Wearable Optical Fiber Beat Frequency Digital Sensing System for Real-Time Non-Invasive Multiple Human Physiological Parameters Monitoring

An optical fiber beat frequency sensing system (BFSS) for multiple human physiological parameters monitoring is proposed. To the best of the authors' knowledge, this is the first BFSS ever reported for multiple human physiological parameters monitoring. By utilizing both fiber Bragg grating (FBG) and fiber laser sensor, not only a low frequency vibration detection with the lowest detectable frequency of 0.25 Hz can be achieved for respiration, heartbeat and pulse signals monitoring, but also human body temperature can be monitored at the same time. Two kinds of beat frequency signals (BFS) are generated in the sensing systems including both polarization laser modes' beat frequency (PMBF) signals and longitudinal mode beat frequency (LMBF) signals. The PMBF signal is utilized for respiration, heartbeat and pulse signals monitoring. Variational mode decomposition (VMD) algorithm is utilized to decompose the monitored time-frequency PMBF signals into single-component respiration, heartbeat and pulse signals. The central frequencies of those signals are obtained by fast Fourier transform (FFT). The LMBF signal is utilized for human body temperature sensing. Measurement results demonstrate that the wearable optical fiber beat frequency digital monitoring system has a simple structure, high signal-to-noise ratio (SNR), stability, accuracy and muti-parameters sensing capability including respiration, heartbeat, pulse and human body temperature without mutual interference.

Automated summary

An optical fiber beat frequency sensing system for monitoring multiple human physiological parameters is proposed, which utilizes FBG and fiber laser sensor to achieve detection of respiration, heartbeat, pulse signals and human body temperature without interference. The system generates two types of beat frequency signals, PMBF for respiration, heartbeat and pulse signals monitoring, and LMBF for human body temperature sensing. The system demonstrates high SNR, stability, accuracy, and capability for multi-parameters sensing.