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Further Information on Signal Processing for Clinical ...
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  • 1. Further Information on Signal Processing for Clinical Neurophysiology 30 March – 1 April, 2005 Introduction This course is designed for professionals and students in medicine, health care and research, with an interest in the acquisition and computerized analysis of neurophysiological signals. It is aimed to users of these techniques, who may currently have little background in signal processing, engineering, mathematics or computing. The course will provide you with a sound understanding of methods, and practical experience in using digital signal processing and analysis tools for clinical investigation and biomedical research, focussing primarily on the EEG, EMG and evoked potentials. During the course, standard and advanced techniques for signal processing will be discussed, including sampling, rectification and amplitude envelope extraction (especially for EMG applications), digital filtering, coherent averaging and other noise-reduction methods, spectral analysis, coherence, and an introduction to pattern recognition for seizure detection. The course will focus on the concepts, principles and rationale of the techniques, emphasizing the practical implications rather than the underlying theory and mathematical foundations. The course will include computing sessions that provide hands-on experience on problems and solutions in the analysis of signals for neurophysiology. Guest speakers will present case-studies and insights from their recent research work. Outcomes Having successfully completed the module, you will be able to • specify and understand the procedures for digital signal acquisition; • explain the rationale and underlying principles of some commonly used signal analysis procedures; • select appropriate approaches for a range of signal analysis tasks in clinical neurophysiology, and interpret and critically evaluate the results obtained;
  • 2. Course Content (provisional) Day 1 1) Review of electrophysiological signals Physiological origin Acquisition Sources of noise and artefact Clinical uses: from acquisition to interpretation 2) Analogue to Digital conversion Sampling theorem and aliasing Quantization File-storage 3) Visit to a laboratory and discussion of current activities (e.g. gait or audiology lab) 4) Hands-on exercises and demos Signal rectification and integration Smoothing: amplitude envelope extraction for the EMG Day 2 1) Fourier transforms 2) Filtering High-pass, low-pass and band-pass filtering; Introduction to the design of digitial filters; Applications in EEG and EMG 3) Coherent averaging Evoked potentials Principles of coherent averaging Artefact rejection 4) Hands-on exercises and demos Frequency domain analysis of EEG and EMG signals Digital filtering Coherent averaging Estimation of activation timing in EMG Day 3 1) Spectral analysis Random and deterministic signals
  • 3. Spectral estimation Applications in EMG and EEG 2) Correlation and coherence Estimating similarity and delay between signals Estimating and interpreting coherence measurements 3) Seminar: Seizure detection in the EEG 4) Hands-on exercises and demos Spectral analysis of EMG and EEG signals Time-varying spectra Teaching The module consists of three days of intensive instruction, involving lectures, demonstrations, and practical implementation of the techniques discussed in the lectures. The latter will be primarily based on Matlab programming exercises and demos using patient-recorded signals. Lap-top computers will be provided. Visits to a laboratory will also be arranged. Pre-requisites You should have some basic familiarity with biomedical signals, and also with the use of Windows -based computers. You do not need previous training in digital signal processing, mathematics (beyond O-level) or computer programming. Some practical experience with neurophysiological signals is desirable. Lecturers Dr. David Simpson Dr. Antonio De Stefano Dr. Christopher James