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Prof David M Simpson BSc, PhD

Professor of Biomedical Signal Processing

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Prof David Simpson is Professor of Biomedical Signal Processing within Engineering and Physical Sciences at the University of Southampton. His research and teaching focuses on the application of engineering techniques in a medical context. He aims to address real-world problems using computational data analysis (signal processing) methods for the benefit of patients and other users.


Biomedical engineering provides a stimulating mix of 'hard' science and engineering, with the excitement of understanding more of biology and the motivation to help patients.

After schooling in Austria, he graduated in Biomedical Electronics from the University of Salford (1981) and then worked as a mathematics and physics teacher in Nigeria. He obtained a PhD in Electrical Engineering from Imperial College of Science, Technology and Medicine, University of London in 1988. From 1989 to 1998 he lectured in the Biomedical Engineering Program at the Federal University of Rio de Janeiro (Brazil), before becoming a research fellow in the Medical Physics Department of Leicester Royal Infirmary. He moved to the University of Southampton (ISVR) in 2001.

His research aims primarily to develop data analysis (signal processing) methods that extract diagnostic information from complex biomedical signals to improve the understanding of physiology and provide innovative diagnostic methods. Specific topics of research include:

  1. Control of blood flow to the brain (cerebral autoregulation)
  2. Assessment of hearing function using electrical signals from the brain (EEG and evoked potentials) and other physiological signals.

In his teaching he aims to enable students to solve problems at the interface between engineering and medicine/health sciences, with an understanding of the relevant technologies as well as the wider context of the application of healthcare technology. He enjoys teaching at the interface between disciplines with students from a wide range of educational backgrounds.

Research interests

Current research interests include:

  1. The control of blood flow to the brain when blood pressure changes (cerebral autoregulation).
  2. Detection of ‘auditory evoked responses’, which are responses in the EEG signals to auditory stimulation such as pips and clicks, as well as speech signals.

Previous work includes rehabilitation after stroke, biofeedback for pain reduction, analysis of depth of anaesthesia using EEG based brain connectivity, cardiovascular/respiratory control and the analysis of neuromuscular control in insect limbs.

David Simpson's research aims to improve the care of patients. To this end he develops and applies signal processing methods that extract diagnostic information from complex biomedical signals (e.g. from traces of ECG or blood pressure) and improves the understanding of physiology and hence innovative diagnostic methods.

Photograph of Prof David Simpson
Figure 1

Figure 1: The analysis of biomedical signals provides new insights into physiology and paves the way to new diagnostic techniques.

Research group

Signal Processing, Audio and Hearing Group

Affiliate research groups

Interdisciplinary Dementia and Ageing Centre , Cerebral Autoregulation Research Network (CARNet)

Research project(s)

Anaesthesia and awareness

Occasionally people wake up during surgery, which is highly distressing. It is a particular problem when a muscle relaxant is given as people are unable to move to tell people that they are awake. We hope to develop methods that can tell if people are awake in operations using either the brain response to sound, or the patterns of connection in the brain.

The Hearing Brain

It is possible to measure the electrical response of the brain to sound. However the signals are very small and can be swamped by electrical activity from rest of the body. In this project we are developing better methods to measure the tiny signals and exploring their clinical applications.

2 ears are better than 1

What benefit do people with hearing loss get from using two devices, one in each ear?

Improving the acquisition of Auditory Evoked Potentials for clinical diagnosis

This research aims to improve acquisition of these responses and to assess and improve their diagnostic utility.

New methods for assessing the control of blood flow in the brain

Objective measures of hearing aid benefit

We would like to develop a set of objective test methods that can be used to compare the various features of modern hearing aids and to predict which features will best improve patient benefit from hearing aids.

Quantitative measurements of impairment and how they relate to activity in the upper limb of the older adult post-stroke

Modelling of the neuronal responses of identified motor neurons across animals

Independent component analysis in the automated detection of evoked potentials from multichannel recording

What are hearing aids up to?

Developing methods to measure the performance of advanced features in hearing aids/cochlear implants and to predict how much they will benefit patients.

Muscle models with applications

How can we improve existing muscle models and use these to detect the effect of therapies, medicines, and any other external factor on muscle performances?

Diversity in blood flow control to the brain

Human response to force and hand-arm vibration

The aim of the project is to understand the mechanisms involved in mediating the physiological responses of human hand to vibration and force. The further model could be developed to link the physiological responses with the biodynamic measures. The results of this project will identify the effective evaluation and prevention methods of hand arm vibration injuries and further guidance to manufacturer of hand held power tools.

Blood flow control in the brain

Blood flow to the brain is tightly controlled by mechanisms that constrict and dilate small blood vessels in response to changes in blood pressure, the level of neuronal activity or other challenges. We aim to improve understanding of this control system and find robust methods to detect when this brain-protective mechanism is impaired.

Member of the Faculty Ethics Committee

Member of Editorial Advisory Board: Biomedical Signal Processing and Control

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Book Chapters



Admissions Tutor for the MSc in Biomedical Engineering

Module lead for:

Introduction to Biomedical Engineering – ISVR6144

Biomedical Applications of Signal and Image Processing – ISVR6138

Tutor in:

Audio and Signal Processing – ISVR2041

Electrical and Electronic Systems – FEEG1004

Prof David M Simpson
Engineering, University of Southampton, Highfield, Southampton. SO17 1BJ United Kingdom

Room Number : 13/4097

Facsimile: (023) 8059 3190

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