Analysis of neuromuscular disorders using statistical and entropy metrics on surface EMG

Rok Istenič (Avtor), Prodromos A. Kaplanis (Avtor), Constantinos S. Pattichis (Avtor), Damjan Zazula (Avtor)

Povzetek

This paper introduces the surface electromyogram (EMG) classification system based on statistical and entropy metrics. The system is intended for diagnostic use and enables classification of examined subject as normal, myopathic or neuropathic, regarding to the acquired EMG signals. 39 subjects in total participated in the experiment, 19 normal, 11 myopathic and 9 neuropathic. Surface EMG was recorded using 4-channel surface electrodes on the biceps brachii muscle at isometric voluntary contractions. The recording time was only 5 seconds long to avoid muscle fatigue, and contractions at fiveforce levels were performed, i.e. 10, 30, 50, 70 and 100 % of maximal voluntary contraction. The feature extraction routine deployed the wavelet transform and calculation of the Shannon entropy across all the scales in order to obtain a feature set for each subject. Subjects were classified regarding the extracted features using three machine learning techniques, i.e. decision trees, support vector machines and ensembles of support vector machines. Four 2-class classifications and a 3-class classification were performed. The scored classification rates were the following: 64+-11% for normal/abnormal, 74+-7% for normal/myopathic, 79+-8% for normal/neuropathic, 49+-20% for myopathic/neuropathic, and 63+-8% for normal/myopathic/neuropathic.

Ključne besede

surface electromyography;neuromuscular disorders;neuropathy;myopathy;EMG signals;signal processing;wavelet transform;metrics;

Podatki

Jezik:	Angleški jezik
Leto izida:	2008
Tipologija:	1.01 - Izvirni znanstveni članek
Organizacija:	UM FERI - Fakulteta za elektrotehniko, računalništvo in informatiko
UDK:	621.391:61
COBISS:	12385046
ISSN:	1790-5052
Št. ogledov:	1428
Št. prenosov:	34
Ocena:	0 (0 glasov)
Metapodatki:

Ostali podatki

Sekundarni jezik:	Angleški jezik
Sekundarne ključne besede:	elektromiografija;nevrologija;medicina;diagnostika;obdelava signalov;obdelava slik;medicinske slike;valčna transformacija;
URN:	URN:SI:UM:
Strani:	str. 28-35
Letnik:	ǂVol. ǂ4
Zvezek:	ǂiss. ǂ2
Čas izdaje:	Feb. 2008
Ključne besede (UDK):	applied sciences;medicine;technology;uporabne znanosti;medicina;tehnika;engineering;technology in general;inženirstvo;tehnologija na splošno;mechanical engineering in general;nuclear technology;electrical engineering;machinery;strojništvo;electrical engineering;elektrotehnika;applied sciences;medicine;technology;uporabne znanosti;medicina;tehnika;medical sciences;medicina;
ID:	13697