Sleep Optimization With Acoustic Therapy

Official title

Sleep Optimization With Acoustic Therapy: A Polysomnography-Based Pre-Post Study

Overview

Insomnia is a highly prevalent sleep disorder characterized by persistent difficulty initiating or maintaining sleep, often accompanied by impaired daytime functioning. Chronic insomnia affects approximately 10-15% of the adult population and is associated with significant physical, psychological, and socioeconomic burden. Traditional management strategies, including cognitive behavioral therapy for insomnia (CBT-I) and pharmacotherapy, have shown varying levels of effectiveness, with some patients remaining refractory to standard interventions or experiencing unwanted side effects. Recent advances in sleep neuroscience have revealed that disturbances in endogenous brain rhythms, particularly reductions in slow-wave activity (SWA) and altered sleep spindle patterns, play a key role in the pathophysiology of insomnia. These findings have sparked interest in non-pharmacological neuromodulation approaches to restore healthy sleep architecture. One such approach is personalized nocturnal sound frequency therapy, in which low-frequency auditory stimuli (e.g., pink noise or slow oscillation-matched tones) are delivered during sleep to entrain and enhance specific sleep-related brain oscillations. Studies in healthy individuals and patients with insomnia have demonstrated that such stimulation can augment slow-wave sleep (N3), reduce nocturnal arousals, and improve perceived sleep quality. Personalized algorithms that adapt sound delivery based on real-time EEG signals further enhance these devices' efficacy and user experience. Despite growing evidence supporting the utility of sound-based sleep modulation, there is limited data on its application in diverse insomnia subtypes and its effect as measured by gold-standard sleep studies such as polysomnography (PSG). This study uses a pre-post PSG design to evaluate the impact of personalized sound frequency therapy on objective sleep architecture and subjective sleep outcomes in patients with insomnia. The findings may provide new insights into the therapeutic potential of acoustic brainwave modulation and support its integration into personalized insomnia care.

Detailed description

Primary Objective:

To evaluate the effect of daily personalized sound frequency therapy on sleep architecture (N1/N2/N3 %, REM %, total sleep time, sleep latency, sleep efficiency) measured by polysomnography after 12 weeks of intervention.

Secondary Objectives:

* To evaluate the effect of daily personalized sound frequency therapy after 12 weeks of intervention * Sleep quality; using Pittsburgh Sleep Quality Index(PSQI) questionnaire , * Insomnia; using Insomnia severity index(ISI) questionaire, * apnea-hypopnea index (AHI) assessed by polysomnography * daytime sleepiness; using the Epworth Sleepiness Score (ESS) intervention. * To assess user adherence, tolerability, and acceptability of the sound therapy.

Hypothesis There is an improvement in terms of sleep architecture, sleep quality (PSQI), insomnia severity (ISI), apnea-hypopnea index (AHI), and daytime sleepiness (ESS) with sound frequency therapy after 12 weeks of intervention.

Study Design:

A prospective, single-arm, longitudinal pre-post interventional study. Intervention duration: 12 weeks.

Baseline and follow-up PSG (full-night polysomnography).

Study Population:

Insomnia patients/hospital staff in Hospital Canselor Tuanku Muhriz UKM

Interventions

• Device Personalized Sound Therapy
  Participants will receive a wearable sound stimulation device for 12 weeks, programmed with personalized low-frequency auditory stimuli (e.g., pink noise or slow-wave-matched sounds). The patient will self-administer the therapy at home, for one hour in the morning (upon waking) and one hour in the evening (around 5 p.m. until just before sleep). The recommended device volume is above 30%, with a frequency range between 15 and 20,000 Hz

Primary outcome measures

• Comparison in Sleep Architexture pre and post treatment [Time frame: 12 weeks]

Secondary outcome measures (5)

• Comparison of Imsonia Severity Index pre and post treatment [Time frame: 12 weeks]
• Comparison of Pittsburgh Sleep Quality Index (PSQI) pre and post treatment [Time frame: 12 weeks]
• Comparison of Epworth Sleepiness Scale (ESS) pre and post treatment [Time frame: 12 weeks]
• adverse events of the therapy [Time frame: 12 weeks]
• adherence of the treatment received [Time frame: 12 weeks]

Eligibility criteria

Inclusion criteria

• Adults aged 18-60 years
• With sleep disturbances based on the PSQI score of >5 and/or ISI score > 15

Exclusion criteria

• Central sleep apnea
• Epilepsy
• Current use of sedative-hypnotics or neurostimulation devices
• Shift workers (people with different working hours patterns, for example morning, afternoon, night shifts)
• Pregnancy
• Moderate to severe OSA (AHI >15)
• Presbycusis or other significant hearing loss
• Patients with psychiatric disorder

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation

N/A

Model

Single group

Masking

Open label

Primary purpose

Treatment

Study locations

Malaysia · 1 center

• National University of Malaysia, Faculty of Medicine — Cheras

Publications

• Lustenberger C, Maric A, Durr R, Achermann P, Huber R. Triangular relationship between sleep spindle activity, general cognitive ability and the efficiency of declarative learning. PLoS One. 2012;7(11):e49561. doi: 10.1371/journal.pone.0049561. Epub 2012 Nov 21. PMID 23185361
• Baglioni C, Spiegelhalder K, Lombardo C, Riemann D. Sleep and emotions: a focus on insomnia. Sleep Med Rev. 2010 Aug;14(4):227-38. doi: 10.1016/j.smrv.2009.10.007. Epub 2010 Feb 6. PMID 20137989
• Perlis ML, Giles DE, Mendelson WB, Bootzin RR, Wyatt JK. Psychophysiological insomnia: the behavioural model and a neurocognitive perspective. J Sleep Res. 1997 Sep;6(3):179-88. doi: 10.1046/j.1365-2869.1997.00045.x. PMID 9358396
• Riemann D, Krone LB, Wulff K, Nissen C. Sleep, insomnia, and depression. Neuropsychopharmacology. 2020 Jan;45(1):74-89. doi: 10.1038/s41386-019-0411-y. Epub 2019 May 9. PMID 31071719
• Ngo HV, Martinetz T, Born J, Molle M. Auditory closed-loop stimulation of the sleep slow oscillation enhances memory. Neuron. 2013 May 8;78(3):545-53. doi: 10.1016/j.neuron.2013.03.006. Epub 2013 Apr 11. PMID 23583623
• Leminen MM, Virkkala J, Saure E, Paajanen T, Zee PC, Santostasi G, Hublin C, Muller K, Porkka-Heiskanen T, Huotilainen M, Paunio T. Enhanced Memory Consolidation Via Automatic Sound Stimulation During Non-REM Sleep. Sleep. 2017 Mar 1;40(3):zsx003. doi: 10.1093/sleep/zsx003. PMID 28364428
• Ong JL, Lo JC, Chee NI, Santostasi G, Paller KA, Zee PC, Chee MW. Effects of phase-locked acoustic stimulation during a nap on EEG spectra and declarative memory consolidation. Sleep Med. 2016 Apr;20:88-97. doi: 10.1016/j.sleep.2015.10.016. Epub 2015 Nov 27. PMID 27318231
• Arnal PJ, Thorey V, Debellemaniere E, Ballard ME, Bou Hernandez A, Guillot A, Jourde H, Harris M, Guillard M, Van Beers P, Chennaoui M, Sauvet F. The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging. Sleep. 2020 Nov 12;43(11):zsaa097. doi: 10.1093/sleep/zsaa097. PMID 32433768

Identifiers

NCT: NCT07503223 · FF-2026-126

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗