Abstract
Fractal dimension was demonstrated to be able to characterize the complexity of biological signals. The EMG time series are well known to have a complex behavior and some other studies already tried to characterize these signals by their fractal dimension. This paper is aimed at studying the correlation between the fractal dimension of surface EMG signal recorded over Rectus Femoris muscles during a vertical jump and the height reached in that jump. Healthy subjects performed vertical jumps at different heights. Surface EMG from Rectus Femoris was recorded and the height of each jump was measured by an optoelectronic motion capture system. Fractal dimension of sEMG was computed and the correlation between fractal dimension and eight of the jump was studied. Linear regression analysis showed a very high correlation coefficient between the fractal dimension and the height of the jump for all the subjects. The results of this study show that the fractal dimension is able to characterize the EMG signal and it can be related to the performance of the jump. Fractal dimension is therefore an useful tool for EMG interpretation.
| Original language | English |
|---|---|
| Pages (from-to) | 120-126 |
| Number of pages | 7 |
| Journal | Chaos, Solitons and Fractals |
| Volume | 66 |
| DOIs | |
| Publication status | Published - 2014 |
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ASJC Scopus subject areas
- Mathematics(all)
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Linear correlation between fractal dimension of surface EMG signal from Rectus Femoris and height of vertical jump. / Ancillao, Andrea; Galli, Manuela; Rigoldi, Chiara; Albertini, Giorgio.
In: Chaos, Solitons and Fractals, Vol. 66, 2014, p. 120-126.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Linear correlation between fractal dimension of surface EMG signal from Rectus Femoris and height of vertical jump
AU - Ancillao, Andrea
AU - Galli, Manuela
AU - Rigoldi, Chiara
AU - Albertini, Giorgio
PY - 2014
Y1 - 2014
N2 - Fractal dimension was demonstrated to be able to characterize the complexity of biological signals. The EMG time series are well known to have a complex behavior and some other studies already tried to characterize these signals by their fractal dimension. This paper is aimed at studying the correlation between the fractal dimension of surface EMG signal recorded over Rectus Femoris muscles during a vertical jump and the height reached in that jump. Healthy subjects performed vertical jumps at different heights. Surface EMG from Rectus Femoris was recorded and the height of each jump was measured by an optoelectronic motion capture system. Fractal dimension of sEMG was computed and the correlation between fractal dimension and eight of the jump was studied. Linear regression analysis showed a very high correlation coefficient between the fractal dimension and the height of the jump for all the subjects. The results of this study show that the fractal dimension is able to characterize the EMG signal and it can be related to the performance of the jump. Fractal dimension is therefore an useful tool for EMG interpretation.
AB - Fractal dimension was demonstrated to be able to characterize the complexity of biological signals. The EMG time series are well known to have a complex behavior and some other studies already tried to characterize these signals by their fractal dimension. This paper is aimed at studying the correlation between the fractal dimension of surface EMG signal recorded over Rectus Femoris muscles during a vertical jump and the height reached in that jump. Healthy subjects performed vertical jumps at different heights. Surface EMG from Rectus Femoris was recorded and the height of each jump was measured by an optoelectronic motion capture system. Fractal dimension of sEMG was computed and the correlation between fractal dimension and eight of the jump was studied. Linear regression analysis showed a very high correlation coefficient between the fractal dimension and the height of the jump for all the subjects. The results of this study show that the fractal dimension is able to characterize the EMG signal and it can be related to the performance of the jump. Fractal dimension is therefore an useful tool for EMG interpretation.
UR - http://www.scopus.com/inward/record.url?scp=84903993008&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84903993008&partnerID=8YFLogxK
U2 - 10.1016/j.chaos.2014.06.004
DO - 10.1016/j.chaos.2014.06.004
M3 - Article
AN - SCOPUS:84903993008
VL - 66
SP - 120
EP - 126
JO - Chaos, Solitons and Fractals
JF - Chaos, Solitons and Fractals
SN - 0960-0779
ER -