{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T04:48:40Z","timestamp":1787892520206,"version":"build-2784847793"},"reference-count":19,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T00:00:00Z","timestamp":1778284800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Reflective-mode photoplethysmography (PPG) potentially enables non-invasive physiological monitoring of heart rate and Peripheral Oxygen Saturation (SpO2) from virtually any anatomical body site, but its performances are strongly affected by several parameters such as local perfusion, skin temperature, and microvascular bed and tissue optical properties. This study systematically evaluates the quality of reflective-mode PPG signals acquired at the finger, wrist, ear, nose, temple, upper lip, and lower lip, using two commercial PPG sensors. PPG signal quality was quantified via Skewness, Kurtosis, Perfusion Index, and Shannon entropy. Heart rate (HR) and pulse transit time (PTT) were also computed. Skewness and Perfusion Index were the most informative quality indices, revealing the finger as the site with the best signal quality and the wrist as the most challenging location. Several facial regions\u2014including the lips, nose, and temple\u2014showed signal quality comparable to the finger. HR estimation was most accurate using the GREEN wavelength, with the lower lip achieving the lowest error, followed by the upper lip and finger. PTT values reflected physiological differences in pulse propagation, being longest at the finger and wrist and shortest at the lips. These findings highlight the potential of non-conventional anatomical sites as alternatives to the finger and wrist for reflective-mode PPG acquisition.<\/jats:p>","DOI":"10.3390\/s26102986","type":"journal-article","created":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T15:39:32Z","timestamp":1778513972000},"page":"2986","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Signal Quality of Reflective-Mode Photoplethysmograms Across Anatomical Sites"],"prefix":"10.3390","volume":"26","author":[{"given":"Federica","family":"Ricci","sequence":"first","affiliation":[{"name":"Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, 00146 Rome, Italy"},{"name":"Department of Cardiovascular, Endocrin-Metabolic Diseases and Ageing, Italian National Institute of Health, 00161 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9223-5178","authenticated-orcid":false,"given":"Cecilia","family":"Vivarelli","sequence":"additional","affiliation":[{"name":"National Center for Artificial Intelligence and Innovative Health Technologies, Italian National Institute of Health, 00161 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6494-9456","authenticated-orcid":false,"given":"Eugenio","family":"Mattei","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular, Endocrin-Metabolic Diseases and Ageing, Italian National Institute of Health, 00161 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanni","family":"Calcagnini","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular, Endocrin-Metabolic Diseases and Ageing, Italian National Institute of Health, 00161 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Park, J., Seok, H.S., Kim, S.S., and Shin, H. 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