Naslov
Automatic Muscle Activity Onset Determination in Countermovement Jump

Autori
Potočanac, Zrinka ; Cifrek, Mario ; Peharec, Stanislav ; Bačić, Petar

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Abstracts of the XVIII Congres of the International Society of Electrophysiology and Kinesiology / Farina, Dario ; Falla, Deborah ; Popivić, Dejan ; Sinkjaer, Thomas - Aaalborg : Department of Health Science and Technology, Aalborg University, 2010

ISBN
978-87-7094-047-4

Skup
XVIII Congress of the International Society of Electrophysiology and Kinesiology (ISEK 2010)

Mjesto i datum
Aalborg, Danska, 16.07.2010. - 19.07.2010

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
SEMG; muscle onset; countermovement jump

Sažetak
Aim of this research was to find a method (and its parameters) that would allow for correct and automatic determination of muscle onset and offset while performing countermovement jump movements thus enabling further analysis of these movements. Surface electromyographic signals of leg muscles were recorded on both legs as 25 professional handball players performed countermovement jump. All jumps were synchronized in time to force platform recordings. Two algorithms for automatic onset determination were tested. First algorithm, as previously described in (Hodges and Bui, 1996), searched for a time window in which mean amplitude of the samples exceeded given amplitude threshold and considered first sample of such window as the muscle onset moment. This algorithm was then modified to remove short periods falsely detected as muscle activity by adding post processing that determined if detected activity was too short. If the detected muscle activity change resulted in activity shorter than time given as the duration threshold it was discarded as false detection. These algorithms were tested on recorded signals with different combinations of parameters (amplitude and duration threshold values, time window width) on both full wave rectified EMG signal and low pass filtered EMG signal with different cut off frequencies. Comparison with onset/offset times determined visually by an experienced researcher is pending. Modified algorithm for detecting muscle onset showed better results while basic threshold algorithm found a large number of short activity burst periods. Due to low standard deviation of the baseline, better results were obtained using amplitude threshold defined as a percentage of maximum signal amplitude.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

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