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
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