研究目的
To develop a non-invasive smart monitoring system using multi-core fiber optic interferometers for detecting body activities (on the bed, off the bed, body movement) and respiration rate during sleep, addressing the need for user-friendly and secure health monitoring for elderly individuals.
研究成果
The smart monitoring system based on multi-core fiber-optic interferometers successfully detects three body activities (off the bed, on the bed, body movement) and calculates respiration rate (e.g., 8 bpm). It offers advantages such as light weight, compact construction, electromagnetic immunity, and non-invasive operation, making it suitable for elderly health monitoring. Future work could focus on enhancing algorithm robustness and testing in varied environments.
研究不足
The system's performance may be limited by the sensitivity of the fiber sensor to micro-strain and environmental factors. Optimization of fiber lengths and coupling efficiency is required, and the system's accuracy in diverse real-world scenarios needs further validation.
1：Experimental Design and Method Selection:
The system uses a fiber-optic interferometer based on a seven-core fiber (SCF) sandwiched between multi-mode fibers (MMF) to create interference among cores. An algorithm is optimized to process collected data for activity identification and respiration rate calculation.
2：Sample Selection and Data Sources:
Data is collected from users on a bed using the fiber sensor embedded in the mattress, with signals representing body activities and respiration.
3：List of Experimental Equipment and Materials:
Includes a laser source (Amonics, 1550nm DFB Laser Source), attenuator, MSM fiber sensor (SMF-MMF-SCF-MMF-SMF), photodetector (PD), data acquisition (DAQ) card, computer, fusion splicer (Fujikura LZM-100), optical spectrum analyzer (YOKOGAWA, AQ6370), SCF from YOFC, and MMF.
4：Experimental Procedures and Operational Workflow:
Fabricate the interferometer by splicing SCF to MMF using a fusion splicer. Set up the system with laser source, attenuator, MSM sensor, PD, DAQ card, and computer. Collect light intensity signals at 200 Hz sampling rate. Process data using algorithms to extract jitter levels and apply Fast Fourier Transform (FFT) for respiration frequency.
5：Data Analysis Methods:
Use an algorithm to extract jitter levels from raw data for activity classification and FFT to determine respiration rate from frequency peaks.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容-
Fusion Splicer
LZM-100
Fujikura
Used to splice the SCF to MMF in the fabrication of the interferometer.
暂无现货
预约到货通知
-
Optical Spectrum Analyzer
AQ6370
YOKOGAWA
Used to observe the output interference spectrum of the MSM structure.
立即获取同款设备
-
Laser Source
1550nm DFB Laser Source
Amonics
Provides the light source for the interferometer system.
暂无现货
预约到货通知
-
Photodetector
Converts light intensity signals to electrical signals for data acquisition.
暂无现货
预约到货通知
-
Data Acquisition Card
Collects data from the photodetector at a specified sampling rate.
暂无现货
预约到货通知
-
Seven-Core Fiber
YOFC
Used as the sensing element in the interferometer for multi-core interference.
暂无现货
预约到货通知
-
Multi-Mode Fiber
Used to expand and couple light beam into the SCF cores.
暂无现货
预约到货通知
-
Attenuator
Adjusts the light intensity in the experimental setup.
暂无现货
预约到货通知
-
登录查看剩余6件设备及参数对照表
查看全部
