The importance of the intensive care unit environment in sleep-A study with healthy participants.

Sleep disruption is common among intensive care unit patients, with potentially detrimental consequences. Environmental factors are thought to play a central role in ICU sleep disruption, and so it is unclear why environmental interventions have shown limited improvements in objectively assessed sleep. In critically ill patients, it is difficult to isolate the influence of environmental factors from the varying contributions of non-environmental factors. We thus investigated the effects of the ICU environment on self-reported and objective sleep quality in 10 healthy nurses and doctors with no history of sleep pathology or current or past ICU employment participated. Their sleep at home, in an unfamiliar environment ('Control'), and in an active ICU ('ICU') was evaluated using polysomnography and the Richard-Campbell Sleep Questionnaire. Environmental sound, light and temperature exposure were measured continuously. We found that the control and ICU environment were noisier and warmer, but not darker than the home environment. Sleep on the ICU was perceived as qualitatively worse than in the home and control environment, despite relatively modest effects on polysomnography parameters compared with home sleep: mean total sleep times were reduced by 48 min, mean rapid eye movement sleep latency increased by 45 min, and the arousal index increased by 9. Arousability to an awake state by sound was similar. Our results suggest that the ICU environment plays a significant but partial role in objectively assessed ICU sleep impairment in patients, which may explain the limited improvement of objectively assessed sleep after environmental interventions.

Hybrid in-phase and continuous auditory stimulation significantly enhances slow wave activity during sleep.

Recent evidence has shown that enhancing slow-wave activity (SWA) during sleep has positive effects on cognitive, metabolic, and autonomic function. We have developed a consumer, integrated device that automatically detects sleep stages from a single electroencephalogram (EEG) signal and delivers auditory stimulation in a closed-loop manner. The stimulation was delivered in 15-auditory tone blocks separated from each other by at least 15 seconds. The first tone in a block was synchronized to the up-state of a detected slow-wave while subsequent ones were separated from each other by a constant 1-second inter-tone interval. The system was tested in a study involving 22 participants and SWA enhancement (average 45.8%; p=0.0027) was found in 19/22 participants.

Closed-loop system to enhance slow-wave activity.

OBJECTIVE: Recent evidence reports cognitive, metabolic, and sleep restoration benefits resulting from the enhancement of sleep slow-waves using auditory stimulation. Our objective is to make this concept practical for consumer use by developing and validating an electroencephalogram (EEG) closed-loop system to deliver auditory stimulation during sleep to enhance slow-waves. APPROACH: The system automatically detects slow-wave sleep with 74% sensitivity and 97% specificity and optimally delivers stimulation in the form of 50 ms-long tones separated by a constant one-second inter-tone interval at a volume that is dynamically modulated such that louder tones are delivered when sleep is deeper. The system was tested in a study involving 28 participants (18F, 10M; 36.9 ± 7.3 years old; median age: 40 years old) who used the system for ten nights (five nights in a sham condition and five in a stimulation condition). Four nights in each condition were recorded at-home and the fifth one in-lab. MAIN RESULTS: The analysis in two age groups defined by the median age of participants in the study shows significant slow wave activity enhancement (+16.1%, p < 0.01) for the younger group and absence of effect on the older group. However, the older group received only a fraction (57%) of the stimulation compared to the younger group. Changes in sleep architecture and EEG properties due to aging have influenced the amount of stimulation. The analysis of the stimulation timing suggests an entrainment-like phenomenon where slow-waves align to the stimulation periodicity. In addition, enhancement of spindle power in the stimulation condition was found. SIGNIFICANCE: We show evidence of the viability of delivering auditory stimulation during sleep, at home, to enhance slow wave activity. The system ensures the stimulation delivery to be at the right time during sleep without causing disturbance.

Automatic characterization of sleep need dissipation dynamics using a single EEG signal.

In the two-process model of sleep regulation, slow-wave activity (SWA, i.e. the EEG power in the 0.5-4 Hz frequency band) is considered a direct indicator of sleep need. SWA builds up during non-rapid eye movement (NREM) sleep, declines before the onset of rapid-eye-movement (REM) sleep, remains low during REM and the level of increase in successive NREM episodes gets progressively lower. Sleep need dissipates with a speed that is proportional to SWA and can be characterized in terms of the initial sleep need, and the decay rate. The goal in this paper is to automatically characterize sleep need from a single EEG signal acquired at a frontal location. To achieve this, a highly specific and reasonably sensitive NREM detection algorithm is proposed that leverages the concept of a single-class Kernel-based classifier. Using automatic NREM detection, we propose a method to estimate the decay rate and the initial sleep need. This method was tested on experimental data from 8 subjects who recorded EEG during three nights at home. We found that on average the estimates of the decay rate and the initial sleep need have higher values when automatic NREM detection was used as compared to manual NREM annotation. However, the average variability of these estimates across multiple nights of the same subject was lower when the automatic NREM detection classifier was used. While this method slightly over estimates the sleep need parameters, the reduced variability across subjects makes it more effective for within subject statistical comparisons of a given sleep intervention.