This paper is in the following e-collection/theme issue:

Biomedical Engineering Reviews (12) Telehealth and Telemonitoring (1671) mHealth for Wellness, Behavior Change and Prevention (2871) Insomnia and Sleep Hygiene (167) Sleep Monitoring, Sleep Quality, Sleep Disorders (183)

Published on in Vol 5, No 1 (2020): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20921, first published .
Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review

Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review

Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review

Authors of this article:

Qiang Pan1 Author Orcid Image ;   Damien Brulin1 Author Orcid Image ;   Eric Campo1 Author Orcid Image
Article Authors Cited by (31) Tweetations (3) Metrics

Journals

  1. Pan Q, Brulin D, Campo E. Home sleep monitoring based on wrist movement data processing. Procedia Computer Science 2021;183:696 View
  2. Farooq A, Zhang P. A comprehensive review on the prospects of next-generation wearable electronics for individualized health monitoring, assistive robotics, and communication. Sensors and Actuators A: Physical 2022;344:113715 View
  3. Pan Q, Brulin D, Campo E. Evaluation of a Wireless Home Sleep Monitoring System Compared to Polysomnography. IRBM 2023;44(2):100735 View
  4. Sadek I, Abdulrazak B. Contactless remote monitoring of sleep: evaluating the feasibility of an under-mattress sensor mat in a real-life deployment. Health Systems 2023;12(3):264 View
  5. Siyanbade J, Abdulrazak B, Sadek I. Unobtrusive Monitoring of Sleep Cycles: A Technical Review. BioMedInformatics 2022;2(1):204 View
  6. Hussain Z, Sheng Q, Zhang W, Ortiz J, Pouriyeh S. Non-invasive Techniques for Monitoring Different Aspects of Sleep: A Comprehensive Review. ACM Transactions on Computing for Healthcare 2022;3(2):1 View
  7. Pan Q, Brulin D, Campo E. Wrist movement analysis for long-term home sleep monitoring. Expert Systems with Applications 2022;187:115952 View
  8. Chouraki A, Tournant J, Arnal P, Pépin J, Bailly S. Objective multi-night sleep monitoring at home: variability of sleep parameters between nights and implications for the reliability of sleep assessment in clinical trials. SLEEP 2023;46(5) View
  9. Radhakrishnan B, Kirubakaran E, Jebadurai I, Selvakumar A, Peter J. Efficacy of Single-Channel EEG: A Propitious Approach for In-home Sleep Monitoring. Frontiers in Public Health 2022;10 View
  10. Radhakrishnan B. L. , Ezra K, Jebadurai I. Feature Extraction From Single-Channel EEG Using Tsfresh and Stacked Ensemble Approach for Sleep Stage Classification. International Journal of e-Collaboration 2023;19(3):1 View
  11. Zhong L, He S, Lin J, Wu J, Li X, Pang Y, Li Z. Technological Requirements and Challenges in Wireless Body Area Networks for Health Monitoring: A Comprehensive Survey. Sensors 2022;22(9):3539 View
  12. Ying S, Wang L, Zhao Y, Ma M, Ding Q, Xie J, Yao D, Mitra S, Chen M, Liu T. A Novel In-Home Sleep Monitoring System Based on Fully Integrated Multichannel Front-End Chip and Its Multilevel Analyses. IEEE Journal of Translational Engineering in Health and Medicine 2023;11:211 View
  13. Haghi M, Asadov A, Boiko A, Ortega J, Martínez Madrid N, Seepold R. Validating Force Sensitive Resistor Strip Sensors for Cardiorespiratory Measurement during Sleep: A Preliminary Study. Sensors 2023;23(8):3973 View
  14. Wenjian W, Qian X, Jun X, Zhikun H. DynamicSleepNet: a multi-exit neural network with adaptive inference time for sleep stage classification. Frontiers in Physiology 2023;14 View
  15. Jang H, Lee S, Son Y, Seo S, Baek Y, Mun S, Kim H, Kim I, Kim J. Exploring Variations in Sleep Perception: Comparative Study of Chatbot Sleep Logs and Fitbit Sleep Data. JMIR mHealth and uHealth 2023;11:e49144 View
  16. Kwon S, Kim H, Kwon K, Kim H, Kim Y, Lee S, Kwon Y, Jeong J, Trotti L, Duarte A, Yeo W. At-home wireless sleep monitoring patches for the clinical assessment of sleep quality and sleep apnea. Science Advances 2023;9(21) View
  17. Boiko A, Gaiduk M, Scherz W, Gentili A, Conti M, Orcioni S, Martínez Madrid N, Seepold R. Monitoring of Cardiorespiratory Parameters during Sleep Using a Special Holder for the Accelerometer Sensor. Sensors 2023;23(11):5351 View
  18. Li L, Yang C, Wang Z, Xiao K, Min R. Stretchable polymer optical fiber embedded in the mattress for respiratory and heart rate monitoring. Optics & Laser Technology 2024;171:110356 View
  19. Nagele A, Hough J. “The sleep data looks way better than I feel.” An autoethnographic account and diffractive reading of sleep-tracking. Frontiers in Computer Science 2024;6 View
  20. Haghi M, Madrid N, Seepold R. In-Home, Smart Sleep Monitoring System for Cardiorespiratory Estimation and Sleep Apnea Detection: Proof of Concept. IEEE Sensors Journal 2024;24(8):13364 View
  21. Braun M, Stockhoff M, Tijssen M, Dietz-Terjung S, Coughlin S, Schöbel C. A Systematic Review on the Technical Feasibility of Home-Polysomnography for Diagnosis of Sleep Disorders in Adults. Current Sleep Medicine Reports 2024;10(2):276 View
  22. Huang J, Cai Y, Xie G, Xu X, Geng Z, Jiang Y, Su Y. Hierarchical carbon nanotube-decorated polyacrylonitrile smart textiles for wearable biomonitoring. Wearable Electronics 2024;1:180 View
  23. Hong W. Twistable and Stretchable Nasal Patch for Monitoring Sleep-Related Breathing Disorders Based on a Stacking Ensemble Learning Model. ACS Applied Materials & Interfaces 2024;16(36):47337 View
  24. Haghi M, Gaiduk M, Stoffers M, TaheriNejad N, Penzel T, Madrid N, Seepold R. Evolution of Bed-Based Sensor Technology in Unobtrusive Sleep Monitoring: A Review. IEEE Sensors Journal 2024;24(19):29545 View
  25. Acosta C, Ye Y, Wong K, Zhao Y, Lawrence J, Towell M, D’Oyley H, Mackay-Dunn M, Chow B, Hung L. Implementing AI-Driven Bed Sensors: Perspectives from Interdisciplinary Teams in Geriatric Care. Sensors 2024;24(21):6803 View

Books/Policy Documents

  1. Hand R, Cleland I, Nugent C, Synnott J. Pervasive Computing Technologies for Healthcare. View
  2. Adil H, Adil M, Raghuwanshi S, Gupta A. Machine Learning and Metaheuristics: Methods and Analysis. View
  3. Wyawahare M, Bhole R, Bobade V, Chavan A, Dehankar S. Proceedings of International Conference on Paradigms of Communication, Computing and Data Analytics. View