The University of Southampton
University of Southampton Institutional Repository

Demystifying biomedical signals: A student centred approach to learning signal processing

Demystifying biomedical signals: A student centred approach to learning signal processing
Demystifying biomedical signals: A student centred approach to learning signal processing
The processing and analysis of physiological signals has become firmly established in clinical medicine and biomedical research. Many of the users of this technology however do not come from an engineering or science background, and traditional approaches in teaching signal processing are thus not appropriate for them. We have therefore developed a series of modular courses that are aimed specifically at an audience with a background in medicine, health-care or the life-sciences. In these courses, we focus on the concepts, principles and rationale of applying signal processing methods, rather than the mathematical foundations of the techniques. Thus, we aim to remove some of the perceived ‘mystery’ often surrounding this subject. The very practical approach, with hands-on experience using the MATLAB® software, has been well received, with strong evidence that students have learnt to apply their knowledge. This paper describes the learning and teaching approach taken, and some of the experience acquired.
education, training, signal processing, biomedical engineering
1350-4533
583-589
Simpson, D.M.
9572e2c3-86d5-47a8-98f0-129c372e5432
De Stefano, A.
103547f3-163d-4670-8839-1799a638e653
Allen, R.
9d2d7d1d-d59d-4954-89b7-c48307a208e6
Lutman, M.E.
765efa2b-f995-4ab4-b9bf-acbb6bb6f890
Simpson, D.M.
9572e2c3-86d5-47a8-98f0-129c372e5432
De Stefano, A.
103547f3-163d-4670-8839-1799a638e653
Allen, R.
9d2d7d1d-d59d-4954-89b7-c48307a208e6
Lutman, M.E.
765efa2b-f995-4ab4-b9bf-acbb6bb6f890

Simpson, D.M., De Stefano, A., Allen, R. and Lutman, M.E. (2005) Demystifying biomedical signals: A student centred approach to learning signal processing. Medical Engineering & Physics, 27 (7), 583-589. (doi:10.1016/j.medengphy.2004.11.011).

Record type: Article

Abstract

The processing and analysis of physiological signals has become firmly established in clinical medicine and biomedical research. Many of the users of this technology however do not come from an engineering or science background, and traditional approaches in teaching signal processing are thus not appropriate for them. We have therefore developed a series of modular courses that are aimed specifically at an audience with a background in medicine, health-care or the life-sciences. In these courses, we focus on the concepts, principles and rationale of applying signal processing methods, rather than the mathematical foundations of the techniques. Thus, we aim to remove some of the perceived ‘mystery’ often surrounding this subject. The very practical approach, with hands-on experience using the MATLAB® software, has been well received, with strong evidence that students have learnt to apply their knowledge. This paper describes the learning and teaching approach taken, and some of the experience acquired.

This record has no associated files available for download.

More information

Published date: 2005
Keywords: education, training, signal processing, biomedical engineering

Identifiers

Local EPrints ID: 28472
URI: http://eprints.soton.ac.uk/id/eprint/28472
ISSN: 1350-4533
PURE UUID: c54c285b-9c3c-4e1c-9ee0-9371b6b84d72

Catalogue record

Date deposited: 02 May 2006
Last modified: 15 Mar 2024 07:25

Export record

Altmetrics

Contributors

Author: D.M. Simpson
Author: A. De Stefano
Author: R. Allen
Author: M.E. Lutman

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×