SIGNAL CONDITIONING, DATA ACQUISITION, AND SPECTRAL ANALYSIS - Design and Development of Medical Electronic Instrumentation - page 233

TABLE 5.4 Some Center Frequencies and Frequency
Deviations Specified by IRIG to Yield Constant-Bandwidth
Channels for Acquisition through FM Subcarriers
Frequency Deviation and Nominal
Frequency Response per Channel

2 kHz 4 kHz 8 kHz 16 kHz 32 kHz

400 Hz 800 Hz 1.6 kHz 3.2 kHz 6.4 kHz

Channel Center Frequency (kHz)

8 16 32 64 128

16 32 64 128 256

24 48 96 192 384

32 64 128 256 512

TABLE 5.5 Many Channels of Differing Bandwidth Can Be Accommodated by Selecting Channel Bandwidths
Proportional to Their Carrier Frequencies a

IRIG Proportional Center Lower Deviation Upper Deviation Channel's Nominal

Bandwidth Channel Frequency Limit Limit Bandwidth Frequency Response

7.5% Deviation Channels

1 400 370 430 60 6

2 560 518 602 84 8

3 730 675 785 110 11

4 960 888 1,032 144 14

5 1,300 1,202 1,398 196 20

6 1,700 1,572 1,828 256 25

7 2,300 2,127 2,473 346 35

8 3,000 2,775 3,225 450 45

9 3,900 3,607 4,193 586 59

10 5,400 4,995 5,805 810 81

11 7,350 6,799 7,901 1,102 110

12 10,500 9,712 11,288 1,576 160

13 14,500 13,412 15,588 2,176 220

a These IRIG channels are useful for acquiring multiple physiological signals with different bandwidth requirements. For example, the sub-
ject's skin conductance signal fits well within the 11-Hz bandwidth of channel 3, the 45-Hz bandwidth of channel 8 could accommodate an
EEG channel, and a three-lead wideband ECG can be acquired through channels 11, 12, and 13.

SPECTRAL ANALYSIS

The analysis of a signal based on its frequency content is commonly referred to as spec-
tral analysis . Because of the rhythmic nature of practically every phenomenon in a living
body, frequency-domain analysis is one of the most powerful tools in the examination of
physiological signals. The mathematical basis for this operation, the Fourier transform, has
been known for many years, but it was the introduction of the fast Fourier transform (FFT)
algorithm that made spectral analysis a practical reality. Implementing the FFT in personal
computers and embedded DSP systems has allowed e

cient and economical application
of Fourier techniques to a wide variety of measurement and analysis tasks. Moreover,
because the FFT has been found to be so valuable in applications such as medical signal
processing, radar, and telecommunications, DSP chips are often designed to implement it
with the greatest e ciency.