{"success":true,"database":"eegdash","data":{"_id":"69de6d29897a7725c670234b","dataset_id":"nm000108","associated_paper_doi":null,"authors":["Xinyu Jiang","Chenyun Dai","Xiangyu Liu","Jiahao Fan"],"bids_version":"1.11.0","canonical_name":null,"contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":"10.82901/nemar.nm000108","datatypes":["emg"],"demographics":{"subjects_count":20,"ages":[32,24,22,21,22,22,22,26,30,30,26,27,23,29,32,34,23,27,31,33],"age_min":21,"age_max":34,"age_mean":26.8,"species":null,"sex_distribution":{"m":12,"f":8},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://nemar.org/dataexplorer/detail/nm000108","osf_url":null,"github_url":null,"paper_url":null},"funding":["Shanghai Municipal Science and Technology Major Project (2017SHZDZX01)","Shanghai Pujiang Program (19PJ1401100)","Natural Science Foundation of Shanghai (20ZR1403400)"],"ingestion_fingerprint":"8e4f49dca925f8e81bf9ad0c80cbf2c089bd4bc1f0b70001cd0b3de007d207c9","license":"ODC-By-1.0","n_contributing_labs":null,"name":"HySER: High-Density Surface Electromyogram Recordings","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000108-blue)](https://doi.org/10.82901/nemar.nm000108)\n[![Paper DOI](https://img.shields.io/badge/Paper-10.1109/TNSRE.2021.3082551-blue)](https://doi.org/10.1109/TNSRE.2021.3082551)\n[![PhysioNet](https://img.shields.io/badge/PhysioNet-hd--semg%2F1.0.0-green)](https://physionet.org/content/hd-semg/1.0.0/)\n[![License](https://img.shields.io/badge/License-ODC--By--1.0-lightgrey)](https://opendatacommons.org/licenses/by/1-0/)\n# HySER: High-Density Surface Electromyogram Recordings\nBIDS-formatted version of the Hyser Surface EMG for Hand Gesture Recognition dataset (Jiang et al., 2021). 20 subjects performed 5 task types across 2 sessions using 256-channel high-density surface EMG (HD-sEMG) with simultaneous 5-finger force recordings.\n## Subjects\n20 right-handed participants (12M, 8F; age 21-34). Two sessions per subject separated by 3-25 days. Demographics in `participants.tsv`.\n## Tasks\n| Task | BIDS label | Description | Trials |\n|------|-----------|-------------|--------|\n| Pattern Recognition | `gesture01`-`gesture34` | 34 discrete hand gestures (Table I in paper) | 2 per gesture, each with 3 dynamic + 1 maintenance |\n| Maximum Voluntary Contraction | `mvc` | MVC flexion/extension per finger | 2 per finger, 10s each |\n| Single Finger (1-DOF) | `singlefinger` | Triangle force trajectory, individual fingers | 3 per finger, 25s each |\n| Multi-Finger (N-DOF) | `multifinger` | Simultaneous multi-finger force tracking | 2 per combination, 25s each |\n| Random | `random` | Free finger contractions at any force | 5 trials, 25s each |\n## Equipment\n- **EMG system:** Quattrocento (OT Bioelettronica, Torino, Italy), 2048 Hz, gain 150, 16-bit ADC\n- **Electrodes:** Four 8x8 gelled elliptical arrays (5mm x 2.8mm), 10mm inter-electrode distance\n- **Placement:** Two arrays on extensors (distal/proximal), two on flexors (distal/proximal) of right forearm\n- **Reference:** Olecranon (elbow); Ground: head of ulna (right leg drive)\n- **Hardware filters:** HP 10 Hz (2nd order), LP 500 Hz\n- **Force sensors:** SAS + HSGA (Huatran, Shenzhen, China), 100 Hz, 5 fingers\n## File Organization\n- `*_emg.bdf` - 256-channel EMG data (BDF format)\n- `*_physio.tsv.gz` - 5-finger force data (non-PR tasks only)\n- `*_channels.tsv` - Channel metadata with electrode mapping (`signal_electrode` column)\n- `*_electrodes.tsv` - Electrode positions in local grid coordinates (mm)\n- `*_events.tsv` - Event markers (gesture trials or segment boundaries)\nNon-PR tasks (MVC, singlefinger, multifinger, random) are merged from multiple original recordings into single files per session, with boundary events marking segment junctions.\n## Coordinate Systems\nFour local grid systems (`space-ed`, `space-ep`, `space-fd`, `space-fp`) in mm, anchored to a parent forearm system (`space-forearm`) in anatomical percent coordinates. See `space-*_coordsystem.json` files.\n## Missing Data\n6 gesture recordings absent in source dataset (not conversion failures):\nsub-01/ses-2/gesture25, sub-03/ses-1/gesture04, sub-03/ses-2/gesture04, sub-05/ses-1/gesture34, sub-11/ses-1/gesture08, sub-19/ses-2/gesture11.\n## Conversion\nConverted using EMG-2-BIDS (EEGLAB + bids-matlab-tools). Data integrity verified: mean Pearson correlation >0.9999 between original WFDB and converted BDF across all 1514 recordings. See `dataset_description.json` for generator details.","recording_modality":["emg"],"senior_author":null,"sessions":["1","2"],"size_bytes":116163636943,"source":"nemar","storage":{"backend":"nemar","base":"s3://nemar/nm000108","raw_key":"dataset_description.json","dep_keys":["README.md","participants.json","participants.tsv","space-ed_coordsystem.json","space-ep_coordsystem.json","space-fd_coordsystem.json","space-forearm_coordsystem.json","space-fp_coordsystem.json","task-gesture01_emg.json","task-gesture01_events.json","task-gesture02_emg.json","task-gesture02_events.json","task-gesture03_emg.json","task-gesture03_events.json","task-gesture04_emg.json","task-gesture04_events.json","task-gesture05_emg.json","task-gesture05_events.json","task-gesture06_emg.json","task-gesture06_events.json","task-gesture07_emg.json","task-gesture07_events.json","task-gesture08_emg.json","task-gesture08_events.json","task-gesture09_emg.json","task-gesture09_events.json","task-gesture10_emg.json","task-gesture10_events.json","task-gesture11_emg.json","task-gesture11_events.json","task-gesture12_emg.json","task-gesture12_events.json","task-gesture13_emg.json","task-gesture13_events.json","task-gesture14_emg.json","task-gesture14_events.json","task-gesture15_emg.json","task-gesture15_events.json","task-gesture16_emg.json","task-gesture16_events.json","task-gesture17_emg.json","task-gesture17_events.json","task-gesture18_emg.json","task-gesture18_events.json","task-gesture19_emg.json","task-gesture19_events.json","task-gesture20_emg.json","task-gesture20_events.json","task-gesture21_emg.json","task-gesture21_events.json","task-gesture22_emg.json","task-gesture22_events.json","task-gesture23_emg.json","task-gesture23_events.json","task-gesture24_emg.json","task-gesture24_events.json","task-gesture25_emg.json","task-gesture25_events.json","task-gesture26_emg.json","task-gesture26_events.json","task-gesture27_emg.json","task-gesture27_events.json","task-gesture28_emg.json","task-gesture28_events.json","task-gesture29_emg.json","task-gesture29_events.json","task-gesture30_emg.json","task-gesture30_events.json","task-gesture31_emg.json","task-gesture31_events.json","task-gesture32_emg.json","task-gesture32_events.json","task-gesture33_emg.json","task-gesture33_events.json","task-gesture34_emg.json","task-gesture34_events.json","task-multifinger_emg.json","task-multifinger_events.json","task-mvc_emg.json","task-mvc_events.json","task-random_emg.json","task-random_events.json","task-singlefinger_emg.json","task-singlefinger_events.json"]},"study_design":null,"study_domain":null,"tasks":["gesture01","gesture02","gesture03","gesture04","gesture05","gesture06","gesture07","gesture08","gesture09","gesture10","gesture11","gesture12","gesture13","gesture14","gesture15","gesture16","gesture17","gesture18","gesture19","gesture20","gesture21","gesture22","gesture23","gesture24","gesture25","gesture26","gesture27","gesture28","gesture29","gesture30","gesture31","gesture32","gesture33","gesture34","multifinger","mvc","random","singlefinger"],"timestamps":{"digested_at":"2026-04-30T14:08:26.871570+00:00","dataset_created_at":null,"dataset_modified_at":"2026-02-19T04:47:24Z"},"total_files":1514,"author_year":"Jiang2021","name_source":"canonical","nchans_counts":[{"val":256,"count":1514}],"computed_title":"HySER: High-Density Surface Electromyogram Recordings","sfreq_counts":[],"stats_computed_at":"2026-05-01T13:49:34.660194+00:00","total_duration_s":null}}