Computerized Data Acquisition and Analysis for the Life Sciences: A Hands-on Guide

247 Pages·2001·6.74 MB·English

by  Simon S. Young

Computerized Data Acquisition and Analysis for
the Life Sciences
This book offers an excellent introduction to computer-based data acquisi-
tion and analysis and will be especially valuable to those with little or no
engineering background. In an informal, easy-to-read style, it guides
researchers through the basics of data acquisition systems, explains the
important concepts underlying sampled data, and gives numerous examples
of how to analyse the recorded information. While aimed at researchers in
the life sciences, the topics covered are general and will be valuable to any-
one interested in learning to use data acquisition systems.
A variety of high-quality hardware and software is now available to
researchers, and computerized data acquisition systems are often the princi-
pal method of recording experimental results. Yet for the non-engineer, set-
ting up these systems can be a difficult task. This book takes the reader
through the process step by step, from the type of input to be used (single-
ended or differential, unipolar or bipolar) through to the sampling rate and
the size of the resultant data files. It explains how to set up preamplifiers to
get the best results, and covers the main types of transducer encountered in
life-science work. It then discusses how to obtain useful information from
the large amounts of data recorded. The principles can be applied to the
collection of data from respiratory apparatus, intracellular and extracellular
electrodes, electrocardiograms, behavioural-science experiments, kine-
matics, and a host of other situations. Many illustrations and worked ex-
amples accompany the text, unfamiliar terms are explained, and the
mathematics are kept as simple as possible.
This book is an invaluable tool for the non-engineer who is collect-
ing and analysing experimental data using data acquisition systems.
Researchers, graduate students, and technicians will find it an up-to-date,
accessible, and indispensable guide for setting up their equipment and get-
ting the most out of their experimental data.
Simon S. Young is a Senior Principal Scientist at the Schering-Plough
Research Institute in Kenilworth, New Jersey.

Computerized Data Acquisition
and Analysis for the Life Sciences
A Hands-on Guide
SIMON S. YOUNG
Schering-Plough Research Institute
CAMBRIDGE
UNIVERSITY PRESS
PUBLISHED BY THE PRESS SYNDICATE OF THE UNIVERSITY OF CAMBRIDGE
The Pitt Building, Trumpington Street, Cambridge, United Kingdom
CAMBRIDGE UNIVERSITY PRESS
The Edinburgh Building, Cambridge CB2 2RU, UK
40 West 20th Street, New York, NY 10011-4211, USA
10 Stamford Road, Oakleigh, VIC 3166, Australia
Ruiz de Alarcon 13, 28014 Madrid, Spain
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http://www.cambridge.org
© Cambridge University Press 2001
This book is in copyright. Subject to statutory exception
and to the provisions of relevant collective licensing agreements,
no reproduction of any part may take place without
the written permission of Cambridge University Press.
First published 2001
Printed in the United States of America
Typeface Melior 10/13.5 pt System 3B2 [KW]
A catalogue record for this book is available from
the British Library
Library of Congress Cataloging-in-Publication Data
Young, Simon S., 1958-
Computerized data acquisition and analysis for the life sciences: a hands-on guide/
Simon S. Young
p. cm.
Includes bibliographical references
ISBN 0-521-56281-3 (hardback)
ISBN 0-521-56570-7 (paperback)
1. Life sciences - Data processing. 2. Automatic data collection systems. I. Title.
QH324.2.Y68 2001
570'.285 - dc21 00-045436
ISBN 0 521 56281 3 hardback
ISBN 0 521 56570 7 paperback
Contents
Preface poge ix
1 The Bare Essentials l
Define the Variables to be Measured 1
Convert the Physiological Effect to a Voltage 1
Scale the Signal 2
Select a Unipolar or Bipolar Input Range 2
Choose Single-Ended or Differential Inputs 2
Choose the Sampling Rate and Anti-Aliasing Filters 3
Size of Data Files 3
Calibration 4
Data Analysis 6
2 How a Data Acquisition System Works 7
Analogue-to-Digital Converter 9
Range 13
Unipolar and Bipolar Mode 16
Multiplexing 17
Sample-and-Hold Circuit 19
Single-Ended and Differential Inputs 20
Computers 24
Software 24
Data Format and Storage Space 28
Digital-to-Analogue Converters 34
Digital Input and Output 37
Counter/Timer Inputs 43
vi Contents
3 Important Concepts 46
Sampling Rate 46
Decibels 55
Types of Low-Pass Filters 64
Oversampling 66
Preventing Aliasing 67
Finding the Maximum Frequency Present in a Signal 68
Digital-to-Analogue Conversion 80
4 Connecting to the Real World with Transducers 82
Temperature 83
Strain 87
Force 92
Acceleration 94
Displacement and Rotation 95
Pressure 98
Light 100
Isolation Amplifiers 104
Nonlinear Sensors and Linearization 105
5 Data Manipulation 109
Data Format 111
Statistics 111
Peak, Trough, and Zero-Crossing Detection 116
Resampling and Interpolation 123
Curve Fitting 125
Filters 132
Spectral Analysis and the Fast Fourier Transform 143
Integration 160
Differentiation 162
Correlation 164
Chaos and Nonlinear Analysis 166
Removing 50/60 Hz Interference 169
Two- and Three-Dimensional Signal Analysis 172
6 Examples 178
ECG Signal 178
Cardiac Output by Indicator Dilution 186
Spectral Edge from EEG Data 191
Nonlinear Curve Fitting to a Dose-Response Curve 194
Contents vii
Heart Rate Variability 197
Equine Hoof Anatomy 202
Neurophysiological Recording 206
Appendix Suppliers of Data Acquisition/Analysis Hardware
and Software and Electronic Components 223
Notes 229
References 233
Index 235

Preface
There has been a small revolution in data acquisition systems for scientific use in
recent years. It was not so long ago that hardware and processing power were
expensive and software nonexistent. Every program had to be written from scratch
in a low-level language and, if you did not want your program to take all night to
run, it usually included large chunks of assembler code as well. Nowadays there
are many data acquisition systems to choose from, with good hardware and vastly
improved software running on fast personal computers. Many such systems are
purchased with the aim of using them as the primary method of recording experi-
mental data in the laboratory. Unfortunately, it is not always as easy to set up the
system as the manufacturers would have us believe and getting the machine to do
what you want it to do with your apparatus can be a daunting and frustrating task.
This book was written to help people collect and analyse experimental data using
digital data acquisition systems and is particularly for those whose field of exper-
tise is not engineering or computing. The book explains how data acquisition
systems work, how to set them up to obtain the best performance and how to
process the data. Terms which may be unfamiliar are explained so that manufac-
turer's specifications and literature become clearer and the differences between
systems can be appreciated. The topics covered in the book are general but the
examples are slanted towards the life sciences because this is often the discipline
in which people have the greatest trouble setting up data acquisition systems. For
people with an engineering background some of the material will be familiar but
there are still useful tips and short cuts.
Program listings are not included in the book. There are some practical
problems associated with publishing programs: they have to be cross-platform
and written in several languages if they are to be useful to everyone. But the
main reason is that I would strongly urge you to forget about low-level coding
altogether. Buy a high-level language designed for signal processing (LabView,
ix