Non-invasive systems for sleep monitoring: Respiratory rate and sleep posture classification

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Authors

  • Tran Duc Nghia Institute of Information Technology, Vietnam Academy of Science and Technology
  • Vi Manh Tuyen (Corresponding Author) Faculty of Electrical and Electronic Engineering, Phenikaa University
  • Pham Quang Huy Electric Power University
  • Tran Duc Tan Graduate University of Science and Technology, Vietnam Academy of Science and Technology

DOI:

https://doi.org/10.54939/1859-1043.j.mst.104.2025.3-14

Keywords:

Accelerometer; Respiratory rate; Sleep position; CNN.

Abstract

Sleep plays an essential role in human health. Monitoring sleep has increasingly become an important tool for gaining deeper insights into sleep behavior and detecting related health issues. Polysomnography (PSG) in clinical settings is the gold standard for sleep analysis; however, it is expensive and challenging to implement over long periods. As a result, home-based sleep monitoring methods, particularly non-invasive sensor-based systems, are gaining significant attention. This paper focuses on reviewing recent studies related to non-invasive sleep monitoring systems, including both wearable and non-wearable methods. These systems are designed to continuously measure and monitor users' breathing patterns while also detecting and classifying their sleep postures. Additionally, the paper explores future directions for developing respiratory monitoring and sleep posture classification systems that can operate flexibly across different environments, including settings outside professional medical facilities.

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Published

25-06-2025

How to Cite

[1]
P. T. Tran Duc, Vi Manh Tuyen, Pham Quang Huy, and Tran Duc Tan, “Non-invasive systems for sleep monitoring: Respiratory rate and sleep posture classification”, JMST, vol. 104, no. 104, pp. 3–14, Jun. 2025.

Issue

Vol. 104 (2025)

Section

Overview