Dataset Open Access
EMG and Video Dataset for sensor fusion based hand gestures recognition
Ceolini, Enea;
Taverni, Gemma;
Payvand, Melika;
Donati, Elisa
JSON Export
{
"files": [
{
"links": {
"self": "https://zenodo.org/api/files/102a63cc-433e-49b4-be9f-3ee2f482b38e/relax21_cropped_aps.zip"
},
"checksum": "md5:0aca5c68eb7cecffcd9f2e3a53cb9124",
"bucket": "102a63cc-433e-49b4-be9f-3ee2f482b38e",
"key": "relax21_cropped_aps.zip",
"type": "zip",
"size": 186878096
},
{
"links": {
"self": "https://zenodo.org/api/files/102a63cc-433e-49b4-be9f-3ee2f482b38e/relax21_cropped_dvs_emg_spikes.pkl"
},
"checksum": "md5:8bda33fec74cb4f49a05c6a89eef7163",
"bucket": "102a63cc-433e-49b4-be9f-3ee2f482b38e",
"key": "relax21_cropped_dvs_emg_spikes.pkl",
"type": "pkl",
"size": 2049159861
},
{
"links": {
"self": "https://zenodo.org/api/files/102a63cc-433e-49b4-be9f-3ee2f482b38e/relax21_raw_dvs.zip"
},
"checksum": "md5:e767b6b586c8f6919f945d770fbac529",
"bucket": "102a63cc-433e-49b4-be9f-3ee2f482b38e",
"key": "relax21_raw_dvs.zip",
"type": "zip",
"size": 1592923718
},
{
"links": {
"self": "https://zenodo.org/api/files/102a63cc-433e-49b4-be9f-3ee2f482b38e/relax21_raw_emg.zip"
},
"checksum": "md5:9fab8c87e8f04a56c3fdcb1797644885",
"bucket": "102a63cc-433e-49b4-be9f-3ee2f482b38e",
"key": "relax21_raw_emg.zip",
"type": "zip",
"size": 12711873
}
],
"owners": [
68055
],
"doi": "10.5281/zenodo.3663616",
"stats": {
"version_unique_downloads": 1927.0,
"unique_views": 925.0,
"views": 1065.0,
"version_views": 1979.0,
"unique_downloads": 217.0,
"version_unique_views": 1647.0,
"volume": 449910815210.0,
"version_downloads": 6094.0,
"downloads": 451.0,
"version_volume": 1004042118084.0
},
"links": {
"doi": "https://doi.org/10.5281/zenodo.3663616",
"conceptdoi": "https://doi.org/10.5281/zenodo.3228845",
"bucket": "https://zenodo.org/api/files/102a63cc-433e-49b4-be9f-3ee2f482b38e",
"conceptbadge": "https://zenodo.org/badge/doi/10.5281/zenodo.3228845.svg",
"html": "https://zenodo.org/record/3663616",
"latest_html": "https://zenodo.org/record/3663616",
"badge": "https://zenodo.org/badge/doi/10.5281/zenodo.3663616.svg",
"latest": "https://zenodo.org/api/records/3663616"
},
"conceptdoi": "10.5281/zenodo.3228845",
"created": "2020-02-12T10:15:46.808491+00:00",
"updated": "2020-02-12T19:21:06.424946+00:00",
"conceptrecid": "3228845",
"revision": 2,
"id": 3663616,
"metadata": {
"access_right_category": "success",
"doi": "10.5281/zenodo.3663616",
"version": "3.0",
"license": {
"id": "CC-BY-4.0"
},
"title": "EMG and Video Dataset for sensor fusion based hand gestures recognition",
"related_identifiers": [
{
"scheme": "doi",
"identifier": "10.5281/zenodo.3228845",
"relation": "isVersionOf"
}
],
"relations": {
"version": [
{
"count": 3,
"index": 2,
"parent": {
"pid_type": "recid",
"pid_value": "3228845"
},
"is_last": true,
"last_child": {
"pid_type": "recid",
"pid_value": "3663616"
}
}
]
},
"grants": [
{
"code": "753470",
"links": {
"self": "https://zenodo.org/api/grants/10.13039/501100000780::753470"
},
"title": "Neuromorphic EMG Processing with Spiking Neural Networks",
"acronym": "NEPSpiNN",
"program": "H2020",
"funder": {
"doi": "10.13039/501100000780",
"acronyms": [],
"name": "European Commission",
"links": {
"self": "https://zenodo.org/api/funders/10.13039/501100000780"
}
}
}
],
"keywords": [
"EMG",
"DVS",
"DAVIS",
"Hand gesture recognition",
"Sensor fusion",
"Myo"
],
"publication_date": "2020-02-12",
"creators": [
{
"orcid": "0000-0002-2676-0804",
"affiliation": "Institute of Neuroinformatics, UZH/ETH Zurich",
"name": "Ceolini, Enea"
},
{
"orcid": "0000-0001-8951-3133",
"affiliation": "Institute of Neuroinformatics, UZH/ETH Zurich",
"name": "Taverni, Gemma"
},
{
"orcid": "0000-0001-5400-067X",
"affiliation": "Institute of Neuroinformatics, UZH/ETH Zurich",
"name": "Payvand, Melika"
},
{
"orcid": "0000-0002-8091-1298",
"affiliation": "Institute of Neuroinformatics, UZH/ETH Zurich",
"name": "Donati, Elisa"
}
],
"access_right": "open",
"resource_type": {
"type": "dataset",
"title": "Dataset"
},
"description": "<p>This dataset contains data for hand gesture recognition recorded with 3 different sensors. </p>\n\n<p>sEMG: recorded via the Myo armband that is composed of 8 equally spaced non-invasive sEMG sensors that can be placed approximately around the middle of the forearm. The sampling frequency of Myo is 200 Hz. The output of the Myo is a.u </p>\n\n<p>DVS: Dynamic Video Sensor which is a very low power event-based camera with 128x128 resolution</p>\n\n<p>DAVIS: Dynamic Video Sensor which is a very low power event-based camera with 240x180 resolution that also acquires APS frames.</p>\n\n<p>The dataset contains recordings of 21 subjects. Each subject performed 3 sessions, where each of the 5 hand gesture was recorded 5 times, each lasting for 2s. Between the gestures a relaxing phase of 1s is present where the muscles could go to the rest position, removing any residual muscular activation.</p>\n\n<p> </p>\n\n<p>Note: All the information for the DVS sensor has been extracted and can be found in the *.npy files. In case the raw data (.aedat) was needed please contact</p>\n\n<p> </p>\n\n<p>enea.ceolini@ini.uzh.ch</p>\n\n<p>elisa@ini.uzh.ch</p>\n\n<p>==== README ====</p>\n\n<p> </p>\n\n<p>DATASET STRUCTURE:</p>\n\n<p>EMG, DVS and APS recordings</p>\n\n<p>21 subjects</p>\n\n<p>3 sessions for each subject</p>\n\n<p>5 gestures in each session ('pinky', 'elle', 'yo', 'index', 'thumb')</p>\n\n<p> </p>\n\n<p>SINGLE DATASETS:</p>\n\n<p>- relax21_raw_emg.zip: contains raw sEMG and annotations (ground truth of gestures) in the format `subjectXX_sessionYY_ZZZ` with `XX` subject ID (01 to 21), `YY` session ID (01-03) and `ZZZ` that can be ‘emg’ or ‘ann’.</p>\n\n<p> </p>\n\n<p>- relax21_raw_dvs.zip: contains the full-frame dvs events in an array with dimensions 0 -> addr_x, 1 -> addr_y, 2 -> timestamp, 3 -> polarity. The timestamps are in seconds and synchronized with the Myo. Each file is in the format `subjectXX_sessionYY_dvs` with `XX` subject ID (01 to 21), `YY` session ID (01-03).</p>\n\n<p> </p>\n\n<p>- relax21_cropped_aps.zip: contains the 40x40 pixel aps frames for all subjects and trials in the format `subjectXX_sessionYY_Z_W_K` with `XX` subject ID (01 to 21), `YY` session ID (01-03), Z gesture ('pinky', 'elle', 'yo', 'index', 'thumb’), W trial ID (1-5), `K` frame index.</p>\n\n<p> </p>\n\n<p>- relax21_cropped_dvs_emg_spikes.pkl: spiking dataset that can be used to reproduce the results in the paper. The dataset is a dictionary with the following keys:</p>\n\n<ul>\n\t<li><strong>- </strong><strong>y</strong>: array of size 1xN with the class (0->4).</li>\n\t<li><strong>- </strong><strong>sub</strong>: array of size 1xN with the subject id (1->10).</li>\n\t<li><strong>- </strong><strong>sess</strong>: array of size 1xN with the session id (1->3).</li>\n\t<li><strong>- </strong><strong>dvs</strong>: list of length N, each object in the list is a 2d array of size 4xT_n where T_n is the number of events in the trial and the 4 dimensions rappresent: 0 -> addr_x, 1 -> addr_y, 2 -> timestamp, 3 -> polarity .</li>\n\t<li><strong>- </strong><strong>emg</strong>: list of length N, each object in the list is a 2d array of size 3xT_n where T_n is the number of events in the trial and the 3 dimensions rappresent: 0 -> addr, 1 -> timestamp, 3 -> polarity.</li>\n</ul>\n\n<p> </p>\n\n<p> </p>"
}
}
1,979
6,094
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 1,979 | 1,065 |
| Downloads | 6,094 | 451 |
| Data volume | 1.0 TB | 449.9 GB |
| Unique views | 1,647 | 925 |
| Unique downloads | 1,927 | 217 |
Indexed in
- Publication date:
- February 12, 2020
- DOI:
-
- Keyword(s):
- EMG DVS DAVIS Hand gesture recognition Sensor fusion Myo
- Grants:
-
European Commission:
- NEPSpiNN - Neuromorphic EMG Processing with Spiking Neural Networks (753470)
- License (for files):
- Creative Commons Attribution 4.0 International