BSP

Course Description:

Biomedical signal processing (BSP) is about algorithms for processing a particular class of digital signals which are acquired in biomedical research and clinical medicine. Biomedical signals are recordings of physiological activities of organisms, ranging from gene and protein sequences, to neural and cardiac rhythms, to tissue and organ images. Electrocardiogram (ECG), electroencephalogram (EEG), electromyogram (EMG) and various sensory evoked potentials are a few examples of such bioelectric signals. In spite of slight differences in origins and data acquisition procedures, all recorded vital signals share common characteristic features (in different space and time scales) and suffer from common disturbances and artifacts. Biomedical signal processing aims at extracting significant information from such signals. A large number of processing algorithms have been particularly proposed to suppress disturbances in physiological recordings and facilitate diagnostic feature extraction. With the aid of biomedical signal processing, biologists and neuroscientists can develop hypotheses to explain physiological functions and physicians can monitor distinct states of malfunctions/disorders. This lecture briefly introduces bio-electrical phenomena, data acquisition procedures, filtering fundamentals, spectrum estimation and feature extraction. In addition, it provides a few examples of elementary linear and non-linear modeling formalisms. Although the topics covered by this lecture are specialized for processing of vital signals, the introduced method are generally described to be applicable in problems of other fields of science and technology.


References:

  • Cohen, Arnon. Biomedical Signal Processing: Time and frequency domains analysis, Volume I. CRC-Press, 1986.
  • Sörnmo, Leif, and Pablo Laguna. Bioelectrical signal processing in cardiac and neurological applications. Vol. 8. Academic Press, 2005.
  • Alan, V. Oppenheim, W. Schafer Ronald, and R. B. John. "Discrete-time signal processing." New Jersey, Printice Hall Inc (1989).
  • Akay, Metin. Biomedical signal processing. Academic Press, 2012.
  • Devasahayam, Suresh R. Signals and systems in biomedical engineering: signal processing and physiological systems modeling. Springer Science & Business Media, 2012.


Pre-requisites:

Solid knowledge of linear algebra, elementary probability, calculus and complex variables


Lecture Notes:

PhysioNet (MIMIC, MIT-BIH Arrhythmia Database), ADHD-200, BSI


Homework:

Quiz and exams: