Efficacy and Accuracy of an AI-Driven Sleep Earbud for Chronic Insomnia

This study evaluates a new smart sleep earbud designed to help adults suffering from chronic insomnia. The device uses artificial intelligence (AI) to track a user's real-time heart rate and movement through the ear canal, automatically adjusting soothing music parameters to help the user fall asleep faster and achieve deeper sleep. Participants will spend three consecutive nights in a hospital sleep laboratory. The first night serves as a baseline screening using medical-grade sleep tracking (polysomnography) to rule out other hidden sleep conditions like sleep apnea. On the second and third nights, participants will test two different audio options in a randomized order: the AI-driven adaptive music and standard, non-adjusting music. Researchers will compare the earbud's internal sensor data against the hospital's clinical equipment to verify the earbud's tracking accuracy, and participants will complete brief touch-screen brain function tests each morning. Following the lab phase, participants will continue using the earbuds in their natural home environment for two weeks before a final check-up. The goal is to determine if personalized, AI-adjusted sound therapy can effectively treat insomnia symptoms and if a consumer ear-worn device can monitor sleep architecture as accurately as a clinical hospital system.

Inclusion Criteria * Aged 18 to 55 years (inclusive). * Able to understand the study protocol and voluntarily sign the informed consent form. * Meets the diagnostic criteria for chronic insomnia disorder according to the International Classification of Sleep Disorders, Third Edition (ICSD-3) or DSM-5. * Duration of insomnia symptoms is greater than 3 months but less than 2 years. * Insomnia Severity Index (ISI) total score \> 8 (indicating mild or greater clinical insomnia). * Currently drug-free status: No use of any prescription or over-the-counter medications that affect sleep (including sedatives, hypnotics, antidepressants, antihistamines, or traditional Chinese medicine sleep aids) for at least 2 weeks (or more than 5 drug half-lives) prior to enrollment. * Owns a smartphone and is capable of operating mobile applications to complete electronic questionnaires. * Willing and able to tolerate wearing earplugs or earbuds during sleep. Exclusion Criteria * Comorbid primary sleep disorders: Diagnosed via screening (STOP-Bang questionnaire) or polysomnography (PSG) with moderate-to-severe obstructive sleep apnea (OSA, defined as Apnea-Hypopnea Index $\\ge$ 15), narcolepsy, periodic limb movement disorder (PLMD), or other sleep disorders that could interfere with sleep quality assessments. * Severe psychiatric or psychological conditions: A Patient Health Questionnaire (PHQ-9) score \> 10 or a Generalized Anxiety Disorder scale (GAD-7) score \> 10. * History of schizophrenia, bipolar disorder, major depressive disorder, or active suicidal ideation. * Active substance abuse or dependence: History of alcohol abuse (exceeding 14 standard drinks per week) or illicit drug use within the past 3 months. * Comorbid somatic medical conditions: Severe or unstable physical illnesses (e.g., severe heart failure, malignant tumors, chronic pain) or neurological disorders known to impair sleep monitoring accuracy. * Active ear diseases, ear canal discharge, structural abnormalities, or a history of related otologic surgeries that prevent or restrict earbud placement. * Known history of hypersensitivity or allergic reactions to silicone or plastic materials. * Disruptive lifestyle factors: Current engagement in shift work schedules or travel across more than 3 time zones within 2 weeks prior to study entry. * Inability to provide independent informed consent or successfully complete cognitive testing due to profound language or cognitive barriers.