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In this paper, we investigate the possibility of using image-based pulse transit time (iPTT) to estimate blood pressure using an RGB (red, green, blue)-camera video taken from the face only. It is generally known that there is a correlation between iPTT and blood pressure. iPTT refers to the difference between the times when a pulse wave reaches two different parts of the body. Therefore, it is possible to estimate blood pressure without contact, with iPTTs obtained from the RGB camera. However, this method requires simultaneous capture of images of the face and palm. Recording of such videos is limited by the subject's posture. Hence, it is very difficult to achieve blood pressure estimation in a real-world environment. To solve these problems, this study examined whether it is possible to measure pulse wave propagation based on a single part of the body. The results showed that there was a time difference between the pulse waves at the forehead and the chin, thus it was possible to measure iPTT using only the face. Pulse waves were obtained from the chin and forehead, and the correlations between iPTT and blood pressure from the acquired pulse waves were examined. The results showed a negative correlation between these iPTT measures and blood pressure. The results suggest that simple, non-contact blood pressure estimation will be possible in the future. [ABSTRACT FROM AUTHOR]

The state-of-the-art blood pressure measurement is beside common cuff-based methods the cuff-less estimation of pulse-transit-time, which is the time a blood pressure wave requires to travel from left ventricle of the heart to another peripheral point in the cardiovascular system. Within this work we present a novel estimation method for cuff-less blood pressure measurement by analysing a single photoplethysmographic signal in the frequency domain. The harmonic phase-shift of the fundamental frequency and the first harmonic within the photoplethysmographic signal has proven a strong correlation of r = 0.8514 and r = 0.9315 with systolic and diastolic blood pressure respectively.

Aims: This cross-sectional study was set up to assess the feasibility of mass screening for atrial fibrillation (AF) with only the use of a smartphone.Methods and Results: A local newspaper published an article, allowing to subscribe for a 7-day screening period to detect AF. Screening was performed through an application that uses photo-plethysmography (PPG) technology by exploiting a smartphone camera. Participants received instructions on how to perform correct measurements twice daily, with notifications pushed through the application's software. In case of heart rhythm irregularities, raw PPG signals underwent secondary offline analysis to confirm a final diagnosis. From 12 328 readers who voluntarily signed up for screening (49 ± 14 years; 58% men), 120 446 unique PPG traces were obtained. Photo-plethysmography signal quality was adequate for analysis in 92% of cases. Possible AF was detected in 136 individuals (1.1%). They were older (P < 0.001), more frequently men (P < 0.001), and had higher body mass index (P = 0.004). In addition, participants who strictly adhered to the recommended screening frequency (i.e. twice daily) were more often diagnosed with possible AF (1.9% vs. 1.0% in individuals who did not adhere; P = 0.008). Symptoms of palpitations, confusion, and shortness of breath were more frequent in case of AF (P < 0.001). The cumulative diagnostic yield for possible AF increased from 0.4% with a single heart rhythm assessment to 1.4% with screening during the entire 7-day screening period.Conclusion: Mass screening for AF using only a smartphone with dedicated application based on PPG technology is feasible and attractive because of its low cost and logistic requirements. [ABSTRACT FROM AUTHOR]

Highlights • Wrist/fingertip PPG can be used for cuff-less continuous blood pressure measurement. • Pulse transit time can be obtained from wrist/finger PPG for estimation of BP. • Demographic features and PPG/APG features must be considered for precise estimation. • Highly contributing features in precise estimation of SBP and DBP were obtained. • Contributed features for estimating SBP and DBP are different. Abstract Continuous monitoring of blood pressure improves prevention and control of cardiovascular diseases. Currently, cuff-based oscillometric sphygmomanometers are commonly used to monitor the systolic and diastolic blood pressure. However, this technique is discontinuous in nature and inconvenient for repeated measurements. Here we have proposed indirect measurement of blood pressure from photo-plethysmograms (PPG) simultaneously recorded from wrist and fingertip. The signals were recorded from 111 participants and different morphological features were obtained from PPG and its second derivative, acceleration plethysmograms (APG). Moreover, different measures of pulse transit time (PTT) and pulse wave velocity (PWV) were obtained from the recorded PPGs. Multi-layer Neural Networks were used to estimate the non-linear relationship between these features and systolic and diastolic blood pressures (SBP and DBP). Mean absolute errors of 6.77 and 4.82 mmHg were achieved in comparison with measurements from a validated commercial oscillometric sphygmomanometer. Feature analysis provided insight about the importance of features for estimating BP, and demonstrated that these features are not the same for SBP and DBP. Using the highest-ranked 15 and 13 features obtained from moving-backward algorithm the mean absolute errors were reduced to 5.31 and 4.62 mmHg for SBP and DBP. However, the optimum optimal feature sets provided by a genetic algorithm for estimating SBP/DBP led to the lowest mean absolute errors of 4.94/4.03. These results compared to previous studies and the available standards suggest that the method is a promising substitute for oscillometric sphygmomanometers which can be used conveniently for continuous monitoring of blood pressure. [ABSTRACT FROM AUTHOR]

Heartrate monitoring can be very decisive in terms of detecting heart-related diseases in early stages. Given that smartphones are used almost ubiquitously by humans on a daily basis and that they are equipped with several sensors and a powerful CPU, they are the ideal tools to accomplish daily heartrate monitoring. Many studies have shown the possibility of monitoring the heartrate in a very accurate way by using smartphone camera and the photo-plethysmography technique. However, in real cases, when using a smartphone camera as the input sensor, the pulse signal usually contains noise caused by fingertip movements, pressure changes between the smartphone camera and the fingertip, or changes in ambient light intensity. Hence, many techniques have been proposed to filter and detect real peaks in the pulse signal and avoid noise peaks. Most of those state-of-the-art techniques rely on the assumption that real peaks are those having the maximum values in their respective cycles. In some cases, the assumption is not correct, which decreases the accuracy of peak detection. Hence, this paper proposes a novel method to detect a pulse signal’s real peaks. The proposed method first smoothens a pulse signal by using a second-order Butterworth band-pass filter over a wide frequency range. Then, it considers the local minima of the signal as peaks and builds an optimization tree based on statistical properties, such as uniformity of peak time locations, peak count within a period, and variance in times elapsed between adjacent peaks, to detect combinations of peaks that optimize the heartrate computation. Results from experiments conducted using synthetic and real signals show that the proposed method can detect a pulse signal’s real peaks with higher precision as compared to conventional methods, and is very robust to signal noises. The proposed method has a significant heartrate estimation accuracy in various real scenarios and across smartphone models; its error rate is as low as 0.8588±0.0653 beats per minute, even in cases of signals with extensive noise. [ABSTRACT FROM AUTHOR]

Photo-plethysmography (PPG) is a non-contact non-invasive optical imaging technique which uses intensity and colour based information of transmitted or reflected light for bio-signal analysis. The major application areas are blood pulsation and blood oxygen saturation measurement. One of the major concerns of conventional PPG for blood pulsation measurement is its accuracy. Reflection based PPG contains a useful backscattered light component from the superficial and deep layer tissues of the skin and non-informative direct reflection from the skin surface. The direct reflection component reduces accuracy of blood pulsation measurement. This paper presents a technique, termed as Polarization Sensitive PPG (PSPPG), which removes the direct reflection component using polarizing filters. Experimental results show 30% improvement in the accuracy of blood pulsation measurement over conventional PPG. Further, statistical analysis of the measured results shows that the PSPPG is more accurate and reliable in comparison to conventional PPG for better bio-signal analysis. [ABSTRACT FROM AUTHOR]

In this paper, a blood pressure estimation system is proposed. Blood pressure variation is estimated by multiple regression analysis using photo-plethysmograph signals. Multiple regression analysis has been performed considering the multicollinearity between explanatory variations. Furthermore, by changing kinds of parameters of the pulse wave used for estimation, improvement of accuracy of blood pressure estimation has been aimed. Experimental results have shown that the estimated blood pressure values have been within about ±10mmHg as compared with measured blood pressure values using a cuff. [ABSTRACT FROM AUTHOR]

Abstract: Photo-plethysmography (PPG) is frequently used in research on microcirculation of blood. Usually PPG time series are analyzed by conventional linear methods, mainly Fourier analysis. These methods may not be optimal for the investigation of nonlinear effects of the heart circulation system like vasomotion, autoregulation, thermoregulation, breathing, heartbeat and vessels. PPG is a non-invasive procedure and takes minimal time to be carried out. The wavelet analysis of the PPG time series is a specific, sensitive nonlinear method for the in vivo identification of heart circulation patterns and human health status. This nonlinear analysis of PPG signals provides additional information which cannot be detected using conventional approaches. The wavelet analysis has been used to study healthy subjects and to characterize the health status of patients with a functional cutaneous microangiopathy which was associated with diabetic neuropathy. Additionally the fact that the absorption-coefficients and scattering-coefficients for blood differ at different wavelengths has been exploited and is used for calculation of the optical absorbability characteristics of human blood yielding information on blood components like hemoglobin and oxygen saturation. The measured PPG time signals and the ratio between the peak to peak pulse amplitudes are used for a measurement of these parameters. A newly developed PMD device has been introduced. The non-invasive in-vivo multi-spectral method is based on the radiation of monochromatic light, emitted by laser diodes, through an area of skin on the finger. Delays between the proportions of hemoglobin and plasma in the intravasal volume should be detected photo-electrically by signal-analytic evaluation of the signals. The computed nonlinear coefficients are used for the measurement and calculation of the relative hemoglobin concentration change. Results with this photometric method to measure changes in the hemoglobin concentration were demonstrated during measurements with a hemodynamic model and healthy subjects. The PMD is suitable for non-invasive continuous on-line monitoring of one or more biologic constituent values. The objective of this development is to reduce the dependence on measurement techniques which require that a sample of blood be withdrawn from the patient for in-vitro analysis. Any invasive method used on the patient to obtain blood is accompanied by problems of inconvenience, stress, and discomfort. The patient is also exposed to the normal risks of infection associated with such invasive methods. [Copyright &y& Elsevier]

In order to extract the pulse wave signal of blood volume effectively in the case of uneven light, a light-adaptive heart rate detection method based on webcam was proposed. In this method, adaptive gamma transform is applied to face image sequence to eliminate the influence of illumination. The pulse wave source signal was extracted from the forehead area and the blood volume pulse wave was obtained by wavelet filtering. The heart rate is estimated by Fourier transform analysis. The Bland-Altman analysis indicates that the method used in this paper is in good agreement with the measurement results of the electronic sphygmomanometer, and the adaptive gamma transformation used in this paper eliminates the influence of light interference, and the measurement error of heart rate is significantly reduced, which is completely able to meet the requirements of daily heart rate monitoring.

Aims: This cross-sectional study was set up to assess the feasibility of mass screening for atrial fibrillation (AF) with only the use of a smartphone., Methods and Results: A local newspaper published an article, allowing to subscribe for a 7-day screening period to detect AF. Screening was performed through an application that uses photo-plethysmography (PPG) technology by exploiting a smartphone camera. Participants received instructions on how to perform correct measurements twice daily, with notifications pushed through the application's software. In case of heart rhythm irregularities, raw PPG signals underwent secondary offline analysis to confirm a final diagnosis. From 12 328 readers who voluntarily signed up for screening (49 ± 14 years; 58% men), 120 446 unique PPG traces were obtained. Photo-plethysmography signal quality was adequate for analysis in 92% of cases. Possible AF was detected in 136 individuals (1.1%). They were older (P < 0.001), more frequently men (P < 0.001), and had higher body mass index (P = 0.004). In addition, participants who strictly adhered to the recommended screening frequency (i.e. twice daily) were more often diagnosed with possible AF (1.9% vs. 1.0% in individuals who did not adhere; P = 0.008). Symptoms of palpitations, confusion, and shortness of breath were more frequent in case of AF (P < 0.001). The cumulative diagnostic yield for possible AF increased from 0.4% with a single heart rhythm assessment to 1.4% with screening during the entire 7-day screening period., Conclusion: Mass screening for AF using only a smartphone with dedicated application based on PPG technology is feasible and attractive because of its low cost and logistic requirements., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2019. For permissions, please email: journals.permissions@oup.com.)