12 Biomedical Engineering Fundamentals
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of the EEG signal. These frequency components are also used in the diagnostics of
various diseases and disorders.
The analysis of EEG signals is also possible with frequency measure which is
known as spectral edge frequency (SEF). This measure plays a significant role in
the analysis of depth of anesthesia. It is found that a decrease in the value of SEF
corresponds to a deeper level of anesthesia [30].
Similarly, median peak frequency (MPF) is another frequency measure in which
frequency situated at 50% of the energy level is considered. The MPF gives the highfrequency contribution present in the frequency spectrum. This measure is also used
in the analysis and classification of anesthesia depth [30].
In the frequency-domain analysis of ECG signal, the QRS complex is well
localized in the high-frequency region. On the other hand, the low-frequency
components are mainly due to P and T waves. The ST segment in the ECG signal
mostly contains the low-frequency component. The frequency contents in a normal
ECG signal and the deviating ECG signal have a significant difference because
the normal heart rate is in the range of 60–100 beats per minute, whereas the
fibrillation can exceed the range of 200 beats per minute. The depolarization and
repolarization ramps in ECG signal are also changed under diseased conditions. This
requires a much wider frequency bandwidth to identify different phenomena. The
minor deviation of higher frequency in ECG signal creates a much larger number
of harmonics which describe the frequency-domain features in the ECG signal.
Therefore, a frequency span of 0–100 Hz usually represents normal ECG signal,
whereas arrhythmias may require a high-frequency analysis up to 200 Hz. However,
the high-frequency spectra will also be dominated by noise and it may not contribute
any additional information [30].
A disease named as sinus tachycardia is also often detected in the frequency
domain. A sinus tachycardia is detected when a sinus rhythm higher than 100 beats
per minute appears. This similar condition may also occur during a physiological
response to physical exercise or physical stress but it may lead to congestive heart
failure in diseased cases. The case of sinus arrhythmia is also possible when the
longest PP or RR intervals exceed the shortest interval by 0.16 s. This condition is
frequent in teenage groups who have never suffered a heart disease [30].
The detection of fetal heart diseases using ECG signal during pregnancy is
another area where the frequency-domain analysis plays a vital role. The ECG
signals recorded from the leads placed on the abdomen of the mother are used to
monitor the fetal heart diseases. The P and T waves obtained with the maternal ECG
signal can easily be recognized in most cases. The maternal heart rate is usually
lower than the fetal heart rate which is distinct from the mother’s and the baby’s
ECG signals using filters designed in the frequency-domain.
The frequency-domain analysis of EMG signal leads to the fact that the frequency
spectrum is mostly in the higher frequencies during fatigue, whereas the power
spectrum is shifted toward lower frequencies after fatigue. This frequency shift
indicates the muscle status such as rest and contraction states [30]. There are
many features which are used for the frequency-domain analysis of EMG signals.
The mean frequency (MF) measure is able to denote muscle fatigue during cyclic
597
of the EEG signal. These frequency components are also used in the diagnostics of
various diseases and disorders.
The analysis of EEG signals is also possible with frequency measure which is
known as spectral edge frequency (SEF). This measure plays a significant role in
the analysis of depth of anesthesia. It is found that a decrease in the value of SEF
corresponds to a deeper level of anesthesia [30].
Similarly, median peak frequency (MPF) is another frequency measure in which
frequency situated at 50% of the energy level is considered. The MPF gives the highfrequency contribution present in the frequency spectrum. This measure is also used
in the analysis and classification of anesthesia depth [30].
In the frequency-domain analysis of ECG signal, the QRS complex is well
localized in the high-frequency region. On the other hand, the low-frequency
components are mainly due to P and T waves. The ST segment in the ECG signal
mostly contains the low-frequency component. The frequency contents in a normal
ECG signal and the deviating ECG signal have a significant difference because
the normal heart rate is in the range of 60–100 beats per minute, whereas the
fibrillation can exceed the range of 200 beats per minute. The depolarization and
repolarization ramps in ECG signal are also changed under diseased conditions. This
requires a much wider frequency bandwidth to identify different phenomena. The
minor deviation of higher frequency in ECG signal creates a much larger number
of harmonics which describe the frequency-domain features in the ECG signal.
Therefore, a frequency span of 0–100 Hz usually represents normal ECG signal,
whereas arrhythmias may require a high-frequency analysis up to 200 Hz. However,
the high-frequency spectra will also be dominated by noise and it may not contribute
any additional information [30].
A disease named as sinus tachycardia is also often detected in the frequency
domain. A sinus tachycardia is detected when a sinus rhythm higher than 100 beats
per minute appears. This similar condition may also occur during a physiological
response to physical exercise or physical stress but it may lead to congestive heart
failure in diseased cases. The case of sinus arrhythmia is also possible when the
longest PP or RR intervals exceed the shortest interval by 0.16 s. This condition is
frequent in teenage groups who have never suffered a heart disease [30].
The detection of fetal heart diseases using ECG signal during pregnancy is
another area where the frequency-domain analysis plays a vital role. The ECG
signals recorded from the leads placed on the abdomen of the mother are used to
monitor the fetal heart diseases. The P and T waves obtained with the maternal ECG
signal can easily be recognized in most cases. The maternal heart rate is usually
lower than the fetal heart rate which is distinct from the mother’s and the baby’s
ECG signals using filters designed in the frequency-domain.
The frequency-domain analysis of EMG signal leads to the fact that the frequency
spectrum is mostly in the higher frequencies during fatigue, whereas the power
spectrum is shifted toward lower frequencies after fatigue. This frequency shift
indicates the muscle status such as rest and contraction states [30]. There are
many features which are used for the frequency-domain analysis of EMG signals.
The mean frequency (MF) measure is able to denote muscle fatigue during cyclic