Inhalation motion analysis and visualization of error areas using two IMU sensors

Inhalation motion analysis and visualization of error areas using two IMU sensors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Inhalation motion analysis and visualization of error areas using two IMU sensors Atsushi Hasegawa, Tomoyuki Shimono, Katsunori Masaki, Shunya Takano, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3977630/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper proposes an inhaler-use behavior evaluation method that uses inertial sensors to monitor patients with bronchial asthma and chronic obstructive pulmonary disease (COPD). COPD is common disease, and the accurate use of inhalers is vital to controlling its symptoms. However, many patients improperly use their inhalers. Hence, by augmenting an Ellipta™ inhaler with inertial measurement units, this study evaluates patient inhalation motions using the acquired motion data. Compared with conventional methods, ours is less affected by external factors, such as sound and temperature, and it can be applied outside clinical settings. Specifically, a linear discriminant analysis algorithm is provided for selecting characteristic variables for each error type, and a judgment method using these variables is proposed. A dynamic programming matching algorithm is then applied to determine correctness. Experimental results show that our method provides high discriminant accuracy, and it accounts for the similarity of waveforms, which allows us to visualize errors, unlike contemporary methods. We expect that our inhalation method and the accompanying dataset will offer valuable guidance for future research as well as useful feedback to patients. Physical sciences/Engineering Physical sciences/Engineering/Electrical and electronic engineering Health sciences/Health care Health sciences/Health care/Patient education Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3977630","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":276339071,"identity":"08d0e5e8-809a-4549-849f-7bf5f987e736","order_by":0,"name":"Atsushi Hasegawa","email":"","orcid":"","institution":"Yokohama National University","correspondingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Hasegawa","suffix":""},{"id":276339072,"identity":"6d37c78d-ff4e-4c2f-9c09-6a17d6611b26","order_by":1,"name":"Tomoyuki 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COPD is common disease, and the accurate use of inhalers is vital to controlling its symptoms. However, many patients improperly use their inhalers. Hence, by augmenting an Ellipta™ inhaler with inertial measurement units, this study evaluates patient inhalation motions using the acquired motion data. Compared with conventional methods, ours is less affected by external factors, such as sound and temperature, and it can be applied outside clinical settings. Specifically, a linear discriminant analysis algorithm is provided for selecting characteristic variables for each error type, and a judgment method using these variables is proposed. A dynamic programming matching algorithm is then applied to determine correctness. Experimental results show that our method provides high discriminant accuracy, and it accounts for the similarity of waveforms, which allows us to visualize errors, unlike contemporary methods. 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