Passive Photonic Integrated Circuits Elements Fabricated on a Silicon Nitride Platform.

The fabrication processes for silicon nitride photonic integrated circuits evolved from microelectronics components technology-basic processes have common roots and can be executed using the same type of equipment. In comparison to that of electronics components, passive photonic structures require fewer manufacturing steps and fabricated elements have larger critical dimensions. In this work, we present and discuss our first results on design and development of fundamental building blocks for silicon nitride integrated photonic platform. The scope of the work covers the full design and manufacturing chain, from numerical simulations of optical elements, design, and fabrication of the test structures to optical characterization and analysis the results. In particular, technological processes were developed and evaluated for fabrication of the waveguides (WGs), multimode interferometers (MMIs), and arrayed waveguide gratings (AWGs), which confirmed the potential of the technology and correctness of the proposed approach.

Photonic Integrated Interrogator for Monitoring the Patient Condition during MRI Diagnosis.

In this work, we discuss the idea and practical implementation of an integrated photonic circuit-based interrogator of fiber Bragg grating (FBG) sensors dedicated to monitoring the condition of the patients exposed to Magnetic Resonance Imaging (MRI) diagnosis. The presented solution is based on an Arrayed Waveguide Grating (AWG) demultiplexer fabricated in generic indium phosphide technology. We demonstrate the consecutive steps of development of the device from design to demonstrator version of the system with confirmed functionality of monitoring the respiratory rate of the patient. The results, compared to those obtained using commercially available bulk interrogator, confirmed both the general concept and proper operation of the device.

Deep learning-based method for the continuous detection of heart rate in signals from a multi-fiber Bragg grating sensor compatible with magnetic resonance imaging.

A method for the continuous detection of heart rate (HR) in signals acquired from patients using a sensor mat comprising a nine-element array of fiber Bragg gratings during routine magnetic resonance imaging (MRI) procedures is proposed. The method is based on a deep learning neural network model, which learned from signals acquired from 153 MRI patients. In addition, signals from 343 MRI patients were used for result verification. The proposed method provides automatic continuous extraction of HR with the root mean square error of 2.67 bpm, and the limits of agreement were -4.98-5.45 bpm relative to the reference HR.