The University of Southampton
Courses

# ELEC2226 Biomedical Control

## Module Overview

To develop knowledge of the analysis of linear continuous-time systems. To introduce the basic analysis and design tools for electronic system control and its application in biomedical purposes.

### Aims and Objectives

#### Module Aims

The module aims at providing students with tools for the analysis of linear continuous-time systems, and to introduce basic analysis and design tools for electronic system control in view of their application in biomedical purposes.

#### Learning Outcomes

##### Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• The principles of control theory.
• The techniques used to design and analyse the performance of control systems.
• Application of hardware, signal processing techniques and control systems design in biomedical technology.
• Research undertaken in biomedical rehabilitation and assistive technology.
##### Transferable and Generic Skills

Having successfully completed this module you will be able to:

• Use the control point of view to analyse biomedical problems.
##### Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• Apply time and frequency domain techniques for the analysis of linear systems of any order.
• Analyse and design simple linear control systems.
• Use MATLAB as a design and simulation tool.
• Program control system design and analysis problems in MATLAB.
• Engage proficiently with the more advanced signal processing and control courses.
• Understand how control systems and signal processing techniques are applied in biomedical technology.
• Appreciate the latest research methods being undertaken in biomedical rehabilitation and assistive technology.

### Syllabus

Control (26 lectures): - Recap of the Laplace Transform and its properties, including initial and final value theorem - Differential equations and transfer functions - Characteristic equation - Block diagram notation - Use of Matlab and other CAD tools. - Feedback Control Systems - Open loop v closed loop - Stability - Sensitivity - Disturbance rejection - Transient response - Steady state error - Root Locus Analysis - Bode Plots - Gain and Phase Margin, Bandwidth - Estimation of system transfer functions - Stability in the Frequency Domain - Nyquist Stability Criterion - Gain and Phase Margin - Controller Design - Common control methodologies - PI, PD and PID, Pole placement, Pole-zero cancellation - Compensators, Phase Lead and Lead-Lag - Benefits and Disadvantages - the need for other control strategies Application of control theory and signal processing in biomedical engineering (10 lectures): - Overview of control theory and signal processing techniques within biomedical applications. - Overview of current state of the art control techniques for rehabilitation and assistive technology. - Fundamentals of biomedical electronics and signal processing, to include discussion of: Electromyography (EMG) Electroencephalography (EEG) Biomechanical kinematic and kinetic signals Functional Electrical Stimulation (FES) with special reference to their application in control systems design for rehabilitation and assistive technology. - Research case study: application of control techniques in lower limb orthoses (e.g. for drop foot) - Research case study: application of control techniques in upper limb stroke rehabilitation, and in Parkinsonian/Multiple Sclerosis tremor suppression.

### Learning and Teaching

TypeHours
Tutorial12
Specialist Laboratory9
Lecture36
Total study time57

T. F. Quatieri. (2001). Discrete-Time Speech Signal Processing: Principles and Practice.

Soderberg (eds. 1992). Selected Topics in Surface Electromyography for Use in the Occupational Setting: Expert Perspectives NIOSH (document 91-100).

R. C. Dorf and R. H. Bishop. (2005). Modern Control Systems.

D. A. Winter (1990). Biomechanical and Motor Control of Human Movement. (2nd ed.).

G. Clifford, F. Azuaje, F. and P. McSharry, P. (eds.) (2006). Advanced Methods and Tools for ECG Data Analysis.

B. M. Nigg, and W. Herzog. (1994). Biomechanics of the Musculo-skeletal System.

R. Shadmehr and S. P. Wise (2004). The Computational Neurobiology of Reaching and Pointing: A Foundation for Motor Learning (Computational Neuroscience).

R. Rangayyan (2002).  Biomedical Signal Analysis: A Case-Study Approach.

### Assessment

#### Summative

MethodPercentage contribution
Exam  (2 hours) 75%
Specialist Lab 15%
Tutorial questions 10%

#### Referral

MethodPercentage contribution
Exam 100%

#### Repeat Information

Repeat type: Internal & External