A Novel Magnetic Respiratory Sensor for Human Healthcare

TL;DR

This paper introduces a non-invasive magnetic sensor that accurately monitors breathing patterns and detects respiratory issues like COVID-19, offering a contactless solution for healthcare and home use.

Contribution

The study presents a novel magneto-LC resonance sensor capable of precise, contactless respiratory monitoring and disease detection, improving upon existing contact-based devices.

Findings

High sensitivity in detecting individual breathing patterns

Ability to identify respiratory-related diseases like COVID-19

Accurate measurement of breath strength and anomalies

Abstract

Breathing is vital to life. Therefore, the real-time monitoring of breathing pattern of a patient is crucial to respiratory rehabilitation therapies such as magnetic resonance exams for respiratory-triggered imaging, chronic pulmonary disease treatment, and synchronized functional electrical stimulation. While numerous respiratory devices have been developed, they are often in direct contact with a patient, which can yield inaccurate or limited data. In this study, we developed a novel, non-invasive, and contactless magnetic sensing platform that can precisely monitor breathing, movement, or sleep patterns of a patient, thus providing efficient monitoring at a clinic or home. A magneto-LC resonance (MLCR) sensor converts the magnetic oscillations generated by breathing of the patient into an impedance spectrum, which allows for a deep analysis of breath variation to identify respiratory-related diseases like COVID-19. Owing to its ultrahigh sensitivity, the MLCR sensor yields a distinct breathing pattern for each patient tested. The sensor also provides an accurate measure of the strength of breath at multiple stages as well as anomalous variations in respiratory rate and amplitude. This suggests that the MLCR sensor can detect symptoms of COVID-19 in a patient due to shortness of breath or difficulty breathing as well as track the progress of the disease in real time.