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Biomedical Signal Processing Fall 2017

Biomedical Signal Processing (Course Number: 340113)

[under construction]

Jacobs University Bremen, Fall 2017, Fatemeh Hadaeghi


Class sessions:  

Wednesdays 11:15- 12:30, East Hall 3


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.



General measurments and diagnostic systems, the origin of biomedical signals, biomedical aquisition and processing, digital signals and systems, sampling, random processes, z- transform, estimation theory, frequency domain analysis, time series analysis: linear prediction, spectral estimation


Grading and Exams:

The final course grade will be determined as follows:

- class attendance (presence sheets) will count for 10% of the final grade

- three miniquizzes which each will account to 10% of the final grade

- homework will count for 15% of the final grade

- one final exam will count for 45% of the final grade

All quizzes and the final exam are open book.

Miniquiz makeup rules: if a miniquiz is missed without excuse, it will be graded with 0 points. An oral makeup will be offered for medically excused miniquizzes according to the Jacobs rules (especially, the medical excuse must be announced to me before the miniquiz). Non-medical excuses can be accepted on a case-by-case basis.



Primary text:

Required reading:

  • Alan, V. Oppenheim, W. Schafer Ronald, and R. B. John. "Discrete-time signal processing." New Jersey, Printice Hall Inc (1989).
  • Cohen, Arnon. Biomedical Signal Processing: Time and frequency domains analysis, Volume I. CRC-Press, 1986. 

Recommended reading: 

  • Alan, V. Oppenheim, W. Schafer Ronald, and R. B. John. Discrete-time signal processing. New Jersey, Printice Hall Inc (1989).
  • Cohen, Arnon. Biomedical Signal Processing: Time and frequency domains analysis, Volume I. CRC-Press, 1986. 
  • Proakis, John G., and Dimitris G. Manolakis. Digital signal processing: principles, algorithms, and applications. (1996). 
  • Cohen, Arnon. Biomedical Signal Processing: Compression and automatic recognition, Volume II. CRC-Press, 1986. 
  • Rangayyan, Rangaraj M. Biomedical signal analysis. Vol. 33. John Wiley & Sons, 2015. 
  • Sörnmo, Leif, and Pablo Laguna. Bioelectrical signal processing in cardiac and neurological applications. Vol. 8. Academic Press, 2005. 
  • Van Drongelen, Wim. Signal processing for neuroscientists: an introduction to the analysis of physiological signals. Academic press, 2006.
  • Najarian, Kayvan, and Robert Splinter. Biomedical signal and image processing. CRC press, 2005. 
  • Cerutti, Sergio, and Carlo Marchesi, eds. Advanced methods of biomedical signal processing. Vol. 27. John Wiley & Sons, 2011. 
  • 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. 
  • Sanei, Saeid, and Jonathon A. Chambers. EEG signal processing. John Wiley & Sons, 2013. 
  • Acharya, Rajendra, et al., eds. Advances in cardiac signal processing. Berlin: Springer, 2007.