Photoplethysmography (PPG) devices are widely used in clinical practice but the origin of PPG signal is still under debating. The classical theory assumes that the PPG waveform stems from variations of blood volume in pulsating arteries. In this research we analysed high-speed video recordings of capillaries in a fingernail bed. It was found that speed of erythrocytes in capillaries has pronounced modulation in time, which follows variations of instantaneous blood pressure in arteries. However, the mean speed significantly differs even for neighbour capillaries whereas change of the speed occurs in phase for the most of capillaries. Moreover, the light intensity remitted from the papillary dermis is also modulated at the heartbeat frequency displaying significant correlation with waveforms of the RBC speed. Obtained results can hardly be explained by the classical theory of PPG signal formation. Shallow penetrating visible light acquires modulation of erythrocytes density in the capillary bed without interacting with deeper situated pulsating arteries. Therefore, the capillary bed could serve as a distributed sensor for monitor the status of deep vessels. Better understanding of the photoplethysmography basis will result in a wider range of applications of this fast growing technology in both medical and research practice.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5643323PMC
http://dx.doi.org/10.1038/s41598-017-13552-4DOI Listing

Publication Analysis

Top Keywords

ppg signal
8
classical theory
8
pulsating arteries
8
capillary bed
8
video capillaroscopy
4
capillaroscopy clarifies
4
clarifies mechanism
4
mechanism photoplethysmographic
4
photoplethysmographic waveform
4
waveform appearance
4

Similar Publications

Nowadays, photoplethysmograph (PPG) technology is being used more often in smart devices and mobile phones due to advancements in information and communication technology in the health field, particularly in monitoring cardiac activities. Developing generative models to generate synthetic PPG signals requires overcoming challenges like data diversity and limited data available for training deep learning models. This paper proposes a generative model by adopting a genetic programming (GP) approach to generate increasingly diversified and accurate data using an initial PPG signal sample.

View Article and Find Full Text PDF

Introduction: Vascular access (VA) is essential for patients with hemodialysis, and its dysfunction is a major complication that can reduce quality of life or even threaten life. VA patency is not only difficult to predict on an individual basis, but also challenging to predict in real-time. To overcome this challenge, this study aimed to develop a machine learning approach to predict 6-month primary patency (PP) using photoplethysmography (PPG) signals acquired from the tips of both index fingers.

View Article and Find Full Text PDF

In the early stages of atrial fibrillation (AF), most cases are paroxysmal (pAF), making identification only possible with continuous and prolonged monitoring. With the advent of wearables, smartwatches equipped with photoplethysmographic (PPG) sensors are an ideal approach for continuous monitoring of pAF. There have been numerous studies demonstrating successful capture of pAF events, especially using deep learning.

View Article and Find Full Text PDF

Objective: We study the changes in morphology of the photoplethysmography (PPG) signals-acquired from a select group of South Asian origin-through a low-cost PPG sensor, and correlate it with healthy aging which allows us to reliably estimate the vascular age and chronological age of a healthy person as well as the age group he/she belongs to.

Methods: Raw infrared PPG data is collected from the finger-tip of 173 appar- ently healthy subjects, aged 3-61 years, via a non-invasive low- cost MAX30102 PPG sensor. In addition, the following metadata is recorded for each subject: age, gender, height, weight, family history of cardiac disease, smoking history, vitals (heart rate and SpO2).

View Article and Find Full Text PDF

A Hybrid Photoplethysmography (PPG) Sensor System Design for Heart Rate Monitoring.

Sensors (Basel)

November 2024

Major of Device Science and Engineering, Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka 8160811, Japan.

A photoplethysmography (PPG) sensor is a cost-effective and efficacious way of measuring health conditions such as heart rate, oxygen saturation, and respiration rate. In this work, we present a hybrid PPG sensor system working in a reflective mode with an optoelectronic module, i.e.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!