# Acoustic stimulation and other emerging approaches to enhance sleep: design notes for the next generation of closed-loop neurostimulation technology

## TL;DR

This paper reviews new technologies that use sound and brain stimulation to improve sleep quality and efficiency, aiming to create personalized and adaptable sleep enhancement systems.

## Contribution

The paper proposes a modular, open-source platform for closed-loop neurostimulation to enhance sleep through real-time brain rhythm interaction.

## Key findings

- Closed-loop neurostimulation can enhance key sleep oscillations like slow waves and spindles to improve memory consolidation.
- Complementary methods for REM sleep and sleep onset latency show the versatility of neurostimulation systems.
- A modular and open-source ecosystem is needed to address challenges in stimulation timing and personalization.

## Abstract

Sleep is indispensable to human health, supporting memory consolidation, emotional regulation, immune function, and metabolic homeostasis. Despite its importance, chronic sleep disturbances are pervasive, with especially high prevalence in operational and clinical populations. This review synthesizes recent advances in sleep enhancement through closed-loop neurostimulation, focusing on systems that dynamically interact with endogenous brain rhythms to improve sleep quality and efficiency. Key oscillatory targets—including slow waves, sleep spindles, and hippocampal ripples—are examined in the context of memory consolidation, with evidence supporting their augmentation via temporally precise auditory and electrical stimulation. Complementary methods targeting rapid eye movement (REM) sleep and sleep onset latency are discussed, underscoring the versatility of closed-loop systems. The review identifies outstanding questions regarding stimulation timing, modality selection, physiological limits, and the dissociation between slow oscillations and delta activity. To address these challenges, we advocate for a modular, open-source ecosystem that integrates real-time sleep state decoding with configurable effectors across auditory, electrical, and other domains. Such a platform would enable reproducible, scalable, and personalized interventions for sleep enhancement. This systems-level approach is aimed at accelerating translational research and catalyzing a paradigm shift toward actively regulated, on-demand sleep interventions.