{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T00:21:28Z","timestamp":1758846088127,"version":"3.44.0"},"reference-count":54,"publisher":"Association for Computing Machinery (ACM)","issue":"3","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92467202, 62272216, 62372224, 62402217"],"award-info":[{"award-number":["92467202, 62272216, 62372224, 62402217"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20243040,BK20241377"],"award-info":[{"award-number":["BK20243040,BK20241377"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2025,9,3]]},"abstract":"<jats:p>Chronic respiratory conditions such as Chronic Obstructive Pulmonary Disease (COPD) and asthma often progress insidiously, making early detection vital for effective intervention. Current gold-standard Pulmonary Function Testing (PFT) methods, such as spirometry, evaluate lung function by measuring airflow rates to detect potential obstructions. But, their cost, often several hundred dollars or more, limits their accessibility for regular at-home monitoring. In this paper, we present SpiroSense, a novel system that transforms a smartphone into a portable, low-cost, and accurate PFT device for everyday use by integrating a custom 3D-printed attachment costing just a dozen dollars. However, a critical limitation arises from the smartphone's inherent audio sampling rate (typically 48kHz), which constrains the airflow resolution to 11.9L\/s when using conventional cross-correlation-based time delay estimation. This coarse resolution is insufficient to capture key pulmonary metrics, such as a Peak Expiratory Flow (PEF) of 10 L\/s, with high fidelity. To address this, we propose SonicFlow, which establishes a foundational airflow rate sensing model based on ultrasonic phase features and improves the airflow rate resolution to 0.148L\/s. Furthermore, airflow-induced high-frequency harmonic noise within the 3D-printed model, combined with ambient environmental noise, further complicates accurate sensing. To mitigate this, we introduce NoiseClear, an end-to-end ultrasonic signal enhancement model designed to effectively suppress noise while preserving critical airflow velocity information. We prototype SpiroSense and evaluate its performance on a cohort of 59 participants, including 29 healthy individuals and 30 patients. Experimental results show that SpiroSense achieves average estimation error of 6.44% for Forced Vital Capacity (FVC), 7.42% for Forced Expiratory Volume in one second (FEV1), and 3.01% for the FEV1\/FVC ratio.<\/jats:p>","DOI":"10.1145\/3749489","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T17:15:45Z","timestamp":1756919745000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["SpiroSense: Transforming Smartphones into Pulmonary Metrics Monitors with Ultrasonic Technology"],"prefix":"10.1145","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5184-2900","authenticated-orcid":false,"given":"Long","family":"Fan","sequence":"first","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2994-6743","authenticated-orcid":false,"given":"Lei","family":"Xie","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7579-5678","authenticated-orcid":false,"given":"Shiyuan","family":"Ma","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8207-1125","authenticated-orcid":false,"given":"Yanling","family":"Bu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1479-9023","authenticated-orcid":false,"given":"Chuyu","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2755-9802","authenticated-orcid":false,"given":"Weibang","family":"Pan","sequence":"additional","affiliation":[{"name":"Nanjing University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8093-5073","authenticated-orcid":false,"given":"Lu","family":"Ke","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1467-4519","authenticated-orcid":false,"given":"Sanglu","family":"Lu","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,9,3]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/JLT.2016.2627017"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/PROC.1963.2308"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376444"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447993.3483251"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3517258"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/PerCom45495.2020.9127380"},{"key":"e_1_2_1_7_1","unstructured":"Contec. 2024. CONTEC SP100A Spirometer. https:\/\/www.contecmed.com\/productinfo\/859505.html. [Accessed 15-01-2024]."},{"key":"e_1_2_1_8_1","unstructured":"Contec. 2024. CONTEC SP70B Spirometer. https:\/\/www.contecmed.com\/productinfo\/603431.html. [Accessed 15-01-2024]."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM199407073310107"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1183\/18106838\/breathe.4.3.251"},{"key":"e_1_2_1_11_1","volume-title":"Music Source Separation in The Waveform Domain. arXiv preprint arXiv:1911.13254","author":"D\u00e9fossez Alexandre","year":"2019","unstructured":"Alexandre D\u00e9fossez, Nicolas Usunier, L\u00e9on Bottou, and Francis Bach. 2019. Music Source Separation in The Waveform Domain. arXiv preprint arXiv:1911.13254 (2019)."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM53939.2023.10229085"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3659619"},{"volume-title":"Proc. of the 2016 CHI. 5675--5685","author":"Goel Mayank","key":"e_1_2_1_14_1","unstructured":"Mayank Goel, Elliot Saba, Maia Stiber, Eric Whitmire, Josh Fromm, Eric C. Larson, Gaetano Borriello, and Shwetak N. Patel. 2016. SpiroCall: Measuring Lung Function over a Phone Call. In Proc. of the 2016 CHI. 5675--5685."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201908-1590ST"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/WCSP58612.2023.10404383"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2024.3413955"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2023.3285869"},{"key":"e_1_2_1_19_1","volume-title":"Pathophysiology of Airflow Limitation in Chronic Obstructive Pulmonary Disease. The Lancet 364, 9435","author":"Hogg James C","year":"2004","unstructured":"James C Hogg. 2004. Pathophysiology of Airflow Limitation in Chronic Obstructive Pulmonary Disease. The Lancet 364, 9435 (2004), 709--721."},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM52122.2024.10621199"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3570361.3613290"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.nanolett.2c04228"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITC-CSCC62988.2024.10628365"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1021\/acssensors.2c00824"},{"volume-title":"Proc. of the ACM IMWUT. 280--289","author":"Larson Eric C.","key":"e_1_2_1_25_1","unstructured":"Eric C. Larson, Mayank Goel, Gaetano Boriello, Sonya Heltshe, Margaret Rosenfeld, and Shwetak N. Patel. 2012. SpiroSmart: using a microphone to measure lung function on a mobile phone. In Proc. of the ACM IMWUT. 280--289."},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3643832.3661889"},{"key":"e_1_2_1_27_1","first-page":"1","article-title":"Facial Landmark Detection Based on High Precision Spatial Sampling via Millimeter-wave Radar","volume":"8","author":"Li Yi","year":"2024","unstructured":"Yi Li, Chuyu Wang, Lei Xie, Qiancheng Jin, Long Fan, Jingyi Ning, and Sanglu Lu. 2024. Facial Landmark Detection Based on High Precision Spatial Sampling via Millimeter-wave Radar. Proc. of the ACM IMWUT 8, 4 (2024), 1--26.","journal-title":"Proc. of the ACM IMWUT"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1398-9995.2012.02821.x"},{"key":"e_1_2_1_29_1","unstructured":"Abadi Mart\u00edn Agarwal Ashish Barham Paul Brevdo Eugene Chen Zhifeng Citro Craig S Corrado Greg Davis Andy Dean Jeffrey Devin Matthieu et al. 2015. TensorFlow: Large-scale Machine Learning on Heterogeneous Systems."},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1136\/thx.47.11.904"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1378\/chest.123.6.1899"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/2742647.2742674"},{"volume-title":"Impulse Oscillometry System. https:\/\/intl.vyaire.com\/products\/ios-impulse-oscillometry. [Accessed","year":"2023","key":"e_1_2_1_33_1","unstructured":"n.d. 2023. Impulse Oscillometry System. https:\/\/intl.vyaire.com\/products\/ios-impulse-oscillometry. [Accessed 19 Nov. 2023]."},{"key":"e_1_2_1_34_1","volume-title":"Rabe","author":"Pauwels Romain A.","year":"2004","unstructured":"Romain A. Pauwels and Klaus F. Rabe. 2004. Burden and Clinical Features of Chronic Obstructive Pulmonary Disease (COPD). The Lancet 364, 9434 (2004), 613--620."},{"key":"e_1_2_1_35_1","first-page":"797","article-title":"Measuring Lung Function in Airways Diseases","volume":"74","author":"Petousi Nayia","year":"2019","unstructured":"Nayia Petousi, Nick P Talbot, Ian Pavord, and Peter A Robbins. 2019. Measuring Lung Function in Airways Diseases: Current and Emerging Techniques. Thorax 74, 8 (2019), 797--805.","journal-title":"Current and Emerging Techniques. Thorax"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1378\/chest.109.1.152"},{"key":"e_1_2_1_37_1","doi-asserted-by":"crossref","unstructured":"James S Robertson William E Siri Hardin B Jones et al. 1950. Lung Ventilation Patterns Determined by Analysis of Nitrogen Elimination Rates; Use of the Mass Spectrometer as a Continuous Gas Analyzer. The journal of clinical investigation 29 5 (1950) 577--590.","DOI":"10.1172\/JCI102295"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3379503.3403543"},{"key":"e_1_2_1_39_1","article-title":"ERS\/ATS Technical Standard on Interpretive Strategies for Routine Lung Function Tests","volume":"60","author":"Stanojevic Sanja","year":"2022","unstructured":"Sanja Stanojevic, David A Kaminsky, Martin R Miller, Bruce Thompson, Andrea Aliverti, Igor Barjaktarevic, Brendan G Cooper, Bruce Culver, Eric Derom, Graham L Hall, et al. 2022. ERS\/ATS Technical Standard on Interpretive Strategies for Routine Lung Function Tests. European Respiratory Journal 60, 1 (2022).","journal-title":"European Respiratory Journal"},{"key":"e_1_2_1_40_1","volume-title":"Non-Contact Video-Based Assessment of the Respiratory Function Using a RGB-D Camera. Sensors 21","author":"Valenzuela Andrea","year":"2021","unstructured":"Andrea Valenzuela, Nicol\u00e1s Sibuet, Gemma Hornero, and Oscar Casas. 2021. Non-Contact Video-Based Assessment of the Respiratory Function Using a RGB-D Camera. Sensors 21 (2021)."},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1183\/13993003.02129-2016"},{"key":"e_1_2_1_42_1","first-page":"1","article-title":"RespTracker","volume":"2021","author":"Wan Haoran","year":"2021","unstructured":"Haoran Wan, Shuyu Shi, Wenyu Cao, Wei Wang, and Guihai Chen. 2021. RespTracker: Multi-user Room-scale Respiration Tracking with Commercial Acoustic Devices. In IEEE INFOCOM 2021. 1--10.","journal-title":"Multi-user Room-scale Respiration Tracking with Commercial Acoustic Devices. In IEEE INFOCOM"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/2971648.2971744"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2877607"},{"volume-title":"Your Breath Doesn't Lie: Multi-user Authentication by Sensing Respiration Using mmWave Radar. In 2022 19th IEEE SECON. 64--72","author":"Wang Yao","key":"e_1_2_1_45_1","unstructured":"Yao Wang, Tao Gu, Tom H. Luan, and Yong Yu. 2022. Your Breath Doesn't Lie: Multi-user Authentication by Sensing Respiration Using mmWave Radar. In 2022 19th IEEE SECON. 64--72."},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM48880.2022.9796912"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581791.3596854"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/IWQoS54832.2022.9812913"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.202204-0643OC"},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3450318"},{"key":"e_1_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2019.2939791"},{"key":"e_1_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3191785"},{"key":"e_1_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1007\/s42765-021-00097-5"},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-112-10-763"}],"container-title":["Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3749489","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T16:28:58Z","timestamp":1758817738000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3749489"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,3]]},"references-count":54,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,9,3]]}},"alternative-id":["10.1145\/3749489"],"URL":"https:\/\/doi.org\/10.1145\/3749489","relation":{},"ISSN":["2474-9567"],"issn-type":[{"type":"electronic","value":"2474-9567"}],"subject":[],"published":{"date-parts":[[2025,9,3]]},"assertion":[{"value":"2025-09-03","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}