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In the present work, gender differences in sleep spindle topography were examined in 40 subjects. Their median age was 32 years (range 22–49 years). Spindles were detected from 3,306,060 s of visually scored stage 2 sleep EEG by a previously validated automatic fuzzy detector at 1-second intervals. A total of 271,168 spindles were found from the six EEG channels analyzed. Females showed a significantly higher percentage of spindles in the left frontal channel than males (Fp1-A2; p = 0.026). To confirm that this difference was gender and not age related, the subjects were divided into two age groups. No significant differences in spindle activity of the frontal channels were found between the groups. However, the interindividual spindle variability seemed to be at least as large as that stemming from gender.Copyright © 2002 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Objective: The objective of the present work was to develop and compare methods for automatic detection of bilateral sleep spindles. Methods and materials: All-night sleep electroencephalographic (EEG) recordings of 12 healthy subjects with a median age of 40 years were studied. The data contained 6043 visually scored bilateral spindles occurring in frontopolar or central brain location. In the present work a new sigma index for spindle detection was developed, based on the fast Fourier transform (FFT) spectrum, aiming at approximating our previous fuzzy spindle detector. The sigma index was complemented with spindle amplitude analysis, based on finite impulse response (FIR) filtering, to form of a combination detector of bilateral spindles. In this combination detector, the spindle amplitude distribution of each recording was estimated and used to tune two different amplitude thresholds. This combination detector was compared to bilaterally extracted sigma indexes and fuzzy detections, which aim to be independent of absolute spindle amplitudes. As a fourth method a fixed spindle amplitude detector was included. Results: The combination detector provided the best overall performance; in S2 sleep a 70% true positive rate was reached with a specificity of 98.6%, and a false-positive rate of 32%. The bilateral sigma indexes provided the second best results, followed by fuzzy detector, while the fixed amplitude detector provided the poorest results so that in S2 sleep a 70% true positive rate was reached with a specificity of 97.7% and false-positive rate of 46%. The spindle amplitude distributions automatically determined for each recording by the combination detector were compared to amplitudes of visually scored spindles and they proved to correspond well. Inter-hemispheric amplitude variation of visually scored bilateral spindles is also presented. Conclusion: Flexibility is beneficial in the detection of bilateral spindles. The present work advances automated spindle detection and increases the knowledge of bilateral sleep spindle characteristics. [Copyright &y& Elsevier]

Abstract: Accurate analysis of EEG sleep spindle frequency is challenging. The frequency content of true sleep spindles is not known. Therefore, simulated spindle activity was studied in the present work. Five types of simulated test signals were designed, all containing a dominant spindle represented by a 13-Hz sine wave as such or with a waxing and waning pattern accompanied by a secondary spindle activity in three test signals. Background EEG was included in four test signals, modeled either as small additional sinusoids across the spindle frequency range or as filtered Gaussian noise segments. The purpose of this study was to investigate how accurately the dominant spindle frequency of 13Hz could be resolved with different methods in the presence of the interfering waveforms. A matching pursuit (MP) based approach, discrete Fourier transform (DFT) with Hanning windowing with and without zero padding, Hankel total least squares (HTLS) and wavelet methods were compared in the analyses. MP method provided best overall performance, followed closely by DFT with zero padding. Comparative studies like this are important to decide the method of choice in clinical sleep EEG analysis. [Copyright &y& Elsevier]

Abstract: Sleep apnea syndrome is known to disturb sleep. The purpose of the present work was to study spindle frequency in apnea patients. All-night sleep EEG recordings of 15 apnea patients and 15 control subjects with median ages of 47 and 46 years, respectively, were studied. A previously presented and validated multi-channel spindle analysis method was applied for automatic detection and frequency analysis of bilateral frontopolar and central spindles. Bilateral frontopolar spindles of apnea patients were found to show lower frequencies on the left hemisphere than on the right. Such an inter-hemispheric spindle frequency difference in apnea patients is a novel finding. It could be that the hypoxias and hypercapnias caused by apneic episodes result in local disruption in the regulation of sleep in the frontal lobes. [Copyright &y& Elsevier]

A fully automatic method to quantify sleep depth during the night was developed in the present work. The method was tested using 20 all-night recordings from 10 healthy control subjects and 10 sleep apnea patients. The results showed statistically significant differences in sleep depth between control subjects and sleep apnea patients. The overall sleep was lighter in apnea patients than in healthy control subjects, most likely indicating a disturbed sleep caused by apneas. The automatic parameters presented provide a method to quantify the light sleep and could in the future possibly be used in clinical sleep studies and follow-up of treatment. [Copyright &y& Elsevier]