Thesis Details

Klasifikace příkazů z EMG pomocí neuronové sítě

Bachelor's Thesis Student: Zauška Ján Academic Year: 2019/2020 Supervisor: Szőke Igor, Ing., Ph.D.
English title
Command Classification from EMG Using Neural Network
Language
Czech
Abstract

This work deals with classification of 15 commands (short words), from small dataset recorded by sEMG electrodes placed on face and neck of speaker. Two types of speech are differentiated in recordings - audible speech, what is classic speech and silent speech, hence speech, in which sound output is suppressed. This work describes EMG signal processing, feature extraction, classifier design and classification results. The convolutional neural network architecture was used as a classifier. There are a lot of experiments in this work that compare the classification accuracy of silent and audible speech.

Keywords

EMG, AI, CNN, Electromyography, Silent speech, Neural Networks, Convolutional Neural networks

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology
Files
Status
defended, grade B
Date
10 July 2020
Reviewer
Šůstek Martin, Ing.
Committee
Černocký Jan, prof. Dr. Ing. (DCGM FIT BUT), předseda
Češka Milan, doc. RNDr., Ph.D. (DITS FIT BUT), člen
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Orság Filip, Ing., Ph.D. (DITS FIT BUT), člen
Rychlý Marek, RNDr., Ph.D. (DIFS FIT BUT), člen
Citation
ZAUŠKA, Ján. Klasifikace příkazů z EMG pomocí neuronové sítě. Brno, 2020. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2020-07-10. Supervised by Szőke Igor. Available from: https://www.fit.vut.cz/study/thesis/22911/
BibTeX 
@bachelorsthesis{FITBT22911,
    author = "J\'{a}n Zau\v{s}ka",
    type = "Bachelor's thesis",
    title = "Klasifikace p\v{r}\'{i}kaz\r{u} z EMG pomoc\'{i} neuronov\'{e} s\'{i}t\v{e}",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2020,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/22911/"
}

Theses

Back to top