Toward Sensor to Reproduce Human Sense - The Electronic Nose Artificial Olfaction Technology - page 130

All living things, from cells to organism, deliver signals of biological origin.
Such signals can be electrical, mechanical, or chemical. All such signals can be of
interest for diagnosis, for patient monitoring and biomedical research. The main
task of processing biomedical signals is to filter out the signal of interest from the
noisy background and to reduce the redundant data stream to only a few, but
relevant parameters.
Signal analysis is a technique which includes computer algorithms to analyze
and transform the signal in an effort to create natural, meaningful, and alternate
representations of the useful information contained in the signal while minimize
the effects of noise. In most cases signal processing is a multi-step process that
involves both numerical and graphical methods.
Biomedical signal analysis is the innovative applications of biomedical signals
through various creative integrations of the method and biomedical knowledge.
Various applications ranges are from the construction of artificial limbs and aids
for the disabled to the development of sophisticated medical monitoring systems
that can operate in a noninvasive manner to give real time views of the workings of
the human body. There are a number of medical systems in common use. These
includes ultrasound, electrocardiography (ECG) and plythesmography are widely
used for many purposes.
Biomedical signals are study of physiological activities of organisms, series
from gene to protein sequences, to neural and cardiac rhythms, to tissue and organ
images. Biomedical signal processing aims at extracting significant information
from biomedical signals. With the help of biomedical signal processing, biologists
can discover new biology and physicians can monitor distinct illnesses [ 17 ].
A fundamental method for noise cancelation analyzes the signal spectra and
suppresses undesired frequency components. Another analysis framework derives
from statistical signal processing.
The processing of biomedical signals usually consists of at least four stages:
• Measurement or observation, that is, signals acquisition.
• Transformation and reduction of the signals.
• Computation of signal parameters that are diagnostically significant, and
• Interpretation or classification of the signals.
Bio-signal processing stages are shown in Fig. 5.7 . Basic signal processing
schematic is also shown in Fig. 5.8 .
5.9 Classification of Bio-signals
Biosignal may be classified in many ways according to:
• Source or physical nature: in this type classification respects the basic physical
characteristics of the considered process.