Dataset Open Access
Ceolini, Enea;
Taverni, Gemma;
Payvand, Melika;
Donati, Elisa
<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Ceolini, Enea</dc:creator> <dc:creator>Taverni, Gemma</dc:creator> <dc:creator>Payvand, Melika</dc:creator> <dc:creator>Donati, Elisa</dc:creator> <dc:date>2020-02-12</dc:date> <dc:description>This dataset contains data for hand gesture recognition recorded with 3 different sensors. 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 DVS: Dynamic Video Sensor which is a very low power event-based camera with 128x128 resolution DAVIS: Dynamic Video Sensor which is a very low power event-based camera with 240x180 resolution that also acquires APS frames. 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. 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 enea.ceolini@ini.uzh.ch elisa@ini.uzh.ch ==== README ==== DATASET STRUCTURE: EMG, DVS and APS recordings 21 subjects 3 sessions for each subject 5 gestures in each session ('pinky', 'elle', 'yo', 'index', 'thumb') SINGLE DATASETS: - 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’. - 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). - 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. - 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: - y: array of size 1xN with the class (0->4). - sub: array of size 1xN with the subject id (1->10). - sess: array of size 1xN with the session id (1->3). - dvs: 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 . - emg: 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. </dc:description> <dc:identifier>https://zenodo.org/record/3663616</dc:identifier> <dc:identifier>10.5281/zenodo.3663616</dc:identifier> <dc:identifier>oai:zenodo.org:3663616</dc:identifier> <dc:relation>info:eu-repo/grantAgreement/EC/H2020/753470/</dc:relation> <dc:relation>doi:10.5281/zenodo.3228845</dc:relation> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights> <dc:subject>EMG</dc:subject> <dc:subject>DVS</dc:subject> <dc:subject>DAVIS</dc:subject> <dc:subject>Hand gesture recognition</dc:subject> <dc:subject>Sensor fusion</dc:subject> <dc:subject>Myo</dc:subject> <dc:title>EMG and Video Dataset for sensor fusion based hand gestures recognition</dc:title> <dc:type>info:eu-repo/semantics/other</dc:type> <dc:type>dataset</dc:type> </oai_dc:dc>
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