Bob Kemp

A simple format for exchange of digitized polygraphic recordings

A simple digital format supporting the technical aspects of exchange and storage of polygraphic signals has been specified. Implementation of the format is simple and independent of hard- or software environments. It allows for any local montages, transducers, prefiltering, sampling frequencies, etc. At present, 7 laboratories in various countries have used the format for exchanging sleep-wake recordings. These exchanges have made it possible to create a common database of sleep records, to compare the analysis algorithms local to the various laboratories to each other by applying these algorithms to identical signals, and to set up a computer-aided interlaboratory evaluation of manual and automatic analysis methods.

An E-Health Solution for Automatic Sleep Classification according to Rechtschaffen and Kales: Validation Study of the Somnolyzer 24 × 7 Utilizing the Siesta Database

To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficiently large number of controls and patients of all adult age ranges. The present paper describes the development and optimization of an automatic classification system that is based on one central EEG channel, two EOG channels and one chin EMG channel. It adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system (Somnolyzer 24 × 7™) consists of a raw data quality check, a feature extraction algorithm (density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, SEMs and REMs), a feature matrix plausibility check, a classifier designed as an expert system, a rule-based smoothing procedure for the start and the end of stages REM, and finally a statistical comparison to age- and sex-matched normal healthy controls (Siesta Spot Report™). The expert system considers different prior probabilities of stage changes depending on the preceding sleep stage, the occurrence of a movement arousal and the position of the epoch within the NREM/REM sleep cycles. Moreover, results obtained with and without using the chin EMG signal are combined. The Siesta polysomnographic database (590 recordings in both normal healthy subjects aged 20–95 years and patients suffering from organic or nonorganic sleep disorders) was split into two halves, which were randomly assigned to a training and a validation set, respectively. The final validation revealed an overall epoch-by-epoch agreement of 80% (Cohen’s kappa: 0.72) between the Somnolyzer 24 × 7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen’s kappa: 0.68) between two human experts scoring the same dataset. Two Somnolyzer 24 × 7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen’s kappa: 0.991), which confirmed that the variability induced by the quality control procedure, whereby approximately 1% of the epochs (in 9.5% of the recordings) are changed, can definitely be neglected. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24 × 7 and demonstrated its applicability in clinical routine and sleep studies.

European data format 'plus' (EDF+), an EDF alike standard format for the exchange of physiological data.

The European data format (EDF) is a widely accepted standard for exchange of electroencephalogram and polysomnogram data between different equipment and labs. But it hardly accommodates other investigations. EDF+ is a more flexible but still simple format which is compatible to EDF except that an EDF+ file may contain interrupted recordings. Also, EDF+ supports time-stamped annotations for the storage of events such as text annotations, stimuli, averaged signals, electrocardiogram parameters, apnoeas and so on. When compared to EDF, EDF+ can not only store annotations but also electromyography, evoked potentials, electroneurography, electrocardiography and many more types of investigations. Further improvements over EDF include the use of standard electrode names. EDF+ is so much like EDF that existing EDF viewers still display the signals in EDF+ files. Software development is limited mainly to implementing the annotations. EDF+ offers a format for a wide range of neurophysiological investigations which can become a standard within a few years.

The SIESTA project polygraphic and clinical database

The SIESTA project had two major goals: developing new tools for analyzing computer-based sleep recordings and creating a reference database for sleep-related features. Basically, both goals have been reached, although validation and fine tuning of the sleep analyzer is still on-going. Investigations on the Web interface will be finished soon and a documentation of the database (including a CD-ROM with all test forms and all clinical, psychometric and actigraphic data as well as all R&K-scorings) will be published. Besides its scientific impact, the SIESTA project also emphasizes two other important aspects: the need of national and international cooperation between different experts and disciplines and the importance of standardized methods in scientific and clinical research.

Interrater reliability between scorers from eight European sleep laboratories in subjects with different sleep disorders.

Interrater variability of sleep stage scorings is a well‐known phenomenon. The SIESTA project offered the opportunity to analyse interrater reliability (IRR) between experienced scorers from eight European sleep laboratories within a large sample of patients with different (sleep) disorders: depression, general anxiety disorder with and without non‐organic insomnia, Parkinsons disease, period limb movements in sleep and sleep apnoea. The results were based on 196 recordings from 98 patients (73 males: 52.3 ± 12.1 years and 25 females: 49.5 ± 11.9 years) for which two independent expert scorings from two different laboratories were available. Cohens κ was used to evaluate the IRR on the basis of epochs and intraclass correlation was used to analyse the agreement on quantitative sleep parameters. The overall level of agreement when five different stages were distinguished was κ = 0.6816 (76.8%), which in terms of κ reflects a ‘substantial’ agreement ( Landis and Koch, 1977 ). For different groups of patients κ values varied from 0.6138 (Parkinsons disease) to 0.8176 (generalized anxiety disorder). With regard to (sleep) stages, the IRR was highest for rapid eye movement (REM), followed by Wake, slow‐wave sleep (SWS), non‐rapid eye movement 2 (NREM2) and NREM1. The results of regression analysis showed that age and sex only had a statistically significant effect on κ when the (sleep) stages are considered separately. For NREM2 and SWS a statistically significant decrease of IRR with age has been observed and the IRR for SWS was lower for males than for females. These variations of IRR most probably reflect changes of the sleep electroencephalography (EEG) with age and gender.

Acquisition of biomedical signals databases

Aspects to consider when building a database are presented. The work is based on experiences from the SIESTA project which identified sleep disorders.

Ambulatory Monitoring of Sleep-Wakefulness Patterns in Healthy Elderly Males and Females (>88 Years): The “Senieur” Protocol

The study was designed to investigate sleep‐wake patterns in healthy elderly men and women (>88 years) using ambulatory recording techniques.

A model-based detector of vertex waves and K complexes in sleep electroencephalogram

A model of sleep phasic events such as vertex waves, K complexes, delta waves and sleep spindles is proposed. It consists of feedback loops that are driven by white noise (simulating tonic delta and sigma activity) and by isolated random impulses, simulating vertex waves or K complexes, depending on the background tonic activity. A model-based method for the detection of sleep phasic events was implemented in a personal computer. Its performance was investigated using simulated and real whole-night EEG signals. The method was able to detect K complexes and vertex waves in a reliable way in spite of their variable shapes and in the presence of a variety of background activities. The detector appears to have superior performance to those so far reported in the literature. The performance of the detector was also compared to that of an electroencephalographer using normal sleep EEG records of 8 h duration from 6 subjects. The performance was satisfactory both in terms of accuracy and reliability. The problem of detecting K complexes in stages 3 and 4 of sleep is discussed.

Standards for biomedical signal databases

This article presents some requirements imposed on data format specifications derived from different biosignal recording environments. This is followed by a review of four particularly interesting data formats and some notes about other specifications. Finally, the merits of different formats are discussed and some views about future developments are given.

A pharmacodynamic Markov mixed‐effect model for the effect of temazepam on sleep

A hypnogram shows how sleep travels through its various stages in the course of a night. The sleep stage changes can be quantified to study sedative drug effects.