{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T02:18:55Z","timestamp":1778638735684,"version":"3.51.4"},"reference-count":60,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,3,16]],"date-time":"2023-03-16T00:00:00Z","timestamp":1678924800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Physiol."],"abstract":"<jats:p><jats:bold>Background:<\/jats:bold> Intracranial photoplethysmography (PPG) signals can be measured from extracranial sites using wearable sensors and may enable long-term non-invasive monitoring of intracranial pressure (ICP). However, it is still unknown if ICP changes can lead to waveform changes in intracranial PPG signals.<\/jats:p><jats:p><jats:bold>Aim:<\/jats:bold> To investigate the effect of ICP changes on the waveform of intracranial PPG signals of different cerebral perfusion territories.<\/jats:p><jats:p><jats:bold>Methods:<\/jats:bold> Based on lump-parameter Windkessel models, we developed a computational model consisting three interactive parts: cardiocerebral artery network, ICP model, and PPG model. We simulated ICP and PPG signals of three perfusion territories [anterior, middle, and posterior cerebral arteries (ACA, MCA, and PCA), all left side] in three ages (20, 40, and 60\u00a0years) and four intracranial capacitance conditions (normal, 20% decrease, 50% decrease, and 75% decrease). We calculated following PPG waveform features: maximum, minimum, mean, amplitude, min-to-max time, pulsatility index (PI), resistive index (RI), and max-to-mean ratio (MMR).<\/jats:p><jats:p><jats:bold>Results:<\/jats:bold> The simulated mean ICPs in normal condition were in the normal range (8.87\u201311.35\u00a0mm\u00a0Hg), with larger PPG fluctuations in older subject and ACA\/PCA territories. When intracranial capacitance decreased, the mean ICP increased above normal threshold (&amp;gt;20\u00a0mm\u00a0Hg), with significant decreases in maximum, minimum, and mean; a minor decrease in amplitude; and no consistent change in min-to-max time, PI, RI, or MMR (maximal relative difference less than 2%) for PPG signals of all perfusion territories. There were significant effects of age and territory on all waveform features except age on mean.<\/jats:p><jats:p><jats:bold>Conclusion:<\/jats:bold> ICP values could significantly change the value-relevant (maximum, minimum, and amplitude) waveform features of PPG signals measured from different cerebral perfusion territories, with negligible effect on shape-relevant features (min-to-max time, PI, RI, and MMR). Age and measurement site could also significantly influence intracranial PPG waveform.<\/jats:p>","DOI":"10.3389\/fphys.2023.1085871","type":"journal-article","created":{"date-parts":[[2023,3,16]],"date-time":"2023-03-16T04:23:34Z","timestamp":1678940614000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Effect of intracranial pressure on photoplethysmographic waveform in different cerebral perfusion territories: A computational study"],"prefix":"10.3389","volume":"14","author":[{"given":"Haipeng","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Pan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyue","family":"Lei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiyuan","family":"Hui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ru","family":"Gong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junfeng","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dingchang","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2023,3,16]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e0232523","DOI":"10.1371\/journal.pone.0232523","article-title":"Measurement of normal retinal vascular pulse wave attenuation using modified photoplethysmography","volume":"15","author":"Abdul-Rahman","year":"2020","journal-title":"PLOS ONE"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1794","DOI":"10.1016\/j.jbiomech.2006.07.008","article-title":"Modelling the circle of Willis to assess the effects of anatomical variations and occlusions on cerebral flows","volume":"40","author":"Alastruey","year":"2007","journal-title":"J. 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