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Probability Density Function of EMG Signals based on Hand Movements in Time and Frequency Domain

by Ramanpreet Kaur, Payal Patial
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 3
Year of Publication: 2015
Authors: Ramanpreet Kaur, Payal Patial
10.5120/21518-4494

Ramanpreet Kaur, Payal Patial . Probability Density Function of EMG Signals based on Hand Movements in Time and Frequency Domain. International Journal of Computer Applications. 121, 3 ( July 2015), 6-12. DOI=10.5120/21518-4494

@article{ 10.5120/21518-4494,
author = { Ramanpreet Kaur, Payal Patial },
title = { Probability Density Function of EMG Signals based on Hand Movements in Time and Frequency Domain },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 3 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 6-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume121/number3/21518-4494/ },
doi = { 10.5120/21518-4494 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:07:27.994238+05:30
%A Ramanpreet Kaur
%A Payal Patial
%T Probability Density Function of EMG Signals based on Hand Movements in Time and Frequency Domain
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 3
%P 6-12
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper attempts to estimate the probability density function of hand movements by using EMG signals. Several hand grasps generated from different hand movements, we have analyzed Tip and Lateral. Four well known pdf functions for good fitness of test are Log Logistics (3P), Johnson, Dagum (4P) and Burr (4P), that have been tested. The probability density function has been carried out in time domain and FFT domain as well as in DWT domain. It was observed that there are different distributions for different hand movements, which describe the samples most accurately with the movements of hand with respect to two channels; channel 1 and channel 2. In this scenario, channels 1 is placed on upper limb and channel 2 placed on lower limbs as a reference channel. Although, Burr distribution and Log logistic distribution along with that Dagum has been a good fit for most of the data, it is shown in this paper that Non Negative distribution (Dagum (4P) and Burr (4P) distribution) is a better choice for estimating the Tip and Lateral hand movements.

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Index Terms

Computer Science
Information Sciences

Keywords

EMG signals hand movements' data probability density function and FFT DWT (Non- Negative distribution) Dagum or Burr distribution.

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