On the chaotic nature of biological signals using nonlinear data analysis methodology
Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.
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Universiti Malaysia Perlis
2009
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my.unimap-72912010-01-18T07:01:48Z On the chaotic nature of biological signals using nonlinear data analysis methodology Azian Azamimi, Abdullah Nishio, Yoshifumi azamimi@unimap.edu.my Biological signals Lyapunov functions Control theory Chaotic behavior in systems Biomedical engineering Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. In this study, we analyze the characteristic of biological signals using nonlinear data analysis methodology. Biological signals are not linear so to get a more accurate portrait of nonlinear signals, we must analyze them with nonlinear analysis methods. The nonlinear analysis method is emerging as relatively new and rapidly growing in biomedical field. One of the most useful techniques in nonlinear data analysis is the concept of Lyapunov exponent. As we may know, Lyapunov exponent is often used to define whether a dynamical system is chaotic or not. If the system exhibits at least one positive Lyapunov exponent and is purely deterministic, then it is chaotic. In this work, we measure the finger pulse signal for twenty minutes in two different situations. Then, we analyze the finger pulse signal using nonlinear data analysis method. We extract and evaluate Lyapunov exponent parameters from the finger pulse signal. We finally find the positive value of Lyapunov exponent and confirm the existence of chaotic nature in biological systems. 2009-11-13T08:18:01Z 2009-11-13T08:18:01Z 2009-10-11 Working Paper p.1C5 1 - 1C5 4 http://hdl.handle.net/123456789/7291 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2009) Universiti Malaysia Perlis |
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Biological signals Lyapunov functions Control theory Chaotic behavior in systems Biomedical engineering |
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Biological signals Lyapunov functions Control theory Chaotic behavior in systems Biomedical engineering Azian Azamimi, Abdullah Nishio, Yoshifumi On the chaotic nature of biological signals using nonlinear data analysis methodology |
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Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. |
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azamimi@unimap.edu.my |
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azamimi@unimap.edu.my Azian Azamimi, Abdullah Nishio, Yoshifumi |
format |
Working Paper |
author |
Azian Azamimi, Abdullah Nishio, Yoshifumi |
author_sort |
Azian Azamimi, Abdullah |
title |
On the chaotic nature of biological signals using nonlinear data analysis methodology |
title_short |
On the chaotic nature of biological signals using nonlinear data analysis methodology |
title_full |
On the chaotic nature of biological signals using nonlinear data analysis methodology |
title_fullStr |
On the chaotic nature of biological signals using nonlinear data analysis methodology |
title_full_unstemmed |
On the chaotic nature of biological signals using nonlinear data analysis methodology |
title_sort |
on the chaotic nature of biological signals using nonlinear data analysis methodology |
publisher |
Universiti Malaysia Perlis |
publishDate |
2009 |
url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/7291 |
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1643788750632779776 |
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13.214268 |