Clinical Applications ofSpectral Analysis

Winni Hofman, PhD

University of Amsterdam

Medcare Amsterdam

• Introduction of spectrum calculations

• Spectra and sleep staging• Spectral analysis for differentiating various

night patterns• Spectral analysis and arousals• Frequency analysis of snoring

Outline

4 Examples of applications of Spectral Analysis

Spectral Analysis is a tool to:• Quantify the frequency content of

signals, like EEG or snore signal, for further calculations

• Help you with your manual sleep stage scoring

• Detect problems in the recording, e.g. 60 Hz noise

Frequency content of a signal

EEG frequency bands:Beta - > 12 Hz

Sigma - 12 – 14 Hz

Alpha - 8 – 12 Hz

Theta - 4 – 7 Hz

Delta - 0.5 – 4 Hz

Frequency content of a signalR&K definition of sleep EEG:

• Stage 1: Relatively low voltage, mixed frequency EEG in 2 – 7 cps range without rapid eye movements

• Stage 2: 12-14 cps sleep spindles and K complexes on a background of relatively low voltage, mixed frequency EEG

• Stage 3: 20%-50% of high amplitude, slow wave activity

• Etc…….

Complex signals

• Signals like the EEG are complex signals, existing of many superimposed waveforms with:– Various frequencies– Various amplitudes– Various phase relationships

Describing frequency content of a signal

Sine waves are used for description because they can be defined exactly by their:

– Frequency– Amplitude– Phase

Sine wave

Cosine wave

1 cycle

Spectral Analysis describes a signal:

• By calculating the contributions of the various superimposed frequency components

• Shows these contributions in a Power Spectrum plot

Spectral analysis and Sleep Stages

• Differences in frequencies between sleep stages are visible in a Power Spectrum

R&K definition of stage Wake:

• Wake: alpha activity and/or low voltage, mixed frequency activity

WakeAlpha peak

R&K definition of stage 2:

• Stage 2: 12-14 cps sleep spindles and K complexes on a background of relatively low voltage, mixed frequency EEG

Stage 2

Theta peak

Alpha peak

R&K definition of stage 4:

• Stage 4: > 50% of high amplitude, slow wave activity

Stage 4

Delta peak

R&K definition of stage REM:

• Stage REM: a relatively low voltage, mixed frequency EEG (in conjunction with episodic REMs and low amplitude EMG)

Stage REM

Theta peak

Delta waves with superimposed alpha

Power spectrum S4 with alpha

Spectral colour plot

• Shows changes in frequency content of a signal over longer time period (for example a whole night)

– Colour: power– Y-axis: frequency– X-axis: time

• Each point in time in the Spectral colour plot represents a power spectrum of a 30 sec epoch

Spectral analysis and various sleep patterns

• Changes over time in the distribution of the various frequencies follows changes in sleep pattern:– Rhythmicity in delta sleep– REM sleep periodicity– Periods of wakefullness

Delta activity

Low voltage mixed frequency in REM sleep 50 Hz notch

filter

Transition to stage Wake

Delta

Alpha

Normal sleep pattern

Insomnia sleep pattern

CPAP titration

Sleep pattern during CPAP titration

Heinzer et al., Chest 2002

Spectral analysis and arousal(Black et al., Am.J.Respir.Crit.CareMed., 2000)

• Apnea can be followed by arousal

• Micro-arousals are often not visually recognized as arousals according to ASDA criteria

• Spectral analysis can give more insight into EEG alterations occurring after an apnea

Arousal and Eso

Black et al., 20.., Chest

Arousal and Eso

Black et al., 2000, Am.J.Respir.Crit.CareMed.

Arousal and Eso

Black et al., 2000, Am.J.Respir.Crit.CareMed.

Arousal and Eso

Black et al., 2000, Am.J.Respir.Crit.CareMed.

Spectral analysis of snore sounds

• Differences in frequency content of snoring sounds might be clinically important (high versus low frequency)

Snores with high frequency sound vibrations

Snores with low frequency sound vibrations

High frequency snore sound vibrations

Low frequency snore sound vibrations