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Title:VREDNOTENJE RAČUNALNIŠKO-PODPRTIH POSTOPKOV ZA ROBUSTNO IN NEINVAZIVNO MERJENJE MIŠIČNE UTRUJENOSTI
Authors:Plankelj, Jernej (Author)
Holobar, Aleš (Mentor) More about this mentor... New window
Files:.pdf UNI_Plankelj_Jernej_2014.pdf (2,47 MB)
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Površinski elektromiogram (EMG) omogoča neinvazivno in skoraj nemoteče merjenje mišične utrujenosti. S tem odpira nove možnosti v implementaciji sodobnih vmesnikov mišice-stroj in njihovi uporabi v zabavni industriji, medicini dela, urjenju športnikov ter rehabilitaciji. V diplomskem delu smo primerjali različne postopke računalniško podprtega vrednotenja mišične utrujenosti iz signalov EMG. V ta namen smo preučili zvezo med srednjo usmerjeno vrednostjo zajetih signalov EMG, izmerjeno mišično silo in aktivacijskim signalom mišice, ocenjenim na podlagi dekompozicije signalov EMG na prispevke posameznih motoričnih enot. Preučili smo tako vpliv dolžine okna za izračun srednje usmerjene vrednosti kot tudi vpliv števila kanalov signalov EMG. Slednje smo s poljem 64 elektrod posneli med izometrično skrčitvijo mišice abductor pollicis brevis pri osmih zdravih preiskovancih. Rezultati kažejo, da uporaba predolgega okna in le enega kanala ne omogoča natančne analize mišične utrujenosti.
Keywords:vmesniki mišice-stroj, mišična utrujenost, elektromiogram, amplituda, mišična sila, aktivacijski signal mišice, srednje usmerjena vrednost
Year of publishing:2014
Publisher:J. Plankelj
Source:[Maribor
UDC:004.5:616-073.7(043.2)
COBISS_ID:19165974 Link is opened in a new window
NUK URN:URN:SI:UM:DK:8CVDLVXU
Views:415
Downloads:101
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:DETECTION OF MUSCLE FATIGUE WITH MULTICHANNEL MUSCLE-COMPUTER INTERFACE
Abstract:Surface electromyogram (EMG) enables non-invasive and unobtrusive assessment of muscle fatigue. This opens up new possibilities in the implementation of modern muscle-machine interfaces and their use in the entertainment industry, occupational medicine, rehabilitation and training of athletes. In our thesis, we compared different methods of computer-aided evaluation of muscle fatigue from EMG signals. We examined the relationship between the average rectified value (ARV) of acquired EMG signals, muscle force and neural drive to the muscle. The latter was estimated by decomposing EMG signals into the contributions of individual motor units. We have examined both the impact of the length of the window in AVR calculation, as well as the impact of number of EMG channels. EMG signals were acquired by the array of 64 electrodes during isometric contraction of abductor pollicis brevis muscle in eight healthy subjects. The results show that the use of windows of excessive length and only one EMG channel prevents precise muscle fatigue analysis.
Keywords:muscle-computer interface, muscle fatigue, electromyogram, amplitude, muscle force, neural drive to skeletal muscles, root mean square


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