Personalized Sleep Microclimate Intervention for Chronic Insomnia: An IoT-Driven Environmental Design and Validation Study
DOI:
https://doi.org/10.4108/eetpht.11.11066Keywords:
IoT, Environmental Design, Personalized Medicine, Thermoregulation, Sleep Microclimate, Chronic Insomnia.Abstract
INTRODUCTION: Chronic Insomnia Disorder (CID) is a common public health concern associated with physiological hyperarousal and impaired thermoregulation during sleep onset. Existing pharmacological and psychological treatments often overlook the importance of the sleep environment in facilitating physiological readiness for sleep.
OBJECTIVES: This study aims to evaluate the efficacy of a Personalized Microclimate Control (PMC) system—an IoT-driven, adaptive bedroom environmental intervention—in improving insomnia symptoms and objective sleep outcomes in individuals with CID.
METHODS: A randomized, controlled, parallel-group trial was conducted with 120 participants diagnosed with CID. Participants were assigned to either the PMC intervention group or a Standard Bedroom Environment (SBE) control group for 8 weeks. Real-time physiological data (skin temperature, HRV) were used to automatically adjust environmental parameters (temperature, light). Primary outcomes included Insomnia Severity Index (ISI) scores and objective Total Sleep Time (TST); secondary outcomes included Skin Temperature Drop Rate (STDR) and its correlation with symptom improvement.
RESULTS: The PMC group demonstrated significantly greater improvements across all outcomes compared with the SBE group. ISI scores decreased by 7.47 points in the PMC group versus 2.28 points in the SBE group. TST increased by 43.65 minutes compared to 12.73 minutes in the control group. The PMC system also produced a significantly higher STDR, which was strongly correlated with ISI reduction (r = –0.712, p < 0.001).
CONCLUSION: The findings provide strong evidence that IoT-based personalized environmental design is an effective and scalable non-pharmacological intervention for CID. By integrating smart technology, sleep medicine, and environmental science, the PMC system provides a user-centric and mechanistically supported approach to improving sleep in individuals with insomnia.
Downloads
References
[1] Kim SY, Lee KH, Jeon JE, Lee HY, You JH, Shin J, Seo MC, Seo WW, Lee YJ. Reduced prefrontal activation during cognitive control under emotional interference in chronic insomnia disorder. Journal of Sleep Research. 2025 Jun;34(3):e14383.
[2] Hafner M, Romanelli RJ, Yerushalmi E, Troxel WM. The societal and economic burden of insomnia in adults: an international study. Cambridge, UK: RAND Europe; 2023. Report No. RRA2166-1. [Online]. Available: https://www.rand.org/pubs/research_reports/RRA2166-1.html
[3] Harding EC, Franks NP, Wisden W. The temperature dependence of sleep. Frontiers in neuroscience. 2019 Apr 24;13:336.
[4] Biabani N, Birdseye A, Higgins S, Delogu A, Rosenzweig J, Cvetkovic Z, Nesbitt A, Drakatos P, Steier J, Kumari V, O’Regan D. The neurophysiologic landscape of the sleep onset: a systematic review. Journal of Thoracic Disease. 2023 Aug 14;15(8):4530.
[5] Ichiba T, Kawamura A, Nagao K, Kurumai Y, Fujii A, Yoshimura A, Yoshiike T, Kuriyama K. Periocular skin warming promotes sleep onset through heat dissipation from distal skin in patients with insomnia disorder. Frontiers in Psychiatry. 2022 May 4;13:844958.
[6] Yu DJ, Recchia F, Bernal JD, Yu AP, Fong DY, Li SX, Chan RN, Hu X, Siu PM. Effectiveness of exercise, cognitive behavioral therapy, and pharmacotherapy on improving sleep in adults with chronic insomnia: a systematic review and network meta-analysis of randomized controlled trials. InHealthcare 2023 Aug 4 (Vol. 11, No. 15, p. 2207). MDPI.
[7] Baniassadi A, Manor B, Yu W, Travison T, Lipsitz L. Nighttime ambient temperature and sleep in community-dwelling older adults. Science of The Total Environment. 2023 Nov 15;899:165623.
[8] Morita PP, Sahu KS, Oetomo A. Health monitoring using smart home technologies: scoping review. JMIR mHealth and uHealth. 2023 Apr 13;11:e37347.
[9] Luna-Navarro A, Loonen R, Juaristi M, Monge-Barrio A, Attia S, Overend M. Occupant-Facade interaction: a review and classification scheme. Building and Environment. 2020 Jun 15;177:106880.
[10] Lee T, Cho Y, Cha KS, Jung J, Cho J, Kim H, Kim D, Hong J, Lee D, Keum M, Kushida CA. Accuracy of 11 wearable, nearable, and airable consumer sleep trackers: prospective multicenter validation study. JMIR mHealth and uHealth. 2023 Nov 2;11(1):e50983.
[11] Wang C, Lee C, Shin H. Digital therapeutics from bench to bedside. NPJ digital medicine. 2023 Mar 10;6(1):38.
[12] Bandyopadhyay A, Bae C, Cheng H, Chiang A, Deak M, Seixas A, Singh J. Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine. Journal of Clinical Sleep Medicine. 2023 Oct 1;19(10):1823-33.
[13] Szymusiak R. Body temperature and sleep. Handbook of clinical neurology. 2018 Jan 1;156:341-51.
[14] Gonzalez J, Robinson L, Clemons N, Ordaz O, Lynch E, Thosar S, McHill A, Emens J, Shea S, Bowles N. Skin thermoregulation is associated with cardiac vagal tone during sleep onset. Physiology. 2023 May 1;38(S1):5792031.
[15] Tai Y, Obayashi K, Yamagami Y, Saeki K. Association between circadian skin temperature rhythms and actigraphic sleep measures in real-life settings. Journal of Clinical Sleep Medicine. 2023 Jul 1;19(7):1281-92.
[16] Nagy Z, Gunay B, Miller C, Hahn J, Ouf MM, Lee S, Hobson BW, Abuimara T, Bandurski K, André M, Lorenz CL. Ten questions concerning occupant-centric control and operations. Building and Environment. 2023 Aug 15;242:110518.
[17] Lehrer P, Kaur K, Sharma A, Shah K, Huseby R, Bhavsar J, Sgobba P, Zhang Y. Heart rate variability biofeedback improves emotional and physical health and performance: A systematic review and meta analysis. Applied psychophysiology and biofeedback. 2020 Sep;45(3):109-29.
[18] Xiao K, Huang Z, Xie R. Interpretable Feature Based Machine Learning for Automatic Sleep Detection Using Photoplethysmography: A Cross Disciplinary Approach to Health Management. BIG. D. 2025 Jan 1;2(1):1-9.
[19] Han JM, Estrella Guillén E, Liu S, Chen Y, Samuelson HW. Using explainable artificial intelligence to predict sleep interruptions from indoor environmental conditions: an empirical study. Building Research & Information. 2025 Apr 5:1-20.
[20] Rupp RF, Kim J, Toftum J, Brager G, de Dear R. Ten questions concerning the application of adaptive thermal comfort in mixed-mode buildings. Building and Environment. 2025 Jul 28:113490.
[21] Jiayi CH. Research on Ecological Co-creation Design Theory and Methodology for Future-oriented Sustainable Health Engineering. Green Design Engineering. 2024 Oct 1;1(1):20-32.
[22] Kong SD, Gordon CJ, Hoyos CM, Wassing R, D’Rozario A, Mowszowski L, Ireland C, Palmer JR, Grunstein RR, Shine JM, McKinnon AC. Heart rate variability during slow wave sleep is linked to functional connectivity in the central autonomic network. Brain Communications. 2023;5(3):fcad129.
[23] da Estrela C, McGrath J, Booij L, Gouin JP. Heart rate variability, sleep quality, and depression in the context of chronic stress. Annals of Behavioral Medicine. 2021 Feb 1;55(2):155-64.
[24] Bastien CH, Vallières A, Morin CM. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep medicine. 2001 Jul 1;2(4):297-307.
[25] Chase JD, Busa MA, Staudenmayer JW, Sirard JR. Sleep measurement using wrist-worn accelerometer data compared with polysomnography. Sensors. 2022 Jul 4;22(13):5041.
[26] Saeb S, Nelson BW, Barman P, Verma N, Allen H, de Zambotti M, Baker FC, Arra N, Sridhar N, Sullivan SS, Plowman S. Performance of the Verily Study Watch for measuring sleep compared to polysomnography. Frontiers in Sleep. 2024 Dec 13;3:1481878.
[27] Mitsuyama S, Sakamoto T, Nagasawa T, Kario K, Ozawa S. A pilot study to assess the origin of the spectral power increases of heart rate variability associated with transient changes in the R‐R interval. Physiological Reports. 2024 Jan;12(1):e15907.
[28] Haghayegh S, Khoshnevis S, Smolensky MH, Hermida RC, Castriotta RJ, Schernhammer E, Diller KR. Novel TEMPERATURE‐CONTROLLED sleep system to improve sleep: A p ROOF‐OF‐CONCEPT study. Journal of sleep research. 2022 Dec;31(6):e13662.
[29] Lin W, Li N, Yang L, Zhang Y. The efficacy of digital cognitive behavioral therapy for insomnia and depression: a systematic review and meta-analysis of randomized controlled trials. PeerJ. 2023 Oct 31;11:e16137.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Yuan Gao, Beiqi luo, Fangtian Ying
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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.
