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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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 . 2021
License: CC BY
Data sources: ZENODO
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Effects of Perturbation Velocity, Direction, Background muscle activation, and Task Instruction on Long-Latency Responses Measured from Forearm Muscles

Authors: Weinman, Jacob; Arfa-Fatollahkhani, Paria; Zonnino, Andrea; Nikonowicz, Rebecca C; Sergi, Fabrizio;

Effects of Perturbation Velocity, Direction, Background muscle activation, and Task Instruction on Long-Latency Responses Measured from Forearm Muscles

Abstract

Dataset associated with the original research article published in "Frontiers in Human Neuroscience", by Weinman et al., doi: 10.3389/fnhum.2021.639773 The data is stored in a MATLAB file named EMG.mat. The workspace file contains the following variables: ECU FCR ECULLR FCRLLR time Variable description: ECU and FCR: A 5-dimensional cell array with normalized EMG tracks measured during perturbations. Each combination of condition was repeated 10 times, for each subject, so accessing a specific cell in this variable will provide a 10x2049 array of EMG data, with each row corresponding to one of the 10 repetitions. ECULLR and FCRLLR: A 5-dimensional cell array with LLR amplitude (average of the processed EMG signal during the time window corresponding to a long-latency response: 50 to 100 ms), also measured 10 times for each combination of conditions. Accessing a cell in this data will provide a 10x1 array of average EMG values, with each row corresponding to the average LLR for one of the 10 repetitions. Each of the variables listed above has 5 dimensions, each dimension corresponding to one factor. As an example, the dimensions of variable ECU are ECU{sub,v,d,t,inst}, defined as follows: sub = subject number (1 thru 11). Subject 10 has blank cells in the FCR dataset, due to data corruption from noise. v = velocity (1, 2, 3). 1=50 deg/s, 2=125 deg/s, 3=200 deg/s d = direction (1 or 2). 1=shorten, 2=stretch t = torque (1 or 2). 1=0 mNm, 2=200 mNm inst = instruction (1 or 2), 1=“yield”, 2=“do not intervene” As such, the variable EMG.ECU{1,1,1,1,1} is a 10x2049 variable including 10 repetitions of the timeseries of ECU EMG signal measured from subject 1, for perturbations at 50 deg/s, shortening the ECU (extension perturbations), with 0 mNm background torque, when the instruction was “yield”. time: A 1x2049 array of time values corresponding to the EMG readings in milliseconds. Values in this array are from 0 ms to 200 ms. The time series have 2049 datapoints (sampling frequency: 1024 Hz) representing up to the 200 ms from the perturbation onset. LLR averages were taken from the indexes representing 50 to 100 ms, or 513:1024.

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Keywords

stretch reflex, long latency responses, motor neurophysiology, electromyography, robotics

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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.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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