Closed-loop system to enhance slow-wave activity

Garcia-Molina, Gary; Tsoneva, Tsvetomira; Jasko, Jeff; Steele, Brenda; Aquino, Antonio; Baher, Keith; Pastoor, Sander; Pfundtner, Stefan; Ostrowski, Lynn; Miller, B.L.; Papas, N.; Riedner, Brady A.; Tononi, Giulio; White, David P.

doi:10.1088/1741-2552/aae18f

Cited by 69 publications

(62 citation statements)

References 45 publications

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“…More recently, a new group of devices has emerged for home sleep monitoring that uses EEG electrodes to measure brain activity. These include headbands (19)(20)(21)(22) and devices placed around the ear (23,24). Unlike traditional PSG, these more compact devices are usually cheaper, less burdensome, designed to be worn for multiple nights at home to enable longitudinal data collection, and require minimal or no expert supervision.…”

Section: Introductionmentioning

confidence: 99%

The Dreem Headband as an Alternative to Polysomnography for EEG Signal Acquisition and Sleep Staging

Thorey²,

et al. 2019

Preprint

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Despite the central role of sleep in our lives and the high prevalence of sleep disorders, sleep is still poorly understood. The development of ambulatory technologies capable of monitoring brain activity during sleep longitudinally is critical to advancing sleep science and facilitating the diagnosis of sleep disorders. We introduced the Dreem headband (DH) as an affordable, comfortable, and user-friendly alternative to polysomnography (PSG). The purpose of this study was to assess the signal acquisition of the DH and the performance of its embedded automatic sleep staging algorithms compared to the gold-standard clinical PSG scored by 5 sleep experts. Thirty-one subjects completed an over-night sleep study at a sleep center while wearing both a PSG and the DH simultaneously. We assessed 1) the EEG signal quality between the DH and the PSG, 2) the heart rate, breathing frequency, and respiration rate variability (RRV) agreement between the DH and the PSG, and 3) the performance of the DH's automatic sleep staging according to AASM guidelines vs. PSG sleep experts manual scoring. Results demonstrate a strong correlation between the EEG signals acquired by the DH and those from the PSG, and the signals acquired by the DH enable monitoring of alpha (r= 0.71 ± 0.13), beta (r= 0.71 ± 0.18), delta (r = 0.76 ± 0.14), and theta (r = 0.61 ± 0.12) frequencies during sleep. The mean absolute error for heart rate, breathing frequency and RRV was 1.2 ± 0.5 bpm, 0.3 ± 0.2 cpm and 3.2 ± 0.6 %, respectively. Automatic Sleep Staging reached an overall accuracy of 83.5 ± 6.4% (F1 score : 83.8 ± 6.3) for the DH to be compared with an average of 86.4 ± 8.0% (F1 score: 86.3 ± 7.4) for the five sleep experts. These results demonstrate the capacity of the DH to both precisely monitor sleep-related physiological signals and process them accurately into sleep stages. This device paves the way for high-quality, large-scale, longitudinal sleep studies. Sleep | EEG | Machine learning | Sleep stages | DeviceCorrespondence: research@dreem.com

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Section: Introductionmentioning

confidence: 99%

The Dreem Headband as an Alternative to Polysomnography for EEG Signal Acquisition and Sleep Staging

Thorey²,

et al. 2019

Preprint

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“…In one type of neuromodulation, acoustic stimuli are phase locked to spontaneous slow waves. This has been reported to enhance slow waves in young people, but not in older people (Garcia-Molina et al 2018). Whether this enhancement improves subjective sleep quality and waking function has not been firmly established.…”

Section: Sleep Promotionmentioning

confidence: 98%

Sleep Physiology, Circadian Rhythms, Waking Performance and the Development of Sleep-Wake Therapeutics

Dijk

Landolt

2019

Sleep-Wake Neurobiology and Pharmacology

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“…The home-EEG device was originally developed to acoustically stimulate deep sleep, through automatic EEG-based detection of slow waves (0.5-4 Hz), however we used the device for measurement purposes only, without auditory stimulation. The SmartSleep algorithm, based on 6 second epochs, differentiates between wakefulness, light sleep, and deep sleep (26,27). Even though these sleep stages are calculated based on a single lead, studies have proven feasibility and validity of sleep staging with the home-EEG device (26,(28)(29)(30).…”

Section: Home-eeg Measurementsmentioning

confidence: 99%

Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers – The ANCHOR study

Mentink

Thomas

Melis

et al. 2020

Preprint

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Study objectivesWhile poor sleep quality has been related to increased risk of Alzheimer’s disease, long-time shift workers (maritime pilots) did not manifest evidence of early Alzheimer’s disease in a recent study. We explored two hypotheses of possible compensatory mechanisms for sleep disruption: Increased efficiency in generating deep sleep during workweeks (model 1) and rebound sleep during rest weeks (model 2).MethodsWe used data from ten male maritime pilots (mean age: 51.6±2.4 years) with a history of approximately 18 years of irregular shift work. Subjective sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). A single lead EEG-device was used to investigate sleep in the home/work environment, quantifying total sleep time (TST), deep sleep time (DST), and deep sleep time percentage (DST%). Using multilevel models, we studied the sleep architecture of maritime pilots over time, at the transition of a workweek to a rest week.ResultsMaritime pilots reported worse sleep quality in workweeks compared to rest weeks (PSQI=8.2±2.2 vs. 3.9±2.0; p<0.001). Model 1 showed a trend towards an increase in DST% of 0.6% per day during the workweek (p=0.08). Model 2 did not display an increase in DST% in the rest week (p=0.87).ConclusionsOur findings indicated that increased efficiency in generating deep sleep during workweeks is a more likely compensatory mechanism for sleep disruption in the maritime pilot cohort than rebound sleep during rest weeks. Compensatory mechanisms for poor sleep quality might mitigate sleep disruption-related risk of developing Alzheimer’s disease. These results should be used as a starting point for future studies including larger, more diverse populations of shift workers.

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Closed-loop system to enhance slow-wave activity

Abstract: 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.

Cited by 69 publications

References 45 publications

The Dreem Headband as an Alternative to Polysomnography for EEG Signal Acquisition and Sleep Staging

The Dreem Headband as an Alternative to Polysomnography for EEG Signal Acquisition and Sleep Staging

Sleep Physiology, Circadian Rhythms, Waking Performance and the Development of Sleep-Wake Therapeutics

Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers – The ANCHOR study

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