Sleep Optimization With Acoustic Therapy: A Polysomnography-Based Pre-Post Study
Phase: NA
Conditions: IMSOMNIA, Sleep Disturbance
Sponsor: National University of Malaysia

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DEPARTMENT OF MEDICINE 
UNIVERSITI KEBANGSAAN MALAYSIA 
SONATA Trial – Sleep Optimization with Acoustic Therapy:  
A Polysomnography-Based Pre-Post Study 
 
FF-2026-126 
Version 1 Date : 1 March 2026 
 
Dr Ho Yun Nyen 
Doctor Of Internal Medicine Programme, Faculty Of Medicine, UKM 
 
Supervisor: 
Prof Dr Mohamed Faisal Abd Hamid 
Respiratory Unit, Department Of Medicine, Hospital Canselor Tuanku Muhriz Ukm 
Co-Supervisor: 
Dr Haji Azat Azrai Bin Azmel 
Respiratory Unit, Department Of Medicine, Hospital Canselor Tuanku Muhriz Ukm 
Dr Mas Fazlin Jailaini 
Respiratory Unit, Department Of Medicine, Hospital Canselor Tuanku Muhriz UKM 
 
STATISTICIAN ADVISOR: 
Professor Dr Shamsul Azhar Shah 
Public Health, Epidemiology And Statistics Department, Hospital Canselor Tuanku 
Muhriz, UKM 
 
 

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TABLE OF CONTENTS 
CHAPTER I INTRODUCTION 
CHAPTER II RESEARCH OBJECTIVE 
CHAPTER III LITERATURE REVIEW 
CHAPTER IV METHODOLOGY 
CHAPTER V RESEARCH ETHICS 
CHAPTER VI FINANCIAL PLAN 
CHAPTER VII RESEARCH INFORMATION 
CHAPTER VIII CONSENT FORM 
CHAPTER IX DATA COLLECTION SHEET 
CHAPTER X GANTT CHART 
CHAPTER XI APPENDICES 
CHAPTER XII REFERENCES 
 
 

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CHAPTER I 
INTRODUCTION 
BACKGROUND AND RATIONALE 
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. (1) 
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. 
 

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CHAPTER II 
RESEARCH OBJECTIVE 
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. 
 
 

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CHAPTER III 
LITERATURE REVIEW 
 
Insomnia and Altered Sleep Architecture 
        Insomnia is a disorder of hyperarousal, marked not only by subjective complaints of 
poor sleep but also by objective alterations in sleep architecture. Studies using 
polysomnography have shown that individuals with insomnia often exhibit increased 
sleep latency, reduced sleep efficiency, decreased slow-wave sleep (N3), and 
fragmented REM sleep. These findings suggest that interventions targeting sleep 
architecture may be essential in improving insomnia outcomes beyond behavioral 
strategies alone. (2) 
 
Brain Oscillations and the Role of Slow-Wave Sleep 
        Slow-wave activity (0.5–4 Hz) during non-rapid eye movement (NREM) sleep is 
associated with key restorative functions of sleep, including synaptic downscaling, 
memory consolidation, and metabolic clearance. Insomnia patients often have reduced 
amplitude and incidence of these slow oscillations, which have been proposed as a 
physiological biomarker of hyperarousal. (3, 4)  
 
Auditory Stimulation as a Non-Pharmacological Sleep Modulation Tool 
         Auditory stimulation during sleep, especially low-frequency stimuli such as pink 
noise, has gained attention as a novel approach to enhance slow-wave sleep. A previous 
study demonstrated that closed-loop auditory stimulation, timed with endogenous slow 
oscillations, significantly increased SWA and memory retention in healthy individuals. (5) 
Subsequent studies confirmed that these enhancements can improve perceived sleep 
quality and reduce sleep onset latency. (6, 7) 
 
Personalized Acoustic Stimulation Devices 
         Commercially available sleep technologies (e.g., Dreem, Sleep Shepherd, Kokoon, 
Somnox) now incorporate personalized or adaptive sound therapy, using EEG-informed 
algorithms or preset frequencies tailored to individual sleep cycles. Arnal, Thorey 
(8)2020) validated the Dreem headband as a reliable alternative to full PSG in measuring 
brain activity and delivering auditory stimulation. These devices enable home-based 
delivery of sound stimulation and make scalable interventions possible. 
 
Efficacy in Insomnia and Other Populations 
         While most trials have been conducted in healthy adults, early evidence suggests 

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potential benefits for insomnia populations. A randomized controlled trial integrating 
auditory stimulation into behavioral therapy showed improved sleep maintenance and 
reduced arousals. However, large-scale clinical trials measuring changes in PSG-
confirmed sleep stages post-intervention remain limited. 
 
Knowledge Gaps and Justification for Current Study 
          Despite promising preliminary data, studies are often limited by small sample 
sizes, lack of control for insomnia subtypes, and insufficient objective measures such as 
PSG. Furthermore, the differential effects of personalized sound therapy in insomnia 
patients vs. good sleepers remain underexplored. This study addresses these gaps by 
evaluating both subjective and polysomnography-based outcomes in patients with 
insomnia following a 12-week course of personalized sound therapy. 
Nonetheless, there is a more recent randomized, single blind crossover study 
done by Aloulou (9), comparing sleep quality between subjects listening to personalized 
sound sequences vs non personalized placebo right before bedtime, as opposed to the 
usual nighttime acoustic therapy. The results showed that sleep quality improved with 
personalized sound frequency both objectively and subjectively.  
 

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CHAPTER IV 
METHODOLOGY 
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 
 
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 
 
SAMPLE SIZE CALCULATION 
Sample Size Justification: 
The proposed study uses a pre-post interventional design comparing sleep architecture 
parameters before and after 12 weeks of personalized sound frequency therapy in the 
same subjects. 
 
Based on similar published trials on acoustic stimulation in sleep research Ong, Lo (7), 
the primary outcome is comparing the percentage of slow-wave sleep (N3 stage) pre- 
and post-intervention, and its association with memory retention.  
 
Assumptions for calculation: 

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- Effect size (Cohen’s d): Moderate effect size assumed (d = 0.6), in line with existing 
studies showing ~5–10% absolute change in N3 percentage. 
- Power: 95% 
- Alpha level: 0.05 (two-tailed) 
- Paired comparison: Same subjects serve as their own control. 
 
Using standard formulas for the paired t-test: 
n = [(Z(1-α/2) + Z(1-β)) * σ / δ]^2 
 
 
Where: 
- Z(1-α/2) = 1.96 for 95% CI 
- Z(1-β) = 1.28 for 90% power 
- δ = expected mean difference in N3 (%) 
- σ = standard deviation of the paired difference. 
 
Based on previous literature, an expected mean difference of ~5% with a standard 
deviation of 8% yields: 
n = [(1.96 + 1.28) * / 0.6]^2 ≈ 29.16 
 
To account for dropouts and non-adherence, a 20% attrition buffer is added: 
30 × 1.2 = 40 subjects (rounded up). 
 
Thus, a final sample size of 40 participants must detect a clinically meaningful change in 
sleep architecture with sufficient power and significance. 
Type of Sampling 
The sampling method used in this study is purposive sampling. 
 
Intervention: 
At baseline, participants will undergo a comprehensive evaluation that includes a level 2 
full-night polysomnography (PSG) conducted within 48 hours before starting the 
intervention, completion of standardized questionnaires such as the Insomnia Severity 
Index (ISI), Epworth Sleepiness Scale (ESS), and Pittsburgh Sleep Quality Index (PSQI), as 
well as documentation of sleep and medical history. 

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Following baseline assessment, participants will receive a wearable sound stimulation 
device 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. Acceptable devices include in-ear, open-
ear, or standard headphones, while bone conduction devices are excluded. 
During the 12-week intervention period, participants must maintain daily device usage 
logs with at least 80% compliance and participate in weekly remote check-ins for 
monitoring and support. 
At post-intervention (after 12 weeks), participants will undergo a repeat PSG and 
complete post-treatment ISI and PSQI questionnaires and an adherence and tolerability 
survey to assess user experience, compliance, and acceptance of the sound therapy. 
Clinically meaningful changes were defined based on established MCIDs: reduction in ≥3 
points for PSQI(10), and ≥6 points for ISI (11). 
 
Outcome Measures: 
Primary Outcome: 
- Change in sleep architecture   
Secondary Outcomes: 
- Change in ISI 
- PSQI scores 
- Change in AHI 
- Side effect; and compliance (in % days used) 
-Assess user adherence, tolerability, and acceptability of the sound therapy 
 
Data Analysis: 
- Paired t-tests or Wilcoxon signed-rank test for within-group comparisons 
- Regression analysis to explore predictors of response 

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FLOW DIAGRAM 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Assessed for eligibility 
 (n=  ) 
Excluded  (n=   ) 
   Not meeting inclusion criteria (n=  ) 
   Declined to participate (n=  ) 
   Other reasons (n=  ) 
   Lost to follow up (n=  ) 
   Discontinued intervention 
(reasons) (n=  ) 
 Full-night PSG  
  Baseline questionnaires 
 Sleep history  
Analysed  (n=  ) 
 Completers of preintervention questionnaires, 
full night PSG (pre- and post- intervention), 
post intervention questionnaires 
Analysis 
Assessment (n=)  
Enrollment 
 Repeat PSG after 12 weeks    
 Post intervention questionnaires 
 Adherence and tolerability   
Intervention 
Daily device usage of Personalised Sound 
Therapy with weekly check-ins 

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OPERATIONAL TERMS DEFINITION 
 
1. Insomnia Severity Index (ISI) 
The Insomnia Severity Index is a validated self-reported questionnaire that 
assesses insomnia's nature, severity, and impact over the previous month. It 
consists of 7 items, each scored 0–4, with total scores ranging from 0–28. Higher 
scores indicate greater insomnia severity. An ISI score of > 15 indicates moderate 
insomnia. 
 
2. Apnea-Hypopnea Index (AHI) 
The Apnea-Hypopnea Index quantifies sleep-disordered breathing events per 
hour, calculated during a polysomnography (PSG). It is the sum of apneas 
(complete cessation of airflow) and hypopneas (partial reduction in airflow) 
divided by total sleep time in hours. 
- AHI <5: Normal 
- AHI 5–14: Mild OSA 
- AHI 15–29: Moderate OSA 
- AHI >30: Severe OSA 
 
3. Pittsburgh Sleep Quality Index (PSQI) 
The PSQI is a 19-item self-report questionnaire that assesses subjective sleep 
quality and disturbances over the past month. It yields 7 component scores, 
which are summed to give a global score (0–21). A score >5 indicates poor sleep 
quality. 
 
4.  Epworth Sleepiness Scale (ESS)  
The ESS questionnaire is used to assess a patient's excessive daytime sleepiness 
(EDS) subjectively by rating their likelihood of dozing off during eight activities. A 
score of > 10 indicates excessive daytime sleepiness.   
-<10: normal 
-11-12: mild excessive daytime sleepiness 
-13-15: moderate excessive daytime sleepiness 
-16-24: severe excessive daytime sleepiness 
 
5. Sleep Architecture 
Sleep architecture refers to the structure and pattern of sleep stages recorded 
during overnight polysomnography. It includes Non-Rapid Eye Movement 
(NREM) stages (N1, N2, N3) and Rapid Eye Movement (REM) sleep. Key 

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parameters include percentages of time spent in each stage, total sleep time 
(TST), sleep latency, sleep efficiency, and arousal index. 
 
6.  Treatment Success Definition  
 
A. Objective Criteria 
If Baseline Sleep Efficiency < 85% 
• 
Treatment success is defined as improvement in sleep efficiency (SE) meeting 
any of the following: 
• 
Absolute increase ≥ 5 % from baseline; or 
• 
Relative increase ≥ 10 % if baseline SE < 75 %; or 
• 
Achievement of SE ≥ 85 % after intervention. 
 
If Baseline Sleep Efficiency ≥ 85% 
• 
Treatment success requires: 
 
• 
Maintenance of SE within ± 3 % of baseline (no decline > 3 %), and 
 
• 
Improvement in at least one additional objective parameter: 
• 
Wake after sleep onset (WASO) ↓ ≥ 20 min or ≥ 20 % 
• 
Sleep onset latency: ↓ ≥ 10 min or ≥ 20% 
• 
N3 (slow-wave sleep): ↑ ≥ 5 % absolute or ≥ 20 min (without 
TST/REM loss) 
• 
Arousal index: ↓ ≥ 3–5 events/hour 
 
 
B. Subjective Criteria (Patient-Reported Outcomes) 
At least one of: 
• 
PSQI: ≥ 3-point reduction (MCID) 
• 
ISI: ≥ 6-point reduction (MCID) 
• 
ESS ≥ 2 points reduction in score  
 
 
C. Composite Responder Definition 
• 
Treatment Success Responder: meets both A (objective per stratum) 
and B (subjective). 
• 
Partial Physiological Responder: meets A only. 
• 
Subjective Responder: meets B only. 
• 
Non-Responder: meets neither. 
 

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CHAPTER V 
RESEARCH ETHICS 
Ethical approval approved the Research Ethics Committee of Universiti Kebangsaan 
Malaysia, FF-2026-126. All participants will provide written informed consent before 
enrolment. Participant confidentiality will be protected by coding all data. Participants 
can withdraw at any point without affecting their standard medical care. 
 
 

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CHAPTER VI 
PATIENT INFORMATION SHEET  
 
 
 
Research Title: 
SONATA Trial – Sleep Optimization with Acoustic Therapy: A Polysomnography-Based 
Pre-Post Study 
Purpose of Study: 
This study aims to evaluate the effects of daily sound therapy on sleep architecture 
using full-night polysomnography (PSG). The sound is delivered through a wearable 
device using personalized sound frequencies (e.g., pink noise). The study assesses the 
therapy’s effect on deep sleep (N3), sleep latency, efficiency, and insomnia symptoms, 
using questionnaires and PSG readings before and after 12 weeks of therapy. 
What will the study involve? 
Participation is voluntary. If you agree, you will undergo: 
- Two overnight sleep studies (polysomnography) 
- Wear a sound stimulation device for 1 hours in the morning and evening respectively 
daily for 12 weeks 
- Complete sleep-related questionnaires (PSQI, ISI, ESS) before and after therapy 
- Weekly check ins from researcher (support and monitoring) 
You will not receive sedatives or new medications for this study. Your usual medical care 
will not be affected. 
Benefits: 
• Potential improvement in sleep quality and duration 
• Non-pharmacological therapy with a low side-effect profile 
• Free use of a wearable sound stimulation device for the duration of the study 

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Risks: 
• Minor discomfort from wearing the sound device (Adjustment could be made to suit 
participant if required) 
• Possible ear irritation or skin reaction at the device site 
• No physical or invasive procedure will be performed 
• Might have risk of worsening sleep/headache/seizure and affect daily activities  
Do you have to take part? 
Participation in this study is voluntary. If you agree to take part, then you will be asked 
to sign the “Informed Consent Form”. You will be given a copy of the form and this 
Information Sheet.  
Data & Confidentiality: 
The data from this study will be made into a report which may be published. Access to 
the data is only by the research team and the REC UKM team. The data will be reported 
in a collective manner without reference to an individual. Hence your identity will be 
kept confidential. 
Payment and compensation 
You do not have to pay nor will you be paid to participate in this study. You do have to 
pay for the usual hospital charges.   
Right to Refuse or Withdraw: 
You may refuse or withdraw from the study at any point without affecting your medical 
care or relationship with the hospital.  
Who can I ask about the study? 
If you have any questions, you can direct them to the research team. You can also 
contact the REC UKM for clarifications.  
Dr. Ho Yun Nyen 
Department of Internal Medicine 
Hospital Canselor Tuanku Muhriz (HCTM), UKM 
Mobile : 017-4146071 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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CHAPTER VII 
INFORMED CONSENT FORM 
Research Title:  
SONATA Trial – Sleep Optimization with Acoustic Therapy: A Polysomnography-Based Pre-
Post Study  
 
Researcher’s Name:  
Prof. Dr. Mohamed Faisal Abdul Hamid / Dr. Azat Azrai Azmel / Dr. Mas Fazlin Jailaini / Dr. 
Ho Yun Nyen 
I, …………………………………………………………………, IC No: ……………………………….............,    
• Have read all the information in the Patient Information Sheet and understand the 
aim and purpose of this study. 
• I have been given enough time to think about it, and my questions have been 
answered satisfactorily. 
• Understand that I may freely withdraw from this study at any time without reason 
or repercussions. 
• Understand that anonymity will be ensured in the final write-up. 
I understand all the above and voluntarily agree to participate in this research study, 
follow the study procedures, and provide the necessary information as requested. 
……………………………………………           ……...……………………………………. 
Signature/Thumbprint                       Date 
 
 
……………………………………………            …………………………………………… 
Witness Signature                               Researcher Signature 
 
…………………………………………….             Ho Yun Nyen (941107-14-5782) 
Witness Name /IC no                            Researcher Name 
 
 
…………………………………………..             …………………………………………… 
Date                                                         Date 

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CHAPTER IX 
DATA COLLECTION SHEET 
Name: ______________________________ 
IC No: ______________________________ 
Contact: ____________________________ 
Age: ____________ Gender: M/ F 
Occupation: ________________________ 
Weight: ___________kg 
Comorbidities: _______________________ 
_________________________________________ 
_________________________________________ 
 
Baseline PSG Results: 
- N1: ____% N2: ____% N3: ____% REM: ____% TST: ____ mins AHI: _______ 
 
Post-Intervention PSG Results: 
- N1: ____% N2: ____% N3: ____% REM: ____% TST: ____ mins AHI: ________ 
 
PSG baseline and post-intervention 
 
N1 (%) 
N2 (%) 
N3(%) 
REM (%) 
TST 
(mins) 
AHI 
Pre 
therapy 
 
 
 
 
 
 
Post 
therapy 
 
 
 
 
 
 
 
Questionnaires: 
- ISI: ____ PSQI: ____ ESS: ____ 
Device Usage Log: ______________ 
 
 
 
ISI 
PSQI 
ESS 
Pre therapy 
 
 
 
Post therapy 
 
 
 

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CHAPTER X 
Gantt chart  
 
 
Progression 
/ Timeline  
 
Aug -
Oct 
2025 
  
Nov 
2025- 
Feb 
2026 
March 
2026- 
March 
2027 
April 
–June 
2027 
  
July –
Dec 
2027 
Jan 
2028 
  
Literature 
review & 
Preparation 
of Research 
proposal 
 
 
 
 
 
 
 
Approval of 
HCTM 
Research and 
Ethics 
Committee  
 
 
 
 
 
 
 
Patient 
recruitment  
 
 
 
 
 
 
 
Data entry 
and analysis  
 
 
 
 
 
 
 
Final result 
and 
manuscript 
submission  
 
 
 
 
 
 
 
Final report 
presentation  
 
 
 
 
 
 
 

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CHAPTER XII 
APPENDICES 
Appendices may include patient brochures, device instructions, additional forms, or letters. 
 
 

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Questionnaires used: 
Insomnia Severity Index (ISI) 
 
 
 

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Pittsburgh Sleep Quality Index (PSQI) 
 
 
 
 
 
 

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Epworth Sleepiness Scale (ESS) 
Would 
never 
nod off 
0 
Slight 
chance of 
nodding off 
1 
Moderate 
chance of 
nodding off 
2 
High chance 
of nodding off 
3 
Sitting and reading 
Watching TV 
Sitting, inactive, in a public place 
(e.g., in a meeting, theater, or 
dinner event) 
As a passenger in a car for an 
hour or more without stopping 
for a break 
Lying down to rest when 
circumstances permit 
Sitting and talking to someone 
Sitting quietly after a meal 
without alcohol 
In a car, while stopped for a few 
minutes in traffic or at a light 
 
 

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CHAPTER XII 
REFERENCES 
 
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5. 
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6. 
Leminen MM, Virkkala J, Saure E, Paajanen T, Zee PC, Santostasi G, et al. Enhanced 
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8. 
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9. 
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