Biomedical Engineering
Biomedical signals are signals that are produced by the human body. They are records of the electrical, chemical or mechanical activity that occurs during biological events, such as the beating of the human heart or the contraction of a muscle. Biomedical signals can provide insight into the underlying physiological mechanisms and provide information about the state of health of the biological system that produces these signals.
Traditionally biomedical signals, such as ECG signals, are analysed in the time-domain by skilled physicians. However, abnormalities may be subtle and difficult to detect by visual inspection. Currently the interpretation of biomedical signals depends mainly on physicians' skills, knowledge and experience. Therefore the interpretation may vary. Another limitation is that pathological conditions may not always be obvious in the original time-domain signal. Signal processing techniques can assist in the analysis of biomedical signals by eliminating unwanted information and extracting the relevant features of the signals.
The complexity of biomedical signals provides big challenges. Biomedical signals are generated by complex self-regulating systems and the analysis of biomedical signals is complicated by the fact that the signals are typically both highly irregular and non-stationary. Time dependent variations and transient phenomena play an important role. Traditional signal processing techniques, such as Fourier analysis, do not deal very well with these transient phenomena. A Fourier coefficient represents a frequency component, which lasts for all time and temporary events usually need to be represented by a large number of coefficients. Methods, which allow a more accurate local description and separation of signal characteristics, such as wavelet transforms may therefore be more suitable.
The purpose of this research is the development of signal processing algorithms to extract useful information from biomedical and biological signals. We intend to develop methods, which provide a quantitative evaluation of particular signal features and classify particular patterns. The overall goal is to develop signal-processing tools, which are useful for medical diagnosis and provide insight in the underlying physiological systems, determining their state and providing their future behaviour.
Research Coordinator: Ms Mirjam Jonkman
