Locomotion classification using emg signal - A comparative study

Sarthak Pati; Deepak Joshi; Ashutosh Mishra

doi:10.1109/ICIET.2010.5625677

Locomotion classification using emg signal - A comparative study

Sarthak Pati, Deepak Joshi, Ashutosh Mishra

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Citations (Scopus)

Abstract

This work gives a comparative study on the use of Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN) and Naive-Bayes Classifier (NBC) for recognizing various locomotion modes using parameters derived from the transient EMG signals taken from healthy subjects and thus provide a better control mechanism for lower limb prosthesis. These classifiers have been taken into consideration owing to their extensive use in various realtion, time applications.

Original language	English
Title of host publication	2010 International Conference on Information and Emerging Technologies, ICIET 2010
DOIs	https://doi.org/10.1109/ICIET.2010.5625677
Publication status	Published - 30-12-2010
Externally published	Yes
Event	2nd International Conference on Information and Emerging Technologies, ICIET 2010 - Karachi, Pakistan Duration: 14-06-2010 → 16-06-2010

Conference

Conference	2nd International Conference on Information and Emerging Technologies, ICIET 2010
Country/Territory	Pakistan
City	Karachi
Period	14-06-10 → 16-06-10

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Information Systems

Access to Document

10.1109/ICIET.2010.5625677

Cite this

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title = "Locomotion classification using emg signal - A comparative study",

abstract = "This work gives a comparative study on the use of Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN) and Naive-Bayes Classifier (NBC) for recognizing various locomotion modes using parameters derived from the transient EMG signals taken from healthy subjects and thus provide a better control mechanism for lower limb prosthesis. These classifiers have been taken into consideration owing to their extensive use in various realtion, time applications.",

author = "Sarthak Pati and Deepak Joshi and Ashutosh Mishra",

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doi = "10.1109/ICIET.2010.5625677",

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AU - Pati, Sarthak

AU - Joshi, Deepak

AU - Mishra, Ashutosh

PY - 2010/12/30

Y1 - 2010/12/30

N2 - This work gives a comparative study on the use of Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN) and Naive-Bayes Classifier (NBC) for recognizing various locomotion modes using parameters derived from the transient EMG signals taken from healthy subjects and thus provide a better control mechanism for lower limb prosthesis. These classifiers have been taken into consideration owing to their extensive use in various realtion, time applications.

AB - This work gives a comparative study on the use of Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN) and Naive-Bayes Classifier (NBC) for recognizing various locomotion modes using parameters derived from the transient EMG signals taken from healthy subjects and thus provide a better control mechanism for lower limb prosthesis. These classifiers have been taken into consideration owing to their extensive use in various realtion, time applications.

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U2 - 10.1109/ICIET.2010.5625677

DO - 10.1109/ICIET.2010.5625677

M3 - Conference contribution

AN - SCOPUS:78650568449

SN - 9781424480012

BT - 2010 International Conference on Information and Emerging Technologies, ICIET 2010

T2 - 2nd International Conference on Information and Emerging Technologies, ICIET 2010

Y2 - 14 June 2010 through 16 June 2010

ER -

Locomotion classification using emg signal - A comparative study

Abstract

Conference

All Science Journal Classification (ASJC) codes

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