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. To investigate the effect of ICP changes on the waveform of intracranial PPG signals of different cerebral perfusion territories. 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 years) 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). The simulated mean ICPs in normal condition were in the normal range (8.87-11.35 mm Hg), with larger PPG fluctuations in older subject and ACA/PCA territories. When intracranial capacitance decreased, the mean ICP increased above normal threshold (>20 mm Hg), 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. 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.
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http://dx.doi.org/10.3389/fphys.2023.1085871 | DOI Listing |
Sci Rep
March 2025
Instrumentation and Control Engineering, Dr B R Ambedkar National Institute of Technology, Jalandhar, Jalandhar, Punjab, 144027, India.
Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the coronary arteries, responsible for supplying oxygenated blood to the heart, get occluded due to plaque deposits on their inner walls. The most critical fact about this disease is that it develops gradually over the years and by the time symptomatic changes such as angina or shortness of breath appear, the disease has already become severe.
View Article and Find Full Text PDFFront Physiol
February 2025
College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Objective: This study aims to employ physiological model simulation to systematically analyze the frequency-domain components of PPG signals and extract their key features. The efficacy of these frequency-domain features in effectively distinguishing emotional states will also be investigated.
Methods: A dual windkessel model was employed to analyze PPG signal frequency components and extract distinctive features.
Angew Chem Int Ed Engl
March 2025
Northwest University, College of Chemistry and Materials Science, CHINA.
Hydrogen sulfide (H2S) is increasingly recognized for its critical roles in various physiological and pathological processes. The development of synthetic donors with controllable release profiles is essential for elucidating H2S's complex involvement in cellular signaling, which remains a challenge. Herein, we report a diverse collection of photocaged N-methylation thiocarbamates and thiocarbonates, designed to explore how electronic properties and the leaving efficiency of payloads affect H2S release behaviors.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
The cuffless estimation of blood pressure (BP) has become a prominent area of research in recent years fueled by its potential clinical implications and the growing interest from the wearable device industry. It has been accelerated by the emergence of learning-based models. Most use multiple pulse signals such as ECG, PPG, etc.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
The key to cuffless blood pressure (BP) estimation lies in identifying the efficient noninvasive features or signals that can indicate BP changes. Most these features are identified based on their correlation with BP. However, the correlation does not imply causation, as there might be confounders impacting the relationship between the features and BP.
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