prikaz prve stranice dokumenta Contribution to differential electromyographic diagnostics of low back pain and radiculopathy
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doctoral thesis
Contribution to differential electromyographic diagnostics of low back pain and radiculopathy
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:448344
Ostojić, Saša
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Ostojić, S. (2019). Contribution to differential electromyographic diagnostics of low back pain and radiculopathy (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:448344

Ostojić, Saša. "Contribution to differential electromyographic diagnostics of low back pain and radiculopathy." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:448344

Ostojić, Saša. "Contribution to differential electromyographic diagnostics of low back pain and radiculopathy." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:448344

Ostojić, S. (2019). 'Contribution to differential electromyographic diagnostics of low back pain and radiculopathy', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 16 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:448344

Ostojić S. Contribution to differential electromyographic diagnostics of low back pain and radiculopathy [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 May 16] Available at: https://urn.nsk.hr/urn:nbn:hr:168:448344

S. Ostojić, "Contribution to differential electromyographic diagnostics of low back pain and radiculopathy", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:448344

Metadata
TitleContribution to differential electromyographic diagnostics of low back pain and radiculopathy
Title (croatian)Prilog diferencijalnojelektromiografskoj dijagnostici križobolje i radikulopatije
AuthorSaša Ostojić
MBZ: -346762
MentorMario Cifrek (mentor)
MentorStanislav Peharec (komentor)
Committee memberMario Cifrek (predsjednik povjerenstva)
Committee memberStanislav Peharec (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Data Processing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
Abstract
Low back pain is one of the leading causes of absence from work. Diagnosing low back pain patients or mere differentiation from healthy subjects is therefore an interesting problem. One way to diagnose comes from properties of surface EMG signals to reflect complex changes occurring within skeletal muscles during fatiguing static contractions. This doctoral work introduces differentiation of low back pain patients with radiculopathy from chronic nonspecific low back pain patients and from healthy subjects based only on four surface EMG signals. The measurement protocol was simplified, and subject’s own upper body weight is used to induce muscle fatigue in low back muscles. Surface EMG signals were recorded during static contractions above m. erector spinae. The adaptive time-frequency method, Hilbert-Huang transform, was utilized to estimate power spectrum of the recorded surface EMG signals. As a descriptor of surface EMG spectral changes, the regression line of slope of the median frequency of the power spectrum was calculated and used as classification feature for the decision tree classification. Proposed measurement protocol, defined classification feature and classification model enable electromyographic differentiation of low back pain patients with radiculopathy and chronic nonspecific low back pain patients, where achieved overall accuracy of classification is up to 86.8 %.
Abstract (croatian)
Križobolja je jedan od vodećih razloga izostajanja s posla. Zato je dijagnosticiranje križobolje u pacijenata ili već i samo njihovo razlikovanje od zdravih osoba zanimljiv problem za proučavanje. Jedan od načina dijagnosticiranja proizlazi iz svojstva površinskih EMG signala da odražavaju složene promjene u skeletnim mišićima što nastaju tijekom umarajućih statičkih kontrakcija. Ovaj doktorski rad uvodi diferencijaciju pacijenata s križoboljom s radikulopatijom od pacijenata s kroničnom nespecifičnom križoboljom, te od zdravih ispitanika, temeljem samo četiri površinska EMG signala. Mjerni protokol je pojednostavljen te se težina gornjeg dijela tijela ispitanika koristi za izazivanje mišićnog umora u mišićima donjeg dijela leđa. Površinski EMG signali snimani su tijekom statičkih kontrakcija iznad m. erector spinae. Adaptivna vremensko-frekvencijska metoda, Hilbert-Huang transformacija, korištena je za procjenu spektra snage snimljenih površinskih EMG signala. Kao deskriptor promjene spektra površinskih EMG signala, izračunat je nagib regresijskog pravca frekvencije medijana spektra snage i korišten kao klasifikacijska značajka za klasifikaciju stablom odlučivanja. Predloženi mjerni protokol, definirana klasifikacijska značajka i klasifikacijski model omogućavaju elektromiografsku diferencijaciju pacijenata s križoboljom s radikulopatijom i pacijenata s kroničnom nespecifičnom križoboljom, pri čemu je ostvarena ukupna točnost klasifikacije do 86,8 %.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:168:448344
Study programmeTitle: Computer Science
Study programme type: university
Study level: postgraduate
Academic / professional title: Doktor znanosti (Doktor znanosti)
Type of resourceText
Extentstr. 85; 30 cm
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Created on2019-03-26 08:28:23