{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T18:55:18Z","timestamp":1793904918674,"version":"4.8.0"},"reference-count":34,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Form Res"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Blood pressure (BP) and hemoglobin concentration measurements are essential components of preoperative anesthetic evaluation. Remote photoplethysmography (rPPG) is an emerging technology that may be used to measure BP and hemoglobin concentration noninvasively with just a consumer-grade smartphone, replacing traditional in-person measurements. However, there is limited data regarding the use of this technology in patients with diverse skin tones and medical comorbidities. Hence, widespread applicability is yet to be achieved. The potential benefits of achieving this would be immense, allowing for greater convenience, accessibility, and reduction in labor and resources.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Our study aims to be the first to develop an algorithm for noninvasive rPPG-based BP and hemoglobin concentration measurement that can be used for preoperative evaluation of patients in real-world clinical practice settings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted the study at Singapore General Hospital from March 1, 2023, to June 28, 2024. A total of 200 patients were recruited. Our primary analysis compared the accuracy of rPPG-based systolic and diastolic BP measurements against measurements taken with automated BP measuring devices. Our secondary analysis compared the accuracy of rPPG-based hemoglobin concentration measurement against traditional blood sampling.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Our model performed best with diastolic BP predictions, with a mean absolute percentage error of 7.52% and a mean difference of 0.16 mm Hg (SD 3.22 mm Hg) between reference and measured readings. The 95% CI for the mean difference between predicted and measured diastolic BP was \u00b10.57 (\u22120.41 to 0.73) mm Hg. Systolic BP predictions yielded a mean absolute percentage error of 9.52% and a mean difference of 2.69 mm Hg (SD 7.86 mm Hg). The 95% CI for the mean difference between predicted and measured systolic BP was \u00b11.14 (\u22121.54 to \u22123.83) mm Hg. Hemoglobin concentration predictions had a mean absolute percentage error of 8.52%, with a mean difference of 0.23 g\/dL (SD 0.67 g\/dL). The 95% CI for the mean difference between predicted and reference measured hemoglobin concentration was \u00b10.10 (95% CI 0.13\u20100.33) g\/dL.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Noninvasive rPPG-based measurement of BP and hemoglobin concentration at the preoperative evaluation setting has great potential for improving convenience, improving efficiency, and conserving resources for patients and health care providers. Our model was able to accurately predict diastolic BP in patients with diverse skin tones and medical comorbidities. The findings of this study serve as a basis for further studies to develop and validate the model for noninvasive rPPG-based BP and hemoglobin concentration measurement.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/60455","type":"journal-article","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:05:07Z","timestamp":1740099907000},"page":"e60455-e60455","source":"Crossref","is-referenced-by-count":12,"title":["Remote Photoplethysmography Technology for Blood Pressure and Hemoglobin Level Assessment in the Preoperative Assessment Setting: Algorithm Development Study"],"prefix":"10.2196","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1716-1356","authenticated-orcid":false,"given":"Selene Y L","family":"Tan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5650-7994","authenticated-orcid":false,"given":"Jia Xin","family":"Chai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9995-9985","authenticated-orcid":false,"given":"Minwoo","family":"Choi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2469-1008","authenticated-orcid":false,"given":"Umair","family":"Javaid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2504-3341","authenticated-orcid":false,"given":"Brenda Pei Yi","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-6897-2019","authenticated-orcid":false,"given":"Belinda Si Ying","family":"Chow","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1916-0832","authenticated-orcid":false,"given":"Hairil Rizal","family":"Abdullah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,6,6]]},"reference":[{"issue":"9","key":"R1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3558518","article-title":"Camera measurement of physiological vital signs","volume":"55","author":"McDuff","journal-title":"ACM Comput Surv"},{"key":"R2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3229977","article-title":"ReViSe: remote vital signs measurement using smartphone camera","volume":"10","author":"Qiao","journal-title":"IEEE Access"},{"issue":"2","key":"R3","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1097\/01.SLA.0000081085.98792.3d","article-title":"The aging population and its impact on the surgery workforce","volume":"238","author":"Etzioni","journal-title":"Ann Surg"},{"issue":"9","key":"R4","doi-asserted-by":"publisher","first-page":"2018","DOI":"10.1111\/ans.17674","article-title":"The changing landscape of general surgery in the elderly - 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