Deception_data
…RSP*), electrodermal activity (*EDA*) and electromyography (*EMG*), were obtained at a sampling…
- Participants
- 45
- Channels
- 139 (other)
- Citations
- 4
- Size
- 202 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
77 results for "electromyography" · page 3 of 8 · ranked by relevance
…RSP*), electrodermal activity (*EDA*) and electromyography (*EMG*), were obtained at a sampling…
Imported from OpenNeuro ds004022
This dataset comprises EEG recordings from 12 healthy participants performing upper-limb motor imagery tasks centered on elbow movements. Participants executed kinesthetic imagery of nine goal-directed tasks (drawer opening, soup preparation, weight lifting, door opening, plate cleaning, combing, pizza cutting, and pick-and-place operations) plus rest, cued by visual stimuli. The dataset contains 330 trials recorded at 1000 Hz using 17 EEG channels and is designed for brain-computer interface (BCI) research and motor imagery classification studies.
…the left mastoid. - **PSG_EMG**: Electromyography signals recorded with the PSG system…
This dataset comprises synchronized electroencephalogram (EEG), electrocardiogram (ECG), and pupillography recordings from 75 participants (36 young and 39 older adults) during auditory cued reaction time tasks and passive listening conditions. Participants performed a simple reaction time task and a go/no-go task, with EEG acquired at 500 Hz using 64 scalp electrodes, ECG recorded bipolarly from chest electrodes, and pupil data sampled at 240 Hz. The dataset is designed to investigate age-related differences in neural, cardiac, and pupillary responses during cognitive and perceptual decision-making tasks.
This dataset comprises intraoperative intracranial EEG recordings from 10 patients undergoing brain tumor resection in the perirolandic region. Median nerve somatosensory evoked potentials (SEP) were recorded simultaneously using two 4-contact ECoG electrode strips with different impedance characteristics (low impedance: 3.4 kΩ and high impedance: 6.9 kΩ) to investigate the efficacy of low-impedance electrodes for detecting high-frequency oscillations in clinical neurophysiology.
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.
This dataset comprises electrophysiological recordings (EEG, ECG, EMG) collected from 9 adult burn patients in an intensive care unit during Music-Assisted Relaxation therapy sessions. As part of a randomized clinical trial (NCT04571255), participants underwent two recording sessions with pre-intervention baseline, intervention, and post-intervention phases. The study investigates the physiological effects of music therapy on pain perception and anxiety-depression levels in critically ill burn patients using clinical-grade equipment with standardized electrode montages.
EmoEEG-MC is a multi-context emotional EEG dataset comprising 64-channel EEG and peripheral physiological recordings (PPG, GSR) from 60 participants exposed to video-induced and imagery-induced emotional stimuli. Seven emotion categories (joy, inspiration, tenderness, fear, disgust, sadness, neutral) were evoked and validated through subjective reports, enabling investigation of cross-context emotion decoding. The dataset supports research on neural mechanisms of emotion and generalization of affective computing models across contexts.
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).