Discover datasets

A BIDS-formatted dataset of high-density surface EMG (HDsEMG) recordings from the right tibialis anterior of six healthy male participants. Four 64-channel grids (256 electrodes) recorded trapezoidal isometric dorsiflexion contractions at 30% and 50% of maximal voluntary contraction, together with force signals. The dataset supports studies of electrode grid design and motor unit identification.

Participants

6

Size

448 MB

Version

v1.0.1

Updated

Jun 1, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004541-blue…

Participants

8

Channels

58 (10-10)

Size

2.90 GB

Version

v1.0.0

Updated

Jun 24, 2026

High-density surface EMG (HDsEMG) recordings from the right tibialis anterior of a single healthy participant performing submaximal isometric ankle dorsiflexions at 10 to 70 percent of maximal voluntary contraction. Signals were acquired with two 64-electrode arrays (128 electrodes total) alongside force measurements. The dataset includes labeled motor unit spike trains derived from concurrent invasive EMG, and supports motor unit decomposition research.

Participants

1

Size

1.34 GB

Version

v1.0.1

Updated

Jun 1, 2026

Intracranial EEG (iEEG) recordings from 8 patients undergoing single pulse electrical stimulation while resting in a hospital bed. The dataset supports investigation of stimulation-driven network interactions in the human limbic system. Data are organized in BIDS with metadata for event timing.

Participants

8

Citations

18

Size

19.5 GB

Version

v1.0.0

Updated

Jun 25, 2026

A BIDS-formatted release of the Hyser high-density surface electromyogram (HD-sEMG) dataset. It contains 256-channel forearm EMG with simultaneous five-finger force recordings from 20 right-handed participants across two sessions. Tasks include 34 hand gestures, maximum voluntary contraction, and single-finger, multi-finger and random force-tracking tasks, supporting gesture recognition and force decoding research.

Participants

20

Size

108 GB

Version

v1.0.1

Updated

Feb 20, 2026

A 64-channel EEG dataset from 12 healthy participants using a broad-band visually evoked potential (BBVEP) brain-computer interface with modulated Gold codes. Participants operated a 6x6 matrix speller in an online copy-spelling task, with each cell flashing according to pseudo-random bit-sequences. The dataset supports research on code-modulated VEP (c-VEP) BCIs and reconvolution-based template prediction. It is a preprocessed derivative distributed via MOABB.

Participants

12

Channels

64 (10-10)

Citations

74

HED

v8.4.0

Size

11.0 GB

Version

v1.0.4

Updated

Oct 8, 2026

A code-modulated visual evoked potential (c-VEP) brain-computer interface dataset recorded from 30 healthy participants using 8 EEG electrodes at 512 Hz. Participants fixated on target cells in a 20-symbol grid while all cells flashed pseudo-random modulated Gold codes. The data support comparison of full-calibration, reduced-training and zero-training classification using a reconvolution encoding model.

Participants

30

Channels

8 (10-10)

Citations

66

HED

v8.4.0

Size

3.16 GB

Version

v1.0.5

Updated

Oct 8, 2026