Abstract

Current methods for continuous respiration monitoring such as respiratory inductive or optoelectronic plethysmography are limited to clinical or research settings; most wearable systems reported only measures respiration rate. Here we introduce a wearable sensor capable of simultaneously measuring both respiration rate and volume with high fidelity. Our disposable respiration sensor with a Band-Aid© like formfactor can measure both respiration rate and volume by simply measuring the local strain of the ribcage and abdomen during breathing. We demonstrate that both metrics are highly correlated to measurements from a medical grade continuous spirometer on participants at rest. Additionally, we also show that the system is capable of detecting respiration under various ambulatory conditions. Because these low-powered piezo-resistive sensors can be integrated with wireless Bluetooth units, they can be useful in monitoring patients with chronic respiratory diseases in everyday settings.

Highlights

  • Chronic respiratory disease (CRD) is a growing global health and economic burden

  • We showed that the strain sensors can calculate the respiration rate and volume based on the local changes in strain around the abdomen and ribcage with high fidelity

  • This follows the principles set by Kono and Mead, who reported that the mechanism for respiration has two degrees of freedom: the movement of the ribcage and movement of the abdomen

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Summary

Introduction

Chronic respiratory disease (CRD) is a growing global health and economic burden. Two common CRDs, asthma and chronic obstructive pulmonary disease (COPD), affect over 435 million people worldwide;[1] they each have an estimated medical cost of 50 billion dollars per year.[2,3] mostCRDs can be well controlled or even cured with proper monitoring and care.[1]. We demonstrate that it is possible to measure both respiration rate and volume using a disposable wearable strain sensor placed discreetly on the abdomen and ribcage (Fig. 1a). The relationship between the ΔR of the strain sensors and the hours while the data was recorded wirelessly through a Bluetooth exhalation volume generally followed a power regression model acquisition unit.

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