Biomedical Engineering Reference
In-Depth Information
Chapter 7
Sensor Circuits
7.1 Introduction
Signal processing is defined as improving the quality of the signal at the output of
a measurement system, and very particular is paid to attenuate any noise in the
measurement of biosignals that have not been eliminated by the measurement
system of the sensor/transducer. Also note that signal processing carries out other
functions related to noise, and the exact procedures that are applied depend on the
nature of the raw output signal from a measurement transducer. Various types of
methodologies including signal filtering, signal amplification, signal attenuation,
signal linearization, and bias removal are applied according to the form of cor-
rection required in the raw biosignal.
Usually, signal processing is done by analog techniques using various types of
electronic circuits. On the other hand, the ready availability of digital computers
has meant that signal processing has increasingly been carried out digitally, using
software modules to condition the input measurement data.
Digital signal processing is basically more precise than analog techniques, but
this advantage is reduced if measurements come from analog sensors and trans-
ducers, because an analog-to-digital conversion stage is necessary before the
digital processing can be applied. Also, note that analog processing is faster
compared to the speed of digital signal processing. So here we discuss analog
processing first, then digital processing as well, because analog processing is
required along with digital signal processing.
7.2 Analog Conditioning Circuits
The biomedical sensor/e-nose sensor signal is not suitable to be used as an input
that is normally sent to a data acquisition system. The original signal might not be
suitable because the voltage level is too low, there is some inherent high frequency
noise on the signal, or a transformation of the signal must occur before being time
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