Photoplethysmography (PPG) is used to estimate the skin blood flow using infrared light. Researchers from different domains of science have become increasingly interested in PPG because of its advantages as non-invasive, inexpensive, and convenient diagnostic tool. Traditionally, it measures the oxygen saturation, blood pressure, cardiac output, and for assessing autonomic functions. Moreover, PPG is a promising technique for early screening of various atherosclerotic pathologies and could be helpful for regular GP-assessment but a full understanding of the diagnostic value of the different features is still lacking. Recent studies emphasise the potential information embedded in the PPG waveform signal and it deserves further attention for its possible applications beyond pulse oximetry and heart-rate calculation. Therefore, this overview discusses different types of artifact added to PPG signal, characteristic features of PPG waveform, and existing indexes to evaluate for diagnoses.

On the Analysis of Fingertip Photoplethysmogram Signals

Photoplethysmography (PPG) is an uncomplicated and inexpensive optical measurement method that is often used for heart rate monitoring purposes. PPG is a non-invasive technology that uses a light source and a photodetector at the surface of skin to measure the volumetric variations of blood circulation. Recently, there has been much interest from numerous researchers around the globe to extract further valuable information from the PPG signal in addition to heart rate estimation and pulse oxymetry readings. PPG signal's second derivative wave contains important health-related information. Thus, analysis of this waveform can help researchers and clinicians to evaluate various cardiovascular-related diseases such as atherosclerosis and arterial stiffness. Moreover, investigating the second derivative wave of PPG signal can also assist in early detection and diagnosis of various cardiovascular illnesses that may possibly appear later in life. For early recognition and analysis of such illnesses, continuous and real-time monitoring is an important approach that has been enabled by the latest technological advances in sensor technology and wireless communications. The aim of this article is to briefly consider some of the current developments and challenges of wearable PPG-based monitoring technologies and then to discuss some of the potential applications of this technology in clinical settings.

/pdf/a-review-on-wearable-photoplethysmography-sensors-and-their-3kmqsjhauj.pdf

A review on wearable photoplethysmography sensors and their potential future applications in health care.

With the advance of computer and photonics technology, imaging photoplethysmography ((PPG), iPPG) can provide comfortable and comprehensive assessment over a wide range of anatomical locations. However, motion artifact is a major drawback in current iPPG systems, particularly in the context of clinical assessment. To overcome this issue, a new artifact-reduction method consisting of planar motion compensation and blind source separation is introduced in this study. The performance of the iPPG system was evaluated through the measurement of cardiac pulse in the hand from 12 subjects before and after 5 min of cycling exercise. Also, a 12-min continuous recording protocol consisting of repeated exercises was taken from a single volunteer. The physiological parameters (i.e., heart rate, respiration rate), derived from the images captured by the iPPG system, exhibit functional characteristics comparable to conventional contact PPG sensors. Continuous recordings from the iPPG system reveal that heart and respiration rates can be successfully tracked with the artifact reduction method even in high-intensity physical exercise situations. The outcome from this study thereby leads to a new avenue for noncontact sensing of vital signs and remote physiological assessment, with clear applications in triage

https://www.spiedigitallibrary.org/journals/Journal-of-Biomedical-Optics/volume-16/issue-7/077010/Motion-compensated-noncontact-imaging-photoplethysmography-to-monitor-cardiorespiratory-status-during/10.1117/1.3602852.pdf

Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise

A novel feature ranking algorithm for biometric recognition with PPG signals

Cuffless blood pressure estimation from electrocardiogram and photoplethysmogram using waveform based ANN-LSTM network

Cardiac output (CO) monitoring is essential for indicating the perfusion status of the human cardiovascular system under different physiological conditions. However, it is currently limited to hospital use due to the need for either skilled operators or big, expensive measurement devices. Therefore, in this paper we devise a new CO indicator which can easily be incorporated into existing wearable devices. To this end, we propose an index, the inflection and harmonic area ratio (IHAR), from standard photoplethysmographic (PPG) signals, which can be used to continuously monitor CO. We evaluate the success of our index by testing on sixteen normotensive subjects before and after bicycle exercise. The results showed a strong intra-subject correlation between IHAR and CO imp measured by the bio-impedance method in fifteen subjects (mean r = 3D 0.82, p imp and CO estimated from IHAR (CO IHAR ) was 1.40 L/min. The total percentage error of the results was 16.2%, which was well below the clinical acceptance limit of 30%. The results suggest that IHAR is a promising indicator for wearable and noninvasive CO monitoring.

Noninvasive cardiac output estimation using a novel photoplethysmogram index

Cardiac output (CO) monitoring is not only essential for critically ill patients in the hospital, but also for patients at home and those undergoing cardiopulmonary exercise testing. However, CO is difficult to monitor during daily activities and exercise. In this paper, we aim at developing a novel CO estimation method that can be used under these challenging conditions. The tube model was utilized to derive a CO index, namely the pulse time reflection ratio (PTRR) from an electrocardiogram and photoplethysmogram. After calibration, the PTRR can be used to estimate beat-to-beat CO. The proposed method was verified against CO measured by impedance cardiography on 19 healthy subjects in an incremental intensity exercise test. Results showed that there were strong correlations (r) between the PTRR and reference CO in 18 subjects (mean r: 0.88, n = 245 trials). Two calibration approaches reported in the literature were applied to the proposed method and the corresponding bias +/- precisions of estimation errors were 0 +/- 1.89 L min(-1) and -0.22 +/- 2.12 L min(-1), respectively. The percent errors were 21.94% and 24.90%, smaller than the clinical acceptance limit (30%). To conclude, after calibration, this method can be used to monitor CO on healthy subjects during incremental intensity exercise.

http://iopscience.iop.org/article/10.1088/0967-3334/31/5/008/pdf

The non-invasive and continuous estimation of cardiac output using a photoplethysmogram and electrocardiogram during incremental exercise

Speckle noise reduction is a key problem of the image analysis of medical UltraSound images. In this paper, two important improvements have been developed to a fast anisotropic diffusion algorithm for speckle noise reduction. The Gaussian filter is firstly used before gradient calculation, and then the adaptive algorithm of the factor k is proposed. Numerous experimental results show that the proposed model is superior to other methods in noise removal, fidelity and edge preservation. It is suitable for the preprocessing of a great number of medical UltraSound images, such as three dimensional reconstruction.

Filtering of medical ultrasonic images based on a modified anistropic diffusion equation

Blood pressure monitoring is routinely required in many mobile health applications, but the present cuff based measuring system (Finapres) is often unsuitable due to being too big and uncomfortable. An alternative method is to measure the digital volume pulse, which can be non-invasively recorded using the photoplethysmography (PPG), and predict the blood pressure waveform from that of PPG. The benefit is that the PPG components are easy to embed in many portable and wearable devices. In this study, we predicted the peripheral blood pressure waveform of young healthy adults after exercise from that of the PPG pulse using a General Transfer Function (GTF) method, which had been proved effective for this prediction task at steady state before. To this end, we measured the simultaneous blood pressure and PPG pulses of twelve subjects at steady state and immediately after exercise. Three tests were performed to verify the GTF method. Results showed that a single best-fit GTF (GTFb) derived from all subjects and all measurement phases could predict the blood pressure waveform precisely, both at steady state and after exercise. The prediction performance was further improved when phase dependant GTFs were applied.

L. Wang

Papers

Noninvasive cardiac output estimation using a novel photoplethysmogram index

The non-invasive and continuous estimation of cardiac output using a photoplethysmogram and electrocardiogram during incremental exercise

Filtering of medical ultrasonic images based on a modified anistropic diffusion equation

Blood pressure contour analysis after exercise by the photoplethysmogram using a Transfer Function method

A Novel Photoplethysmogram Index for Total Peripheral Resistance after Bicycle Exercise