Fiber-Optic Interferometry-Based Heart Rate Monitoring

• Published in: IEEE transactions on instrumentation and measurement Vol. 71; pp. 1 - 15
• Main Authors: Jaros, Rene, Nedoma, Jan, Kepak, Stanislav, Martinek, Radek
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biomedical measurement; Empirical mode decomposition (EMD); fiber optic; Fiber optics; filtration; Heart rate; heart rate (HR) estimation; interferometry; Mach–Zehnder interferometer (MZI); Optical interferometry; Phonocardiography; Probes; Sagnac interferometers; Sensors; Signal processing; wavelet transform (WT)
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2022.3178495

The application of fiber-optic-based sensors, especially in the magnetic resonance (MR) environment and the sleep laboratory, has become an intensely discussed topic. Although these sensors offer significant benefits, their practical deployment has two very challenging issues-it is necessary to find a suitable way to construct and encapsulate sensors, and it is also required to ensure that an appropriate advanced signal processing method is chosen. This study focuses on the latter area, aiming to apply advanced methods of processing measured biosignals obtained from fiber-optic sensors that use light interference for their function. These sensors are characterized by the fact that we can classify the measured biosignals as phonocardiography (PCG). This article describes in length the determination of a patient's heart rate (HR) as a basic parameter determining his or her state of health. The study is based on results collected from 11 test subjects (five females and six males), using the following three testing methods: empirical mode decomposition (EMD), complete ensemble EMD with adaptive noise (CEEMDAN), and wavelet transform (WT). The evaluation was conducted by determining the probability of correct detection with the use of overall accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and the harmonic mean between SE and PPV (<inline-formula> <tex-math notation="LaTeX">F1 </tex-math></inline-formula>). The functionality of the system was verified against the relevant reference in the form of simultaneously measured electrocardiograms (ECGs), from which reference annotations were estimated. This work showed that WT seems to be a suitable method, when, for all 11 tested signals, it achieved an ACC of >95%, based on the evaluation parameters, and at the same time, its computational complexity was the lowest of the tested methods.