Clinical Applications of Spectral Analysis Winni Hofman, PhD University of Amsterdam Medcare...
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Transcript of Clinical Applications of Spectral Analysis Winni Hofman, PhD University of Amsterdam Medcare...
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