Sleep State Monitoring System Based on Flexible Pressure Sensor Arrays for Evaluating Sleep Quality
Evaluating sleep quality through monitoring sleep state is crucial for improving the general public’s sleep health. This article proposes a sleep state monitoring system based on flexible pressure sensor arrays, hardware circuits, and intelligent algorithms, which can effectively evaluate sleep quality by monitoring sleeping posture and breathing state. A flexible capacitive pressure sensor array designed specifically for monitoring sleeping posture, which is based on a dust-free cloth substrate and a sponge dielectric layer with multiple layers of microstructure, manufactured using electrospinning technology. In addition, we have developed a three-layer core-shell linear fiber structure flexible capacitive sensor for monitoring breathing state based on wet spinning technology. These soft and biocompatible wearable sensor arrays are connected to signal acquisition circuits, which can wirelessly transmit data on sleeping posture and breathing state to the PC in real time for efficient monitoring. We also constructed a model based on multiclassification support vector machine (SVM) to recognize four sleeping postures, including supine state, prone state, left lying, and right lying, with an accuracy rate of up to 96%. Finally, a comprehensive analysis of sleeping posture and breathing state can provide a comprehensive evaluation of sleep quality and targeted sleep improvement suggestions based on monitoring results. The designed sleep state monitoring system can not only provide long-term sleep data for medical professionals but also provide important information for the diagnosis of patients with sleep disorders.
Authors
- Liangsong Huang (ORCID: https://orcid.org/0000-0003-2833-7150)
- Si Wu (ORCID: https://orcid.org/0000-0002-9757-0629)
- Shuo Wang (ORCID: https://orcid.org/0000-0002-8294-7817)
- Peng Zhang (ORCID: https://orcid.org/0000-0002-2137-8913)
- Yuxia Li (ORCID: https://orcid.org/0000-0003-1068-6387)
- Kun Zhang (ORCID: https://orcid.org/0000-0001-7339-5056)
- Tengteng Su
Institutions
- Qingdao University (CN)
- Affiliated Hospital of Qingdao University (CN)
- Shandong University of Science and Technology (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2024-09-09
- DOI
- https://doi.org/10.1109/jsen.2024.3452940
- Citations
- 11
- Primary Topic
- Sleep and Work-Related Fatigue
- Type
- article
- Field-Weighted Citation Impact
- 5.58
Funders
- National Natural Science Foundation of China