Analiza mioelektričkih signala tijekom dinamičkog umaranja

doctoral thesis

• Author: Mario Cifrek
• Mentor: Stanko Tonković (mentor)
• Committee member: Ante Šantić (član povjerenstva)
• Committee member: Stanko Tonković (član povjerenstva)
• Committee member: Vladimir Medved (član povjerenstva)
• Committee member: Branko Jeren (član povjerenstva)
• Committee member: Ljubo Marangunić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; (Department of Electronic Systems and Information Processing); Zagreb
• Defense date and country: 1997-06-09, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Electrical Engineering; Electronics
• Universal decimal classification (UDC): 621.3; APPLIED SCIENCES. MEDICINE. TECHNOLOGY; Electrical engineering

Abstract

U radu je prikazana jedna metoda mjerenja i analize površinskih mioelektričkih signala u cilju određivanja umora mišića tijekom cikličkih dinamičkih kontrakcija kakve su prisutne u svakodnevnom životu, pri bavljenju određenim sportskim aktivnostima, tijekom treninga ili kineziološke rehabilitacije, a pri kojima postoji i subjektivna varijabilnost određenih biomehaničkih parametara pokreta. Mjereni su površinski mioelektrički signali triju mišića natkoljenice (m. rectus femoris, m. vastus lateralis i m. vastus medialis longus) tijekom izvođenja pokreta ekstenzije i fleksije potkoljenice na komercijalno dostupnoj trenažnoj spravi. Istovremeno s elektromiografskim mjerenjem praćeni su kut poluge trenažne sprave kao kinematički pokazatelj pokreta te frekvencija srčanog ritma kao pokazatelj umora ispitanika. Usporedba vremenskih kinematičkih pokazatelja pokreta pokazala je, prema očekivanju, razlike u izvođenju zadanog pokreta između pojedinih ispitanika. Za analizu mioelektričkih signala izmjerenih tijekom dinamičkih kontrakcija korištena je metoda vremensko-frekvencijske analize nestacionarnih signala koja se temelji na procjeni spektara snage odsječaka signala Fourierovom transformacijom, spektrogram. Kao pokazatelj umora mišića korištena je promjena frekvencije medijana spektra snage izračunata iz spektrograma mioelektričkih signala. Rezultati analize pokazuju da se ovom metodom može objektivno odrediti umor pojedinog mišića iz grupe agonista koji sudjeluju u pokretu, a dodatno ukazuju i na razlike u dominantnom tipu mišićnih vlakana pojedinih mišića. Rezultati rada, razvoj mjerne tehnike te metode obrade i analize signala, primjenjivi su za određivanje umora mišića tijekom cikličkih dinamičkih kontrakcija u najrazličitijim područjima ljudskih djelatnosti kao npr. pri praćenju učinkovitosti terapijskih postupaka kod kineziterapije, treninga sportaša, te ergonomskim ispitivanjima.

Abstract (english)

A method of surface myoelectric signal measurement and analysis is presented with the aim of evaluating muscle fatigue during cyclic dynamic contractions, such as those encountered in everyday sport activities and during training or kinesiological rehabilitation. During such activities subjective variability of certain biomechanical movement parameters exists. Surface myoelectric signals from three upper leg muscles (m. rectus femoris, m. vastus lateralis, m. vastus medialis) were monitored during lower leg extension and flexion exercise on commercially available training device. Simultaneously with electromyographic measurement, shaft angle of the training device as a kinematic parameter of movement was monitored, as well as the heart rate, used as a fatigue indicator of the complete subject’s organism. Comparing kinematic movement parameters, differences in performance of defined movement between subjects were noticed. A method of non-stationary signal time-frequency analysis, based on power spectra estimation using short-time Fourier transform, i. e. spectrogram, was used in the analysis of myoelectric signals recorded during dynamic contractions. As an indicator of muscle fatigue, a change in power spectrum median frequency calculated from the spectrogram has been used. According to the results of the analysis, this method provides an objective evaluation of particular muscle’s fatigue, among the agonists participating in the movement, as well as an indication of differences in dominant muscle fibre type in observed muscles. The results of the study, the developed measurement technique and the method of signal processing and analysis can be applied in muscle fatigue evaluation during cyclic dynamic contractions in various areas of human activities, as for instance during follow-up of sports training efficiency, ergonomic analysis and monitoring of therapeutic methods efficiency in kinesiological rehabilitation.

• Keywords: Vremensko-frekvencijska analiza signala; površinska elektromiografija; EMG; umor mišića; dinamičke kontrakcije; biomehanika mišića; kineziologija; kineziterapija
• Keywords (english): Time-frequency signal analysis; surface electromyography; EMG; muscle fatigue; dynamic contractions; muscle biomechanics; kinesiology; kinesiological rehabilitation
• Language: croatian
• URN:NBN: urn:nbn:hr:168:169649
• Study programme: Title: Doctoral study programme "Electrical Engineering and Computing"; Study programme type: university; Study level: postgraduate; Academic / professional title: doktor/doktorica znanosti, po-dručje tehničkih znanosti (doktor/doktorica znanosti, po-dručje tehničkih znanosti)
• Type of resource: Text
• File origin: Reformatted digital
• Access conditions: Closed access
• Created on: 2019-03-20 10:46:10