Automatic sleep staging: from young adults to elderly patients using multi-class support vector machine

Aging is a process that is inevitable, and makes our body vulnerable to age-related diseases. Age is the most consistent factor affecting the sleep structure. Therefore, new automatic sleep staging methods, to be used in both of young and elderly patients, are needed. This study proposes an automatic sleep stage detector, which can separate wakefulness, rapid-eye-movement (REM) sleep and non-REM (NREM) sleep using only EEG and EOG. Most sleep events, which define the sleep stages, are reduced with age. This is addressed by focusing on the amplitude of the clinical EEG bands, and not the affected sleep events. The age-related influences are then reduced by robust subject-specific scaling. The classification of the three sleep stages are achieved by a multi-class support vector machine using the one-versus-rest scheme. It was possible to obtain a high classification accuracy of 0.91. Validation of the sleep stage detector in other sleep disorders, such as apnea and narcolepsy, should be considered in future work.

Sleep spindle alterations in patients with Parkinson's disease

The aim of this study was to identify changes of sleep spindles (SS) in the EEG of patients with Parkinson's disease (PD). Five sleep experts manually identified SS at a central scalp location (C3-A2) in 15 PD and 15 age- and sex-matched control subjects. Each SS was given a confidence score, and by using a group consensus rule, 901 SS were identified and characterized by their (1) duration, (2) oscillation frequency, (3) maximum peak-to-peak amplitude, (4) percent-to-peak amplitude, and (5) density. Between-group comparisons were made for all SS characteristics computed, and significant changes for PD patients vs. control subjects were found for duration, oscillation frequency, maximum peak-to-peak amplitude and density. Specifically, SS density was lower, duration was longer, oscillation frequency slower and maximum peak-to-peak amplitude higher in patients vs. controls. We also computed inter-expert reliability in SS scoring and found a significantly lower reliability in scoring definite SS in patients when compared to controls. How neurodegeneration in PD could influence SS characteristics is discussed. We also note that the SS morphological changes observed here may affect automatic detection of SS in patients with PD or other neurodegenerative disorders (NDDs).

Analysis of automated quantification of motor activity in REM sleep behaviour disorder

Rapid eye movement (REM) sleep behaviour disorder (RBD) is characterized by dream enactment and REM sleep without atonia. Atonia is evaluated on the basis of visual criteria, but there is a need for more objective, quantitative measurements. We aimed to define and optimize a method for establishing baseline and all other parameters in automatic quantifying submental motor activity during REM sleep. We analysed the electromyographic activity of the submental muscle in polysomnographs of 29 patients with idiopathic RBD (iRBD), 29 controls and 43 Parkinson's (PD) patients. Six adjustable parameters for motor activity were defined. Motor activity was detected and quantified automatically. The optimal parameters for separating RBD patients from controls were investigated by identifying the greatest area under the receiver operating curve from a total of 648 possible combinations. The optimal parameters were validated on PD patients. Automatic baseline estimation improved characterization of atonia during REM sleep, as it eliminates inter/intra-observer variability and can be standardized across diagnostic centres. We found an optimized method for quantifying motor activity during REM sleep. The method was stable and can be used to differentiate RBD from controls and to quantify motor activity during REM sleep in patients with neurodegeneration. No control had more than 30% of REM sleep with increased motor activity; patients with known RBD had as low activity as 4.5%. We developed and applied a sensitive, quantitative, automatic algorithm to evaluate loss of atonia in RBD patients.

Prepulse inhibition is associated with attention, processing speed, and 123I-FP-CIT SPECT in Parkinson's disease

BACKGROUND

Prepulse inhibition is a measure of sensorimotor gating, which reflects the ability to filter or 'gate' irrelevant information. Prepulse inhibition is dramatically altered in basal ganglia disorders associated with dysfunction in the midbrain dopaminergic system, and corresponding cognitive information processing deficits such as slowed processing speed. Parkinson's disease is characterised by the degeneration of the midbrain dopaminergic system and is associated with cognitive dysfunction, including slowed information processing. Although sensorimotor processes in Parkinson's disease have been extensively studied in relation to motor function, less is known about the potential role of sensorimotor processes in cognitive function.

OBJECTIVE

We investigated the relationship between prepulse inhibition, cognition and nigrostriatal dysfunction, as measured with 123I-FP-CIT-SPECT scanning, in patients with Parkinson's disease.

METHODS

38 Parkinson patients were assessed with prepulse inhibition, neuropsychological tests, and neurological investigation. A subset of these patients underwent 123I-FP-CIT-SPECT scanning.

RESULTS

Patients with a higher level of prepulse inhibition performed better on cognitive measures tapping attention and processing speed than patients with a lower level of prepulse inhibition. Furthermore, there were significant correlations between prepulse inhibition and 123I-FP-CIT uptake in the striatum.

CONCLUSIONS

Our results suggest that the level of prepulse inhibition is related to the efficiency of information processing in Parkinson's disease, and to the density of dopamine transporters in the striatum.

Sleep phenomena as an early biomarker for Parkinsonism

Idiopathic Rapid-Eye-Movement (REM) sleep Behavior Disorder (iRBD) is one of the most potential biomarkers for Parkinson's Disease (PD) and some atypical PD (AP). It is characterized by REM sleep with abnormal high surface EMG (sEMG) activity. Some twitching during REM sleep is normal, but no one has defined what normal is, and no well-defined methodology for measuring muscle activity in REM sleep exists. The purpose of this study is to investigate the possibility of detecting abnormal high muscle activity during REM sleep in subjects diagnosed with iRBD. This has been achieved by considering the abnormal high muscle activity during REM sleep in iRBD subjects as an outlier detection problem, while exploiting that iRBD muscle activity is more grouped. It was possible to correctly discriminate all iRBD subjects from healthy elderly control subjects and subjects diagnosed with periodic limb movement (PLM) disorder. However, not all PD subjects were classified as having abnormal muscle activity, which is assumed to support the fact that not all PD subjects develop RBD.

Acute Sleep Restriction Reduces Insulin Sensitivity in Adolescent Boys

BACKGROUND

Short sleep duration has been linked to impaired glucose metabolism in many experimental studies. Moreover, studies have reported indications of an increased metabolic stress following sleep restriction.

OBJECTIVE

We aimed to investigate the effects of partial sleep deprivation on markers of glucose metabolism. Additionally, we aimed to investigate if short sleep duration induces a state of endocrine stress.

DESIGN

A randomized crossover design, with 2 experimental conditions: 3 consecutive nights of short sleep (SS, 4 h/night) and long sleep (LS, 9 h/night) duration.

SUBJECTS AND MEASUREMENTS

In 21 healthy, normal-weight male adolescents (mean ± SD age: 16.8 ± 1.3 y) we measured pre- and post-prandial glucose, insulin, C-peptide, and glucagon concentrations. Furthermore, we measured fasting cortisol, 24-h catecholamines, and sympathovagal balance.

RESULTS

Fasting insulin was 59% higher (P = 0.001) in the SS than the LS condition as was both fasting (24%, P < 0.001) and post-prandial (11%, P = 0.018) C-peptide. Pre- and post-prandial glucose and glucagon were unchanged between conditions. The homeostasis model assessment of insulin resistance (HOMA-IR) index was 65% higher (P = 0.002) and the Matsuda index was 28% lower (P = 0.007) in the SS condition compared to the LS condition. The awakening cortisol response and 24-h norepinephrine were not affected by sleep duration, whereas 24-h epinephrine was 24% lower (P = 0.013) in the SS condition. Neither daytime nor 24-h sympathovagal balance differed between sleep conditions. Short wave sleep was preserved in the SS condition.

CONCLUSION

Short-term sleep restriction is associated with decreased insulin sensitivity in healthy normal-weight adolescent boys. There were no indications of endocrine stress beyond this.

CITATION

Klingenberg L; Chaput JP; Holmbäck U; Visby T; Jennum P; Nikolic M; Astrup A; Sjödin A. Acute Sleep Restriction Reduces Insulin Sensitivity in Adolescent Boys. SLEEP 2013;36(7):1085-1090.

Automatic detection of REM sleep in subjects without atonia

Idiopathic Rapid-Rye-Movement (REM) sleep Behavior Disorder (iRBD) is a strong early marker of Parkinson's Disease and is characterized by REM sleep without atonia (RSWA) and increased phasic muscle activity. Current proposed methods for detecting RSWA assume the presence of a manually scored hypnogram. In this study a full automatic REM sleep detector, using the EOG and EEG channels, is proposed. Based on statistical features, combined with subject specific feature scaling and post-processing of the classifier output, it was possible to obtain an mean accuracy of 0.96 with a mean sensitivity and specificity of 0.94 and 0.96 respectively.

Case-control design as investigative approach to assessing cancer etiology: development and future perspectives

The case-control method evolved out of analyses of series of cases. The analytic form of the case-control study can be found in the 19th century medical literature, but did not appear to be viewed as a special or distinct methodology. The first modern case-control study was the Janet Lane-Claypon's study of breast cancer in 1926, but the design was used only sporadically in medicine until 1950, when 4 published casecontrol studies linked smoking and lung cancer. These 1950s studies synthesized the essential elements of the case-control comparison, produced a conceptual shift within epidemiology, and laid the foundation for the rapid development of the case-control design in the subsequent half century. The powerful consistency of these case-control studies, and the replication of their findings in later prospective studies, promoted the general acceptance of the case-control study as a scientific tool in clinical research. Newer case-control studies have benefited from the advances in design, execution and analysis since 1950s. These advances include more rigorous selection and matching of case and control population, improved interviewing techniques, location of the design within a general framework of epidemiologic strategies for relating exposure to disease, understanding of the measures of effect, and application of increasingly sophisticated statistical procedures to findings. This review traces the development and future perspectives of the case-control design to assessing cancer etiology. With illustrations drawn primarily from the literature on its use and the value of its results to unravelling the etiology of malignant diseases, we tried to explore if the case-control approach firmly ensconced in epidemiology as investigational tool and rivals in importance the more straightforward cohort approach.