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Dataset Open Access

EMG and Video Dataset for sensor fusion based hand gestures recognition

Ceolini, Enea; Taverni, Gemma; Payvand, Melika; Donati, Elisa

This dataset contains data for hand gestures 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 10 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: We did not upload the raw data (*.aedat) for the DAVIS being those files very heavy. All the information for the sensor has been extracted and can be found in the two files *.npz and *.mat. In case the raw data was needed please contact

  • enea.ceolini@ini.uzh.ch
  • elisa@ini.uzh.ch

==== README ====

DATASET STRUCTURE:
EMG and DVS recordings
10 subjects
3 sessions for each subject
5 gestures in each session ('pinky', 'elle', 'yo', 'index', 'thumb')

Data name:
subjectXX_sessionYY_ZZZ
XX : [01, 02, 03, 04, 05, 06, 07, 08, 09, 10] 
YY : [01, 02, 03]
ZZZ : [emg, ann, dvs, davis]

Data format:
emg: .npy
ann: .npy
dvs: .aedat,.npy
davis: .mat,.npz

DVS
DVS recordings only contain DVS events
- .aedat (raw data): can be imported in Matlab using (https://github.com/inivation/AedatTools/tree/master/Matlab) or in Python with function aedat2numpy in converter.py (https://github.com/Enny1991/hand_gestures_cc19/tree/master/jAER_utils)
- .npy (exported data): numpy.ndarray (xpos, ypos, ts, pol), 2D numpy array containing data of all events, timestamps ts reset to the trigger event (synchronized with the myo), timestamps ts in seconds

 
DAVIS
DAVIS recordings contain DVS events and APS frames.
- .mat (exported data): mat structure, name 'aedat', events are inside aedat.data.polarity (aedat.data.polarity.x,aedat.data.polarity.y,aedat.data.polarity.timeStamp,aedat.data.polarity.polarity), aps frames are inside aedat.data.frame.samples, timestamps are in aedat.data.frame.timeStampStart (start of frame collection) or aedat.data.frame.timeStampEnd (end of frame collection)
- .npz (exported data): npz files: ['frames_time', 'dvs_events', 'frames'], 'dvs_events' is a numpy.ndarray (xpos, ypos, ts, pol), 2D numpy array containing data of all events, timestamps ts reset to the trigger event (synchronized with the myo), timestamps ts in seconds; 'frames' and 'frames_time' are aps data, 'frames' is a list of all the frames, reset at the triggered time, 'frames_time' is the time for each frame, we considered the start timeStamps for each frame.


 

 

 

Files (31.9 GB)
Name Size
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subject01_session01_davis.mat
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subject01_session01_davis.npz
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subject01_session01_dvs.aedat
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subject01_session01_dvs.npy
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subject01_session01_emg.npy
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subject01_session02_ann.npy
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subject01_session02_davis.mat
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subject01_session02_davis.npz
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subject01_session02_dvs.npy
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subject01_session03_ann.npy
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subject01_session03_davis.npz
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subject01_session03_dvs.npy
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subject02_session01_ann.npy
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subject02_session01_davis.npz
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subject02_session03_davis.npz
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subject04_session02_dvs.npy
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subject04_session03_davis.npz
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subject09_session03_dvs.npy
md5:ff9b41078afbf7f19b7091e2a7b6f108
78.7 MB Download
subject09_session03_emg.npy
md5:5e84527a71c35f4ed93b08a2577eceda
805.5 kB Download
subject10_session01_ann.npy
md5:25a37147ba135422490a96c67f2f3c3b
506.9 kB Download
subject10_session01_davis.mat
md5:4ffa7eae007bd7dd77176ac9bbccf8ff
134.2 MB Download
subject10_session01_davis.npz
md5:0557e1415cdf16b81ae63eb22e8e20cb
602.4 MB Download
subject10_session01_dvs.aedat
md5:98a10ff19fe21701467c0cfecbc053d1
14.7 MB Download
subject10_session01_dvs.npy
md5:b79770ad0e21931fc68b0ba7f6f1500b
55.9 MB Download
subject10_session01_emg.npy
md5:2ead7e33c4355e4975430ab0ac175f5e
811.0 kB Download
subject10_session02_ann.npy
md5:b77306f2bd5fdd6fc1a9e9cb3ed3f4ea
506.5 kB Download
subject10_session02_davis.mat
md5:4ad4d3c2975468cb6bd5cb4a541a16d5
133.8 MB Download
subject10_session02_davis.npz
md5:9f01bd8c918e1dde12cfae9fe0f4da81
596.1 MB Download
subject10_session02_dvs.aedat
md5:e8a460aec91c8ae32d4fde9695dd9f5f
15.8 MB Download
subject10_session02_dvs.npy
md5:d0cb00275f0d16e844c9fb6af7685018
57.0 MB Download
subject10_session02_emg.npy
md5:90517b3013d8410e2461b7bcea4c0ece
810.3 kB Download
subject10_session03_ann.npy
md5:5d82018828a802df886e2bf0a2862f6d
506.6 kB Download
subject10_session03_davis.mat
md5:d0b8fc7aca971bce7101faca94215e2a
135.8 MB Download
subject10_session03_davis.npz
md5:b56b518a8614183dcd3dbd136cc0d899
613.9 MB Download
subject10_session03_dvs.aedat
md5:1d60d6697059a79d12d78afa22a37657
15.4 MB Download
subject10_session03_dvs.npy
md5:c768552e8aa5731f1b4eef99556a77a5
58.2 MB Download
subject10_session03_emg.npy
md5:4c18646b291bf8e835f8e4cd53831a1f
810.5 kB Download
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