Closed-Loop Acoustic Stimulation of Slow Oscillations Using a Wireless EEG Headband: A Polysomnography-Validated Feasibility Study

Acoustic stimulation precisely timed during sleep can enhance slow oscillations (SOs), a hallmark of deep sleep that is critical for restorative sleep. To date, this approach has largely been restricted to laboratory settings using high-density electroencephalography (EEG). Wearable EEG systems featuring closed-loop acoustic stimulation could enable scalable, home-based approaches to modulating slow-wave sleep. Here, we tested whether a real-time modeling approach (M-CLNS) could be implemented using a wireless EEG headband with forehead electrodes in healthy participants. Acoustic stimulation was delivered during a single night of sleep in alternating stimulation and sham conditions. We evaluated the accuracy of SO phase targeting utilizing the EEG headband and assessed whether it could be used to detect stimulation-induced changes in oscillatory dynamics. The findings were validated against simultaneous polysomnographic (PSG) recordings as an independent reference. We found that SO phase was targeted consistently near the intended phase using the headband, despite reduced amplitude and signal quality compared with simultaneous PSG. Acoustic stimulation produced an immediate enhancement of SO dynamics, as well as sustained increases in SO density and power spectral density within the SO and delta frequency range (0.75–5 Hz) during deep sleep. These effects were apparent both in the EEG headband and PSG signals. These results demonstrate the feasibility of closed-loop acoustic stimulation using a wireless EEG headband, providing a foundation for future home-based and clinical applications.

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Publication Details

Journal
Sensors
Published
2026-10-15
DOI
https://doi.org/10.3390/s26206528
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
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article

Closed-Loop Acoustic Stimulation of Slow Oscillations Using a Wireless EEG Headband: A Polysomnography-Validated Feasibility Study

Stefan L. Jongejan, Lucia M. Talamini, A.C. van der Heijden
Sensors
EEG and Brain-Computer Interfaces
article

Closed-Loop Acoustic Stimulation of Slow Oscillations Using a Wireless EEG Headband: A Polysomnography-Validated Feasibility Study

Stefan L. Jongejan, Lucia M. Talamini, A.C. van der Heijden
article en

Abstract

Acoustic stimulation precisely timed during sleep can enhance slow oscillations (SOs), a hallmark of deep sleep that is critical for restorative sleep. To date, this approach has largely been restricted to laboratory settings using high-density electroencephalography (EEG). Wearable EEG systems featuring closed-loop acoustic stimulation could enable scalable, home-based approaches to modulating slow-wave sleep. Here, we tested whether a real-time modeling approach (M-CLNS) could be implemented using a wireless EEG headband with forehead electrodes in healthy participants. Acoustic stimulation was delivered during a single night of sleep in alternating stimulation and sham conditions. We evaluated the accuracy of SO phase targeting utilizing the EEG headband and assessed whether it could be used to detect stimulation-induced changes in oscillatory dynamics. The findings were validated against simultaneous polysomnographic (PSG) recordings as an independent reference. We found that SO phase was targeted consistently near the intended phase using the headband, despite reduced amplitude and signal quality compared with simultaneous PSG. Acoustic stimulation produced an immediate enhancement of SO dynamics, as well as sustained increases in SO density and power spectral density within the SO and delta frequency range (0.75–5 Hz) during deep sleep. These effects were apparent both in the EEG headband and PSG signals. These results demonstrate the feasibility of closed-loop acoustic stimulation using a wireless EEG headband, providing a foundation for future home-based and clinical applications.

SensorsVol. 26(20)
Good health and well-being
Openalex Percentile: Top 14%
EEG and Brain-Computer Interfaces
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