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ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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EMG from forearm datasets for hand gestures recognition

Authors: Donati, Elisa;

EMG from forearm datasets for hand gestures recognition

Abstract

This dataset contains 2 sets of sEMG recordings: a set containing PINCH movements (4 pinches between thumb and index/middle/ring/pinky finger) and a set containing ROSHAMBO movements (3 movements: rock, paper, scissors). Both sets have been recorded with the Myo armband. The Myo 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.. The PINCH set contains recordings of 22 subjects whilst the ROSHAMBO set contains recordings of 10 subjects. Each subject performed 3 sessions, where each 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. Full details for the ROSHAMBO set can be found in: Donati, Elisa, et al. "Processing EMG signals using reservoir computing on an event-based neuromorphic system." 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE, 2018. For each session, the dataset contains 2 *.npy files one specifying the EMG data (*_emg.npy) the other one (*_ann.npy) specifying the corresponding gestures along the sampled EMG. The data can be easily loaded in python with numpy.

Related Organizations
Keywords

Myo armband, EMG, Hand gestures recognition

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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visibility
download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
4
Average
Average
Average
1K
351
Funded by
EC| NEPSpiNN
Project
NEPSpiNN
Neuromorphic EMG Processing with Spiking Neural Networks
  • Funder: European Commission (EC)
  • Project Code: 753470
  • Funding stream: H2020 | MSCA-IF-EF-ST
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