Non-contact Photoplethysmography Research Articles

An Accurate Non-contact Photoplethysmography via Active Cancellation of Reflective Interference.

Imaging Photoplethysmography (IPPG) is an emerging and efficient optical method for non-contact measurement of pulse waves using an image sensor. While the contactless way brings convenience, the inevitable distance between the sensor and the subject results in massive specular reflection interference on the skin surface, which leads to a low Signal to Interference plus Noise Ratio (SINR) of IPPG. To ease this challenge, this work proposes a novel modulation illumination approach to measure the accurate arterial pulse wave via surface reflection interference isolation from IPPG. Based on the proposed skin reflection model, a specific modulation illumination is designed to separate the surface reflections and obtain the subcutaneous diffuse reflections containing the pulse wave information. Compared with the results under ambient illumination and constant supplemental illumination, the SINR of the proposed method is improved by 4.56 and 3.74 dB, respectively.

Slidingan analysis of analytical signal of non-contact photoplethysmography for assessing heart rate

The paper proposes a method for studying the variability of the subject’s heart rate based on the intellectual analysis of the pulse wave measured with remote photoplethysmography. The logically related stages of the formation of quadrature components based on the Hilbert transform of biomedical signals’ dynamics are presented. Within the framework of modern methods of intellectual analysis of non-stationary time series, realizations of adaptive estimates of instantaneous frequencies and periods of the heartbeat basic tone are obtained.

Sliding spectral correlation analysis of non-contact photoplethysmography signals for assessment of heart rate

Sliding spectral correlation analysis of non-contact photoplethysmography signals for assessment of heart rate

On the cardiorespiratory coordination assessed by the photoplethysmography imaging technique

Cardiorespiratory coordination (CRC) probes the interaction between cardiac and respiratory oscillators in which cardiac and respiratory activity are synchronized, with individual heartbeats occurring at approximately the same temporal positions during several breathing cycles. An increase of CRC has previously been related to pathological stressful states. We studied CRC employing coordigrams computed from non-contact photoplethysmography imaging (PPGI) and respiratory data using the optical flow method. In a blocked study design, we applied the cold pressure test (CPT), water at ambient temperature (AWT), and intermittent resting conditions. In controls (no intervention), CRC remained on initial low levels throughout measurements. In the experimental group (AWT and CPT intervention), CRC decreased during AWT and CPT. Following both interventions, CRC increased significantly, with a rebound effect following AWT. In controls, HR increased steadily over time. CPT evoked a significant HR increase which correlated with subjective stress/pain ratings. The CRC increase following AWT correlated significantly with subjective pain (r = .79) and stress (r = .63) ratings. Furthermore, we observed a significant correlation (r = − .80) between mean RMSSD and mean duration of CRC, which further supports an association between autonomic state and CRC level. CRC analysis obtained from cutaneous tissue perfusion data therefore appears to be a sensitive and useful method for the study of CRC and ANS activity. Future studies need to investigate the physiological principles and clinical significance of these findings.

Infant heart rate estimation based on non-contact UV photoplethysmography

Non-contact cardio signal monitoring is a requisite for premature infants, as adhesive sensors and electrodes such as that for an electrocardiogram can damage the epidermis. Many types of research on infants in the newborn intensive care unit (NICU) are still in their early stages with many challenges. Therefore, this study aims to use a digital camera as a non-contact photoplethysmography imaging method to measure and compare the heart rate from two experiments (without/with ultraviolet rays (UV)) inside the intensive care unit. The two experiments (without/with UV) rays yielded promising results in comparison with the reference measurements obtained from ten infants. The results reveal a robust correlation using the pearson correlation coefficients (PCC) of 0.99 (for without UV) and 0.96 (for with UV). Also, the spearman correlation coefficient (SCC) test of 0.97 and 0.95 for two experiments, respectively Bland–Altman analysis revealed a strong relationship between measured and reference readings from without and with UV. The experimental results obtained a low error rate for mean absolute error (MAE), and root mean squared error (RMSE). Therefore, this work presents a new aspect of non-contact monitoring, showing promising performance for upcoming medical applications.

High-Reliability Non-Contact Photoplethysmography Imaging for Newborn Care by a Generative Artificial Intelligence

High-Reliability Non-Contact Photoplethysmography Imaging for Newborn Care by a Generative Artificial Intelligence

Экспериментальное обоснование ряда требований к аппаратным и методическим средствам неконтактной фотоплетизмографии на основе анализа видеоизображений

Experimental assessment of the possibility of using a scientific video camera for realization of non-contact photoplethysmography is carried out. In view of the wide spread of digital cameras in endoscopic units photoplethysmography based on video-image analysis is an inexpensive and promising method for solving problems of medical diagnostics. A number of requirements to the camera parameters ensuring the specified level of the registered signals coded by RGB values, to the external illumination and video image postprocessing algorithms was substantiated. It was found that at signal levels on the green channel of not less than 130 and not more than 220 a. u. (for a camera with 8-bit color coding depth), the highest level of useful pulse signal is provided. It was shown that any source of light of equivalent color temperature in the range of 3500--6500 K as well as green LEDs can be used as a light source to obtain a high-quality signal of non-contact photoplethysmography. It is demonstrated that the signal has higher signal/noise ratio when the averaging area is larger than 40 × 40 pixels than when averaging over a smaller group of pixels. The obtained results can be used for the implementation of non-contact photoplethysmography to study local blood flow based on video image analysis

A Non-Contact Photoplethysmography Technique for the Estimation of Heart Rate via Smartphone

This paper describes the development of an application for mobile devices under the iOS platform which has the objective of monitoring patients with alterations or affections from cardiac pathologies. The software tool developed for mobile devices provides a patient and a specialist doctor the ability to handle and treat disease remotely while monitoring through the technique of non-contact photoplethysmography (PPG). The mobile application works by processing red, green, and blue (RGB) color video images on a specific region of the face, thus obtaining the intensity of the pixels in the green channel. The results are then processed using mathematical algorithms and Fourier transform, moving from the time domain to the frequency domain to ensure proper interpretation and to obtain the pulses per minute (PPM). The results are favorable because a comparison of the results was made with respect to the application of a medical-grade pulse-oximeter, where an error rate of 3% was obtained, indicating the acceptable performance of our application. The present technological development provides an application tool with significant potential in the area of health.

Importance of Illumination in a Non-Contact Photoplethysmography Imaging System for Burn Wound Assessment

Photoplethysmography imaging (PPGI) is an optical technique that assesses tissue blood perfusion and can assist in the identification of necrotic, non-viable tissue. We present a non-contact PPGI method and prototype system that could aid clinicians and surgeons by improving wound triage decisions and dermal wound management. We assessed features of the non-contact PPGI system and evaluated their impact on the system's ability to generate useful outputs that discern healthy, viable tissue from necrotic, burned tissue. Uniformity and intensity parameters of the illumination source were identified as key variables.

Comparison of speckleplethysmographic (SPG) and photoplethysmographic (PPG) imaging by Monte Carlo simulations and in vivo measurements.

Noncontact photoplethysmography (PPG) is limited by a poor signal-to-noise ratio (SNR). A solution to this limitation is the use of alternate sources of optical contrast to generate a complementary pulsatile waveform. One such source is laser speckle contrast, which is modulated in biological tissues by the flow rate of red blood cells. Averaging a region of interest from a speckle contrast image over time allows for the calculation of a speckleplethysmogram (SPG). Similar to PPG, SPG enables monitoring of heart rate and respiratory rate. A gap in the knowledge base exists as to the precise spatiotemporal relationship between PPG and SPG signals. We have developed an eight-layer tissue model to simulate both PPG and SPG signals in a reflectance geometry via Monte Carlo methods. We modeled PPG by compression of the upper and lower blood nets due to expansion of the larger arterial layer below. The in silico PPG peak-to-peak amplitude percent was greater at 532 nm than at 860 nm (5.6% vs. 3.0%, respectively), which matches trends from the literature. We modeled SPG by changing flow speeds of red blood cells in both the capillaries and arterioles over the cardiac cycle. The in silico SPG peak-to-peak amplitude percent was 24% at 532 nm and 40% at 860 nm. In silico results are similar to in vivo results measured with a two-camera set up for simultaneous imaging of PPG and SPG. Both in silico and in vivo data suggest SPG has a much larger SNR than PPG, which may prove beneficial for noncontact, wide-field optical monitoring of cardiovascular health.

Assessment of a noninvasive optical photoplethysmography imaging device with dynamic tissue phantom models.

Noncontact photoplethysmography (PPG) has been studied as a method to provide low-cost, noninvasive, two-dimensional blood oxygenation measurements and medical imaging for a variety of near-surface pathologies. To evaluate this technology in a laboratory setting, dynamic tissue phantoms were developed with tunable parameters that mimic physiologic properties of the skin, including blood vessel volume change, pulse wave frequency, and tissue scattering and absorption. Tissue phantoms were generated using an elastic tubing to represent a blood vessel where the luminal volume could be modulated with a pulsatile fluid flow. The blood was mimicked with a scattering and absorbing motility standard, and the tissue with a gelatin-lipid emulsion hydrogel. A noncontact PPG imaging system was then evaluated using the phantoms. Noncontact PPG imaging accurately identified pulse frequency, and PPG signals from these phantoms suggest that the phantoms can be used to evaluate noncontact PPG imaging systems. Such information may be valuable to the development of future PPG imaging systems.

Accuracy of smartphone apps for heart rate measurement.

Background Smartphone manufacturers offer mobile health monitoring technology to their customers, including apps using the built-in camera for heart rate assessment. This study aimed to test the diagnostic accuracy of such heart rate measuring apps in clinical practice. Methods The feasibility and accuracy of measuring heart rate was tested on four commercially available apps using both iPhone 4 and iPhone 5. 'Instant Heart Rate' (IHR) and 'Heart Fitness' (HF) work with contact photoplethysmography (contact of fingertip to built-in camera), while 'Whats My Heart Rate' (WMH) and 'Cardiio Version' (CAR) work with non-contact photoplethysmography. The measurements were compared to electrocardiogram and pulse oximetry-derived heart rate. Results Heart rate measurement using app-based photoplethysmography was performed on 108 randomly selected patients. The electrocardiogram-derived heart rate correlated well with pulse oximetry ( r = 0.92), IHR ( r = 0.83) and HF ( r = 0.96), but somewhat less with WMH ( r = 0.62) and CAR ( r = 0.60). The accuracy of app-measured heart rate as compared to electrocardiogram, reported as mean absolute error (in bpm ± standard error) was 2 ± 0.35 (pulse oximetry), 4.5 ± 1.1 (IHR), 2 ± 0.5 (HF), 7.1 ± 1.4 (WMH) and 8.1 ± 1.4 (CAR). Conclusions We found substantial performance differences between the four studied heart rate measuring apps. The two contact photoplethysmography-based apps had higher feasibility and better accuracy for heart rate measurement than the two non-contact photoplethysmography-based apps.

Motion limitations of non-contact photoplethysmography due to the optical and topological properties of skin

Non-contact photoplethysmography (PPG) provides multiple benefits over in-contact methods, but is not as tolerant to motion due to the lack of mechanical coupling between the subject and sensor. One limitation of non-contact photoplethysmography is discussed here, specifically looking at the topology and optical variations of the skin and how this impacts upon the ability to extract a photoplethysmogram when a subject moves horizontally across the field of view of the detector (a panning motion). When this occurs it is shown that whilst the general relationships between the speed of traversal, detection area and resultant signal quality can be found, the quality of signal in each individual case is determined by the properties of the area of skin chosen.

Optimizing Estimates of Instantaneous Heart Rate from Pulse Wave Signals with the Synchrosqueezing Transform.

With recent advances in sensor and computer technologies, the ability to monitor peripheral pulse activity is no longer limited to the laboratory and clinic. Now inexpensive sensors, which interface with smartphones or other computer-based devices, are expanding into the consumer market. When appropriate algorithms are applied, these new technologies enable ambulatory monitoring of dynamic physiological responses outside the clinic in a variety of applications including monitoring fatigue, health, workload, fitness, and rehabilitation. Several of these applications rely upon measures derived from peripheral pulse waves measured via contact or non-contact photoplethysmography (PPG). As technologies move from contact to non-contact PPG, there are new challenges. The technology necessary to estimate average heart rate over a few seconds from a noncontact PPG is available. However, a technology to precisely measure instantaneous heat rate (IHR) from non-contact sensors, on a beat-to-beat basis, is more challenging. The objective of this paper is to develop an algorithm with the ability to accurately monitor IHR from peripheral pulse waves, which provides an opportunity to measure the neural regulation of the heart from the beat-to-beat heart rate pattern (i.e., heart rate variability). The adaptive harmonic model is applied to model the contact or non-contact PPG signals, and a new methodology, the Synchrosqueezing Transform (SST), is applied to extract IHR. The body sway rhythm inherited in the non-contact PPG signal is modeled and handled by the notion of wave-shape function. The SST optimizes the extraction of IHR from the PPG signals and the technique functions well even during periods of poor signal to noise. We contrast the contact and non-contact indices of PPG derived heart rate with a criterion electrocardiogram (ECG). ECG and PPG signals were monitored in 21 healthy subjects performing tasks with different physical demands. The root mean square error of IHR estimated by SST is significantly better than commonly applied methods such as autoregressive (AR) method. In the walking situation, while AR method fails, SST still provides a reasonably good result. The SST processed PPG data provided an accurate estimate of the ECG derived IHR and consistently performed better than commonly applied methods such as autoregressive method.