| Author: | Chen, Yanyao |
| Title: | Sleep monitoring system based on optical fiber strain sensor |
| Advisors: | Yu, Changyuan (EEE) |
| Degree: | M.Sc. |
| Year: | 2024 |
| Department: | Department of Electrical and Electronic Engineering |
| Pages: | 49 pages : color illustrations |
| Language: | English |
| Abstract: | As technology advances, and living standards improve, individuals have a heightened expectation of scientific measurement and the improvement of their health conditions. Health monitoring can potentially benefit individuals by adjusting unhealthy life behaviors, preventing disease. Optical fibers are commonly used in data transmission. The optical fiber strain sensor is another novel application of optical fibers. This dissertation work describes a complete solution for data collection, data uploading, result display, and subsequent health analysis that can be performed based on the optical fiber strain sensor. Chapter 2 describes the optical fiber strain sensor based on a MZI design. Chapter 3 describes the circuit design and the simulation for this system. Chapter 4 describes the health system based on the FOS system. Chapter 5 describes the long-term data collection of Polysomnography (PSG), Electrocardiogram (ECG), and Ballistocardiogram (BCG). Chapter 6 describes how to label PSG and ECG data for sleeping stage judgment and some methods for correlation analysis and preprocessing of raw BCG data. Chapter 7 describes the design and result analysis of the sleeping stage algorithm based on BCG data. BCG is rarely used because of its complex collection. But acquiring health data with the optical fiber strain sensors is convenient, highly sensitive, and contactless. So, collecting BCG data with fiber optic sensors (FOS) for private or public use is an excellent solution. We believe that the solution will gain a massive market in the future. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 8290.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 9.19 MB | Adobe PDF | View/Open |
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