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Traditionally, auscultation is applied to the diagnosis of either respiratory disturbances by respiratory sounds or cardiac disturbances by cardiac sounds. In addition, for sleep apnea syndrome diagnosis, snoring sounds are also monitored. The present study was aimed at synchronous detection of all three sound components (cardiac, respiratory, and snoring) from a single spot. The sounds were analyzed with respect to the cardiorespiratory activity, and to the detection and classification of apneas. Sound signals from 30 subjects including 10 apnea patients were detected by means of a microphone connected to a chestpiece which was applied to the heart region. The complex nature of the signal was investigated using time, spectral, and statistical approaches, in connection with self-defined time-based and event-based characteristics. The results show that the obstruction is accompanied by an increase of statistically relevant spectral components in the range of 300 to 2000 Hz, however, not within the range up to 300 Hz. Signal properties are discussed with respect to different breathing types, as well as to the presence and the type of apneas. Principal component analysis of the event-based characteristics shows significant properties of the sound signal with respect to different types of apneas and different patient groups, respectively. The analysis reflects apneas with an obstructive segment and those with a central segment. In addition, aiming for an optimum detection of all three sound components, alternative regions on the thorax and on the neck were investigated on two subjects. The results suggest that the right thorax region in the seventh intercostal space and the neck are optimal regions. It is concluded that for patient assessment, extensive acoustic analysis offers a reduction in the number of required sensor components, especially with respect to compact home monitoring of apneas. Index Terms--Acoustic measurements, apnea classification, apnea screening, breathing sounds, heart sounds, snoring.

Byline: Svenja Happe (1,2), Peter Anderer (3), Walter Pirker (1), Gerhard Klosch (1), Georg Gruber (3), Bernd Saletu (3), Josef Zeitlhofer (1) Keywords: K-complex; sleep spindle; Parkinson's disease; SPECT; dopamine Abstract: Abstract Objectives Along with spindles, K-complexes are well known hallmarks of stage 2 (S2) sleep. However, little is known about their quantity in S2 sleep of patients with Parkinson's disease (PD). Setting Sleep laboratory, Department of Neurology, University of Vienna, Austria. Patients and methods Whole-night polysomnography (PSG) was performed in twelve treated PD patients and ten healthy controls without history of sleep complaints. The quantity of spontaneous K-complexes, K-alpha-complexes, and sleep spindles in one hour S2 sleep, distributed in four epochs of 15 minutes all through the night, were visually selected and analysed. The quantity and the temporal course of these phasic events were compared with the quantity in age-matched healthy controls. Nine of the twelve PD patients underwent [[.sup.123]I][beta]-CIT SPECT for calculating dopamine transporter binding in the striatum and serotonin transporter density in the thalamus-hypothalamus region. Results There was no difference between the quantity of K-complexes, K-alpha-complexes, and sleep spindles in PD patients and in the healthy control group. K-complexes but not sleep spindles decreased over the night in both groups. The number of sleep spindles did not correlate with the dopamine transporter binding in the striatum or the serotonin binding in the thalamic/hypothalamic region. Conclusion K-complexes and sleep spindles are not reduced and do not seem to be related to the degree of dopaminergic degeneration in treated PD patients. Author Affiliation: (1) Department of Neurology, University of Vienna, Austria (2) Department of Clinical Neurophysiology, University of Gottingen, Robert-Koch-Str. 40, 37099, Gottingen, Germany (3) Department of Psychiatry, University of Vienna, Austria Article History: Registration Date: 01/01/2004 Received Date: 09/02/2004 Accepted Date: 27/05/2004 Article note: This research was supported in part by the European Commission, DG XII (Project Biomed-2 BMH4-CT97--2040 'SIESTA') and by the Austrian National Bank (Project 7870). Svenja Happe, MD, was recipient for a fellowship stipend of the European Neurological Society (ENS).

Sleep and memory studies often focus on overnight rather than long‐term memory changes, traditionally associating overnight memory change (OMC) with sleep architecture and sleep patterns such as spindles. In addition, (para‐)sympathetic innervation has been associated with OMC after a daytime nap using heart rate variability (HRV). In this study we investigated overnight and long‐term performance changes for procedural memory and evaluated associations with sleep architecture, spindle activity (SpA) and HRV measures (R‐R interval [RRI], standard deviation of R‐R intervals [SDNN], as well as spectral power for low [LF] and high frequencies [HF]). All participants (N = 20, Mage = 23.40 ± 2.78 years) were trained on a mirror‐tracing task and completed a control (normal vision) and learning (mirrored vision) condition. Performance was evaluated after training (R1), after a full‐night sleep (R2) and 7 days thereafter (R3). Overnight changes (R2‐R1) indicated significantly higher accuracy after sleep, whereas a significant long‐term (R3‐R2) improvement was only observed for tracing speed. Sleep architecture measures were not associated with OMC after correcting for multiple comparisons. However, individual SpA change from the control to the learning night indicated that only "SpA enhancers" exhibited overnight improvements for accuracy and long‐term improvements for speed. HRV analyses revealed that lower SDNN and LF power was associated with better OMC for the procedural speed measure. Altogether, this study indicates that overnight improvement for procedural memory is specific for spindle enhancers, and is associated with HRV during sleep following procedural learning. [ABSTRACT FROM AUTHOR]