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SpiroSmart addresses these barriers with a low-cost mobile application that performs spirometry sensing using the phone’s built-in microphone. Evaluation on 52 subjects shows a mean 5.1% error versus a clinical spirometer for common lung-function measures. The approach supports pulmonologists in diagnosing obstructive lung ailments.",{"@graph":69,"@context":121},[70,84,104],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/spirosmart-using-a-microphone-to-measure-lung-function-on-a-mobile-phone/399628/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":98,"encodingFormat":97,"isAccessibleForFree":99,"interactionStatistic":100},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/spirosmart-using-a-microphone-to-measure-lung-function-on-a-mobile-phone/399628.png","ImageObject",300,407,{"name":92,"@type":93},"Bulrr","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-27",true,{"@type":101,"interactionType":102,"userInteractionCount":4},"InteractionCounter",{"@type":103},"ViewAction",{"@type":105,"mainEntity":106},"FAQPage",[107,113,117],{"name":108,"@type":109,"acceptedAnswer":110},"What problem does SpiroSmart aim to solve in home spirometry?","Question",{"text":111,"@type":112},"It targets cost and usability barriers that prevent widespread home spirometry adoption, and addresses the lack of coaching, feedback, and quality control in current portable devices.","Answer",{"name":114,"@type":109,"acceptedAnswer":115},"How does SpiroSmart measure lung function using a mobile phone?",{"text":116,"@type":112},"The user records a forced exhalation at the phone screen; the microphone captures audio that a server analyzes to estimate exhaled flow rate from sound envelope, frequency-domain resonance tracking, and linear-prediction white-noise gain.",{"name":118,"@type":109,"acceptedAnswer":119},"How accurate is SpiroSmart compared with a clinical spirometer?",{"text":120,"@type":112},"In a study with 52 subjects, SpiroSmart achieves a mean error of 5.1% when compared to a clinical spirometer for common lung-function measures.","https://schema.org",{"og:url":83,"og:type":123,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":125,"canonical":83},"index,follow",{"doc_id":127,"site_id":62},399628,1790499263,{"code":4,"msg":5,"data":130},{"doc_id":127,"user_id":131,"nickname":92,"user_avatar":132,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":133,"file_id":134,"file_url":135,"file_type":136,"file_size":137,"view_count":4,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":138,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":139,"faqs":140,"seo_title":141,"seo_description":67,"update_tm":128,"read_time":142},5909892115043,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","SpiroSmart: Using a Microphone to Measure Lung Function on a Mobile Phone  \nEric C. Larson1†, Mayank Goel2†, Gaetano Boriello2, Sonya Heltshe3, Margaret Rosenfeld3, Shwetak N. Patel 1,2  \n1Electrical Engineering, 2Computer Science & Engineering,  \nDUB Institute, University of Washington Seattle, WA 98195  \n{eclarson, mayankg, gaetano, [shwetak }@uw.edu](shwetak }@uw.edu)  \n3Seattle Children’s Hospital  \nCenter for Clinical and Translational Research 4800 Sand Point Way NE Seattle, WA 98105  \n{sonya.heltshe, [margaret.rosenfeld}@seattlechildrens.org](margaret.rosenfeld}@seattlechildrens.org)  \nABSTRACT  \nHome spirometry is gaining acceptance in the medical community because of its ability to detect pulmonary exacerbations and improve outcomes of chronic lung ailments. However, cost and usability are significant barriers to its widespread adoption. To this end, we present SpiroSmart, a low-cost mobile phone application that performs spirometry sensing using the built-in microphone. We evaluate SpiroSmart on 52 subjects, showing that the mean error when compared to a clinical spirometer is 5.1% for common measures of lung function. Finally, we show that pulmonologists can use SpiroSmart to diagnose varying degrees of obstructive lung ailments.  \nAuthor Keywords  \nHealth sensing, spirometry, mobile phones, signal processing, machine learning.  \nACM Classification Keywords  \nH5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous.  \nINTRODUCTION  \nSpirometry is the most widely employed objective measure of lung function [37] and is central to the diagnosis and management of chronic lung diseases, such as asthma, chronic obstructive pulmonary disease (COPD), and cystic fibrosis. During a spirometry test, a patient forcefully exhales through a flow-monitoring device (a tube or mouthpiece), which measures instantaneous flow and cumulative exhaled volume (Figure 1) . Spirometry is generally performed in medical offices and clinics using conventional spirometers, but home spirometry with portable devices is slowly gaining acceptance [6,26] . Measurement of spirometry at home allows patients and physicians to more regularly monitor for trends and detect changes in lung function that may need evaluation and/or treatment. Home spirometry has the potential to result in earlier treatment of exacer  \nPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.  \nUbiComp’ 12, Sep 5 – Sep 8, 2012, Pittsburgh, USA. Copyright 2012 ACM 978-1-4503-1224-0/12/09...$15.00.  \nFigure 1. Subjects using SpiroSmart (left) and a clinical spirometer (right) and example curves from each device.  \nbations, more rapid recovery, reduced health care costs, and improved outcomes [15,23,34,35] . However, challenges currently faced by home spirometry are cost, patient compliance and usability, and an integrated method for uploading results to physicians [9,12] . Importantly, while officebased spirometry is coached by a trained technician, current home spirometers have no coaching, feedback, or quality control mechanisms to ensure acceptable measurements. In this paper, we present SpiroSmart, a smartphone-based approach that measures lung function using the phone’s built-in microphone (i.e., a complete software-enabled solution) . SpiroSmart requires the user to hold the smartphone at approximately arm’s length, breathe in their full lung volume, and forcefully exhale at the screen of the phone until the entire lung volume is expelled. The phone’s microphone records the exhalation and sends the audio data toa server, which calculates the exhaled flow rate by estimating models of the user’s vocal tract and t","cbCaipKDV9li6IdN","https://ap.wps.com/l/cbCaipKDV9li6IdN","pdf",1269209,"English","# Introduction\n## Method overview\n## Evaluation and diagnostic use","[{\"question\":\"What problem does SpiroSmart aim to solve in home spirometry?\",\"answer\":\"It targets cost and usability barriers that prevent widespread home spirometry adoption, and addresses the lack of coaching, feedback, and quality control in current portable devices.\"},{\"question\":\"How does SpiroSmart measure lung function using a mobile phone?\",\"answer\":\"The user records a forced exhalation at the phone screen; the microphone captures audio that a server analyzes to estimate exhaled flow rate from sound envelope, frequency-domain resonance tracking, and linear-prediction white-noise gain.\"},{\"question\":\"How accurate is SpiroSmart compared with a clinical spirometer?\",\"answer\":\"In a study with 52 subjects, SpiroSmart achieves a mean error of 5.1% when compared to a clinical spirometer for common lung-function measures.\"}]","SpiroSmart - Using a Microphone to Measure Lung Function on a Mobile Phone | PDF",25]