery-based brain–computer interfaces (BCI) for upper-limb rehabilitation. The data have been converted to BIDS format from the original dataset published by Chang et al. (2025).

Participants

28

Channels

59 (10-10)

Citations

3

HED

v8.4.0

Size

47.1 GB

Version

v1.0.5

Updated

Aug 20, 2026

…layer electroencephalography (EEG), neck electromyography (EMG), inertial measurement unit (IMU) acceleration, ground…

Participants

32

Channels

120 (other)

Citations

3

Size

62.5 GB

Version

v1.0.0

Updated

Aug 19, 2026

A multi-joint upper-limb motor imagery EEG dataset comprising 18 healthy subjects performing eight distinct imagery tasks involving hand, wrist, elbow, and shoulder movements. The dataset contains 320 trials per subject acquired at 1000 Hz using 62-channel EEG with visual cue-based paradigm, designed for brain-computer interface research and motor rehabilitation applications.

Participants

18

Channels

62 (10-10)

Citations

4

HED

v8.4.0

Size

50.0 GB

Version

v1.0.2

Updated

Aug 18, 2026

…I also collected Corrugator EMG (may be labeled EKG) and Skin Conductance…

Participants

23

Channels

64 (10-10)

Size

4.72 GB

Version

v1.0.0

Updated

Jul 10, 2026

Imported from OpenNeuro ds004849

Participants

1

Channels

64 (10-10)

Citations

4

HED

v8.1.0

Size

78.9 MB

Version

v1.0.0

Updated

Jul 10, 2026

…eeg=62, emg=4 Channel names: AF3, AF4, AF7, AF8, C1, C2…

Participants

54

Channels

62 (10-05)

Citations

99

HED

v8.4.0

Size

121 GB

Version

v1.0.5

Updated

Aug 18, 2026

This dataset contains EEG recordings from 10 healthy, right-handed participants performing simple and compound limb motor imagery tasks, including imagined movements of the left hand, right hand, both hands, feet, and combined hand-foot movements, as well as rest periods. The data were collected using a 60-channel EEG system (plus EOG channels) at Tianjin University to study EEG oscillatory patterns and cognitive processes underlying motor imagery, and have been converted to BIDS format with HED event annotations by the MOABB project.

Participants

10

Channels

60 (10-10)

Citations

94

HED

v8.4.0

Size

5.64 GB

Version

v1.0.2

Updated

Aug 18, 2026

…Stored channels include 128 EEG channels plus audio monitor, EOG, EMG, trigger…

Participants

3

Channels

128 (other)

Citations

3

Size

1.54 TB

Version

v1.0.0

Updated

Aug 18, 2026

BCIComp2020UpperLimb is a preprocessed EEG dataset from BCI Competition 2020 Track 4 containing motor imagery recordings of three grasping tasks (cylindrical, spherical, lumbrical) from 15 healthy subjects across three sessions. The dataset comprises 60-channel EEG data sampled at 250 Hz with 450 trials per subject (150 trials per session across 3 sessions), designed to evaluate session-to-session transfer learning in brain-computer interface applications. Data were preprocessed with 60 Hz notch filtering and cue-aligned epoching, with the 4-second motor imagery window extracted for analysis.

Participants

14

Channels

60 (10-10)

Citations

73

HED

v8.4.0

Size

2.76 GB

Version

v1.0.3

Updated

Aug 18, 2026

…electrodermal activity (*EDA*) and electromyography (*EMG*), were obtained at a sampling frequency…

Participants

45

Channels

139 (other)

Citations

4

Size

202 GB

Version

v1.0.0

Updated

Aug 19, 2026