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Sen. Netw."],"published-print":{"date-parts":[[2020,2,29]]},"abstract":"<jats:p>\n            Patients with respiratory diseases require frequent and accurate blood oxygen level monitoring. Existing techniques, however, either need a dedicated hardware or fail to predict low saturation levels. To fill in this gap, we propose a phone-based oxygen level estimation system, called PhO\n            <jats:sub>2<\/jats:sub>\n            , using camera and flashlight functions that are readily available on today\u2019s off-the-shelf smartphones. Since the phone\u2019s camera and flashlight were not made for this purpose, utilizing them for oxygen level estimation poses many difficulties. We introduce a cost-effective add-on together with a set of algorithms for spatial and spectral optical signal modulation to amplify the optical signal of interest while minimizing noise. A near-field-based pressure detection and feedback mechanism are also proposed to mitigate the negative impacts of user\u2019s behavior during the measurement. We also derive a non-linear referencing model with an outlier removal technique that allows PhO\n            <jats:sub>2<\/jats:sub>\n            to accurately estimate the oxygen level from color intensity ratios produced by the smartphone\u2019s camera.\n          <\/jats:p>\n          <jats:p>\n            An evaluation on COTS smartphone with six subjects shows that PhO\n            <jats:sub>2<\/jats:sub>\n            can estimate the oxygen saturation within 3.5% error rate comparing to FDA-approved gold standard pulse oximetry. In addition, our evaluation in hospitals presents high correlation with ground-truth qualified by the 0.83\/1.0 Kendall \u03c4 coefficient.\n          <\/jats:p>","DOI":"10.1145\/3360725","type":"journal-article","created":{"date-parts":[[2020,1,9]],"date-time":"2020-01-09T15:59:51Z","timestamp":1578585591000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Smartphone-Based SpO\n            <sub>2<\/sub>\n            Measurement by Exploiting Wavelengths Separation and Chromophore Compensation"],"prefix":"10.1145","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5350-7583","authenticated-orcid":false,"given":"Nam","family":"Bui","sequence":"first","affiliation":[{"name":"University of Colorado Boulder, Boulder, CO, Colorado"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anh","family":"Nguyen","sequence":"additional","affiliation":[{"name":"University of Colorado Boulder, Boulder, CO, Colorado"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Phuc","family":"Nguyen","sequence":"additional","affiliation":[{"name":"University of Colorado Boulder, Boulder, CO, Colorado"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hoang","family":"Truong","sequence":"additional","affiliation":[{"name":"University of Colorado Boulder, Boulder, CO, Colorado"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashwin","family":"Ashok","sequence":"additional","affiliation":[{"name":"Georgia State University, Atlanta, GA, Georgia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thang","family":"Dinh","sequence":"additional","affiliation":[{"name":"Virginia Commonwealth University, Richmond, VA, Virginia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robin","family":"Deterding","sequence":"additional","affiliation":[{"name":"Children\u2019s Hospital Colorado, Aurora, CO, Colorado"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tam","family":"Vu","sequence":"additional","affiliation":[{"name":"University of Colorado Boulder, Boulder, CO, Colorado"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,1,9]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"680nm Filter 2017. 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