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A Three-Arm Randomized Controlled Trial of Cross-Modal Digital Health System Integrated with Cognitive Behavioral Therapy for Insomnia: Neurophysiological Mechanisms and Clinical Efficacy

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  • @ARTICLE{10.4108/eetpht.11.11044,
        author={Caihong He and Siyu Ying and Yadong Xu and Fangtian Ying},
        title={A Three-Arm Randomized Controlled Trial of Cross-Modal Digital Health System Integrated with Cognitive Behavioral Therapy for Insomnia: Neurophysiological Mechanisms and Clinical Efficacy},
        journal={EAI Endorsed Transactions of Pervasive Health and Technology},
        volume={11},
        number={1},
        publisher={EAI},
        journal_a={PHAT},
        year={2026},
        month={1},
        keywords={cross-modal integration, predictive coding, CBT-I, insomnia disorder, neurophysiology},
        doi={10.4108/eetpht.11.11044}
    }
    
  • Caihong He
    Siyu Ying
    Yadong Xu
    Fangtian Ying
    Year: 2026
    A Three-Arm Randomized Controlled Trial of Cross-Modal Digital Health System Integrated with Cognitive Behavioral Therapy for Insomnia: Neurophysiological Mechanisms and Clinical Efficacy
    PHAT
    EAI
    DOI: 10.4108/eetpht.11.11044
Caihong He1,*, Siyu Ying2, Yadong Xu3, Fangtian Ying1
  • 1: Macau University of Science and Technology
  • 2: The University of Queensland
  • 3: Xiamen Dongyan Xiaochu Network Technology co., LTD
*Contact email: hch01prima@163.com

Abstract

INTRODUCTION: Insomnia Disorder is a global public health problem. Cognitive behavioral therapy for insomnia (CBT-I), as the gold standard for combating insomnia, still has limitations such as low patient adherence and inability to directly intervene in physiological hyperarousal. Traditional sensory interventions lack precise, mechanism-driven designs, making it difficult to effectively suppress this hyperarousal. This study aims to address these limitations by developing a non-pharmacological intervention based on predictive coding theory (PCT) and multi-sensory integration. OBJECTIVES: This study developed a Cross-Modal Digital Health System (CMDH-I) that combines CBT-I principles with personalized, synchronized auditory, visual, and vibro-tactile stimulation, and dynamically modulates the intervention process through a closed-loop control mechanism driven by real-time heart rate variability (HRV) biofeedback. The primary objectives include evaluating the clinical efficacy of CMDH-I combined with CBT-I on objective sleep latency (SL) and subjective sleep quality (PSQI). Furthermore, the study aims to explore the underlying neurophysiological mechanisms, particularly the regulatory role of heart rate variability (HRV-RMSSD) and changes in electroencephalogram (EEG) power spectral density. METHODS: A 6-week, double-blind, three-arm randomized controlled trial (RCT) was conducted on 90 patients with primary insomnia. Participants were randomly assigned to one of three groups: (1) CBT-I + True CMDH-I; (2) CBT-I + Sham CMDH-I (stimulus asynchrony); and (3) CBT-I standard control group. The primary outcomes were objective sleep latency (SL) and subjective sleep quality (PSQI). Secondary outcomes included neurophysiological parameters: electroencephalogram power spectral density (δ/σ wave) and heart rate variability (HRV-RMSSD). RESULTS: The reduction in SL and PSQI scores in the True CMDH-I group was significantly greater than that in the other two groups, exceeding the lowest clinically significant difference (MCID) (p < 0.001). More importantly, mediation analysis showed that the improvement in HRV-RMSSD was one of the main mechanisms by which CMDH-I improved sleep quality, accounting for 58.1% of the total effect. In addition, the increase in frontal lobe EEG delta wave power was closely associated with the increase in HRV-RMSSD (r=0.68), which validated the hypothesis of the vagus-thalamus-cortex pathway proposed in this study. CONCLUSION: CMDH-I is a closed-loop, cross-modal digital health system based on PCT. As a non-pharmacological intervention for sleep disorders, this system outperforms standard CBT-I in clinical efficacy. The research results provide empirical evidence that the system's therapeutic effect is achieved through enhanced parasympathetic activity (increased HRV-RMSSD), thus validating its precise neurophysiological mechanism of sleep regulation. This study establishes a clearly defined digital treatment system, providing objective physiological indicators for personalized sleep medicine and representing a significant advancement

Keywords
cross-modal integration, predictive coding, CBT-I, insomnia disorder, neurophysiology
Received
2025-11-22
Accepted
2025-12-14
Published
2026-01-13
Publisher
EAI
http://dx.doi.org/10.4108/eetpht.11.11044

Copyright © 2026 Caihong He et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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