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Command Classification from EMG Using Neural Network
Zauška, Ján ; Šůstek, Martin (referee) ; Szőke, Igor (advisor)
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.
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The effect of incentive spirometry and postural loading on activity ofvrespiratory muscles
Sakaláš, Radovan ; Truc, Michal (advisor) ; Demeková, Júlia (referee)
Master thesis "The effect of incentive spirometry and postural lability on activity of respiratory muscles" deals mainly with electromyographic activity of respiratory muscles while using incentive spirometry. In the first part the following aspects of breathing are covered: kinesiology, pattern, work, and the respiratory and postural function of respiratory muscles. The next section describes the main types of incentive spirometers and indications and contraindications of their usage. Furthermore, the thesis defines neurophysiological basics needed for electromyographic usage and the influence on its signal quality. The main part of the thesis deals with the issues of incentive spirometer usage and postural lability and the effects on activity of the respiratory muscles. The final section suggests recommendations regarding the suitable position for effective respiratory-postural function training using incentive spirometry. Powered by TCPDF (www.tcpdf.org)
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Command Classification from EMG Using Neural Network
Zauška, Ján ; Šůstek, Martin (referee) ; Szőke, Igor (advisor)
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.
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The effect of incentive spirometry and postural loading on activity ofvrespiratory muscles
Sakaláš, Radovan ; Demeková, Júlia (referee) ; Truc, Michal (advisor)
Master thesis "The effect of incentive spirometry and postural lability on activity of respiratory muscles" deals mainly with electromyographic activity of respiratory muscles while using incentive spirometry. In the first part the following aspects of breathing are covered: kinesiology, pattern, work, and the respiratory and postural function of respiratory muscles. The next section describes the main types of incentive spirometers and indications and contraindications of their usage. Furthermore, the thesis defines neurophysiological basics needed for electromyographic usage and the influence on its signal quality. The main part of the thesis deals with the issues of incentive spirometer usage and postural lability and the effects on activity of the respiratory muscles. The final section suggests recommendations regarding the suitable position for effective respiratory-postural function training using incentive spirometry. Powered by TCPDF (www.tcpdf.org)
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