Electromyographic signals (EMG) may be used to analyze the muscular strain during work. The Amplitude Probability Distribution Function (APDF) provides a statistical quantitative measure of muscle activity for a period of time. The established recording time to properly estimate this distribution function is one hour of recording. This paper
presents a systematic analysis, based on real EMG data, of the period of time necessary to estimate the profile of the muscular load during the period of work using the APDF function. It is shown that it is possible to estimate this function based on a reduced period of time quantifying the uncertainty of the estimate.
%0 Conference Paper
%1 ConfTele2007
%A Lourenco, Andre
%A Fred, Ana
%A Veloso, Antonio
%A Carnide, Filomena
%B ConfTele 2007 (6th Conference on Telecomunications)
%C Peniche, Portugal
%D 2007
%K APDF Amplitude_Probability_Distribution_Function Electromyographic_signals muscular_profile
%T Optimization of Observation Time for Obtaining the Profile of Muscular Load using the APDF Function
%X Electromyographic signals (EMG) may be used to analyze the muscular strain during work. The Amplitude Probability Distribution Function (APDF) provides a statistical quantitative measure of muscle activity for a period of time. The established recording time to properly estimate this distribution function is one hour of recording. This paper
presents a systematic analysis, based on real EMG data, of the period of time necessary to estimate the profile of the muscular load during the period of work using the APDF function. It is shown that it is possible to estimate this function based on a reduced period of time quantifying the uncertainty of the estimate.
@inproceedings{ConfTele2007,
abstract = {Electromyographic signals (EMG) may be used to analyze the muscular strain during work. The Amplitude Probability Distribution Function (APDF) provides a statistical quantitative measure of muscle activity for a period of time. The established recording time to properly estimate this distribution function is one hour of recording. This paper
presents a systematic analysis, based on real EMG data, of the period of time necessary to estimate the profile of the muscular load during the period of work using the APDF function. It is shown that it is possible to estimate this function based on a reduced period of time quantifying the uncertainty of the estimate.},
added-at = {2009-10-25T21:26:17.000+0100},
address = {Peniche, Portugal},
author = {Lourenco, Andre and Fred, Ana and Veloso, Antonio and Carnide, Filomena},
biburl = {https://www.bibsonomy.org/bibtex/2aa1474418f94e6391ed5ef5fb7ce4b67/alourenco},
booktitle = {ConfTele 2007 (6th Conference on Telecomunications)},
interhash = {6170684987bda98cdb70bfc78db0c23d},
intrahash = {aa1474418f94e6391ed5ef5fb7ce4b67},
keywords = {APDF Amplitude_Probability_Distribution_Function Electromyographic_signals muscular_profile},
month = May,
timestamp = {2009-10-25T21:26:17.000+0100},
title = {Optimization of Observation Time for Obtaining the Profile of Muscular Load using the APDF Function},
year = 2007
}