Video pulse rate variability analysis in stationary and motion conditions.

BACKGROUND: In the last few years, some studies have measured heart rate (HR) or heart rate variability (HRV) parameters using a video camera. This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. To date, most of these works have obtained HRV parameters in stationary conditions, and there are practically no studies that obtain these parameters in motion scenarios and by conducting an in-depth statistical analysis. METHODS: In this study, a video pulse rate variability (PRV) analysis is conducted by measuring the pulse-to-pulse (PP) intervals in stationary and motion conditions. Firstly, given the importance of the sampling rate in a PRV analysis and the low frame rate of commercial cameras, we carried out an analysis of two models to evaluate their performance in the measurements. We propose a selective tracking method using the Viola-Jones and KLT algorithms, with the aim of carrying out a robust video PRV analysis in stationary and motion conditions. Data and results of the proposed method are contrasted with those reported in the state of the art. RESULTS: The webcam achieved better results in the performance analysis of video cameras. In stationary conditions, high correlation values were obtained in PRV parameters with results above 0.9. The PP time series achieved an RMSE (mean ± standard deviation) of 19.45 ± 5.52 ms (1.70 ± 0.75 bpm). In the motion analysis, most of the PRV parameters also achieved good correlation results, but with lower values as regards stationary conditions. The PP time series presented an RMSE of 21.56 ± 6.41 ms (1.79 ± 0.63 bpm). CONCLUSIONS: The statistical analysis showed good agreement between the reference system and the proposed method. In stationary conditions, the results of PRV parameters were improved by our method in comparison with data reported in related works. An overall comparative analysis of PRV parameters in motion conditions was more limited due to the lack of studies or studies containing insufficient data analysis. Based on the results, the proposed method could provide a low-cost, contactless and reliable alternative for measuring HR or PRV parameters in non-clinical environments.

A methodology to quantify the differences between alternative methods of heart rate variability measurement.

This work proposes a systematic procedure to report the differences between heart rate variability time series obtained from alternative measurements reporting the spread and mean of the differences as well as the agreement between measuring procedures and quantifying how stationary, random and normal the differences between alternative measurements are. A description of the complete automatic procedure to obtain a differences time series (DTS) from two alternative methods, a proposal of a battery of statistical tests, and a set of statistical indicators to better describe the differences in RR interval estimation are also provided. Results show that the spread and agreement depend on the choice of alternative measurements and that the DTS cannot be considered generally as a white or as a normally distributed process. Nevertheless, in controlled measurements the DTS can be considered as a stationary process.

Facial Video-Based Photoplethysmography to Detect HRV at Rest.

Our aim is to demonstrate the usefulness of photoplethysmography (PPG) for analyzing heart rate variability (HRV) using a standard 5-min test at rest with paced breathing, comparing the results with real RR intervals and testing supine and sitting positions. Simultaneous recordings of R-R intervals were conducted with a Polar system and a non-contact PPG, based on facial video recording on 20 individuals. Data analysis and editing were performed with individually designated software for each instrument. Agreement on HRV parameters was assessed with concordance correlations, effect size from ANOVA and Bland and Altman plots. For supine position, differences between video and Polar systems showed a small effect size in most HRV parameters. For sitting position, these differences showed a moderate effect size in most HRV parameters. A new procedure, based on the pixels that contained more heart beat information, is proposed for improving the signal-to-noise ratio in the PPG video signal. Results were acceptable in both positions but better in the supine position. Our approach could be relevant for applications that require monitoring of stress or cardio-respiratory health, such as effort/recuperation states in sports.

Pulse rate variability analysis by video using face detection and tracking algorithms.

Heart rate variability (HRV) is a physiological parameter which has increased its importance in recent years due to its relationship with the autonomic nervous system (ANS) and cardiovascular disorders. In this work the pulse rate variability (PRV) is measured as a surrogate measurement of HRV using only a video of the face of the subject. Because of pulse rate signals obtained by video are largely affected by the person movements and the analyzed region of interest (ROI), we propose the application of face detection and tracking algorithms as a solution to the artifacts produced by these factors. We compare the obtained results of the proposed method with a pulse sensor signal of a reference system. The statistical analysis results show good agreement between both methods.

Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and fiducial point selection.

This work compares several fiducial points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and fiducial point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.

Real time heart rate variability assessment from Android smartphone camera photoplethysmography: Postural and device influences.

The aim of this paper is to present a smartphone based system for real-time pulse-to-pulse (PP) interval time series acquisition by frame-to-frame camera image processing. The developed smartphone application acquires image frames from built-in rear-camera at the maximum available rate (30 Hz) and the smartphone GPU has been used by Renderscript API for high performance frame-by-frame image acquisition and computing in order to obtain PPG signal and PP interval time series. The relative error of mean heart rate is negligible. In addition, measurement posture and the employed smartphone model influences on the beat-to-beat error measurement of heart rate and HRV indices have been analyzed. Then, the standard deviation of the beat-to-beat error (SDE) was 7.81 ± 3.81 ms in the worst case. Furthermore, in supine measurement posture, significant device influence on the SDE has been found and the SDE is lower with Samsung S5 than Motorola X. This study can be applied to analyze the reliability of different smartphone models for HRV assessment from real-time Android camera frames processing.

Heart rate variability analysis using a seismocardiogram signal.

Seismocardiography is a simple and non invasive method of recording cardiac activity from the movements of the body caused by heart pumping. In this preliminary study we use a smartphone to record this acceleration and estimate the heart rate. We compare the heart rate variability parameters from the seismocardiogram and ECG reference signal. The results show a great similarity and are strongly influenced by the instability in the sampling frequency of the device. The differences between RR series are lower than 10 ms.

New indices for quantification of the power spectrum of heart rate variability time series without the need of any frequency band definition.

This paper presents a new family of indices for the frequency domain analysis of heart rate variability time series that do not need any frequency band definition. After proper detrending of the time series, a cumulated power spectrum is obtained and frequencies that contain a certain percentage of the power below them are identified, so median frequency, bandwidth and a measure of the power spectrum asymmetry are proposed to complement or improve the classical spectral indices as the ratio of the powers of LF and HF bands (LF/HF). In normal conditions the median frequency provides similar information as the classical indices, while the bandwidth and asymmetry can be complementary measures of the physiological state of the tested subject. The proposed indices seem to be a good choice for tracking changes in the power spectrum in exercise stress, and they can guide in the determination of frequency band limits in other animal species.

Drowsiness detection by thoracic effort signal analysis in real driving environments.

Detection of drowsiness while driving is a leading objective in advanced driver assistance systems. This work presents a new index to assess the alertness state of drivers based on the respiratory dynamics derived from an inductive band. More than 100 hours of driving in real environments from 13 healthy subjects were analyzed. The proposed method has a sensitivity of 93.7% and specificity of 86.3% in detecting full awake drivers while it has a sensitivity of 83.1% and specificity of 95.3% in detecting drowsy drivers. The results show that the proposed index may be promising to assess the alertness state of real drivers.

The effect of electrocardiographic lead choice on RR time series.

Results of heart rate variability analysis depend on the quality of the initial RR time series that is measured only in one lead of the ECG. This work shows that RR time series can subtly change from lead to lead so the choice of the analyzed lead is another source of uncertainty. The standard deviation of the differences of two RR time series obtained from different leads can change from 0.5 ms to more than 20 ms depending on the amount of noise, the morphological changes of the QRS complexes, the strategies of fiducial point determination and the measured subject. This source of uncertainty is in healthy subjects greater than that associated to the sampling frequency of the ECG for sampling frequencies greater than 400 Hz.

Analog-to-digital converters nonlinear errors correction in thermal diagnostics for the laser interferometer space antenna mission.

Low-noise temperature measurements at frequencies in the millihertz range are required in the laser interferometer space antenna (LISA) and LISA PathFinder missions. The required temperature stability for LISA is around 10 microK Hz(-1/2) at frequencies down to 0.1 mHz. In this paper we focus on the identification and reduction in a source of excess noise detected when measuring time-varying temperature signals. This is shown to be due to nonidealities in the analog-to-digital converter (ADC) transfer curve, and degrades the measurement by about one order of magnitude in the measurement bandwidth when the measured temperature drifts by a few approximately microK s(-1). In a suitable measuring system for the LISA mission, this noise needs to be reduced. Two different methods based on the same technique have been implemented, both consisting in the addition of dither signals out of band to mitigate the ADC nonideality errors. Excess noise of this nature has been satisfactorily reduced by using these methods when measuring temperature ramps up to 10 microK s(-1).

Magnetic polarization effects of temperature sensors and heaters in LISA Pathfinder.

Temperature sensors and heaters belong in the diagnostics subsystem of the LISA Technology Package (LTP) on board LISA Pathfinder, the technology demonstrator for LISA. A number of these diagnostics items are placed at short distances from the LTP proof masses and are negative temperature coefficient (NTC) thermistors. By design, these devices have tiny amounts of ferromagnetic materials, which therefore constitute a potential source of disturbance to the performance of the LTP. In this paper we report on detailed magnetic characterization of the NTCs and use the data to evaluate their impact on the acceleration noise budget of the LTP. The effect is seen to be small if the NTCs are submitted to a demagnetization process before they are attached. Remagnetization is unlikely, as rather strong fields (approximately millitesla) are required to produce enough NTC magnetic polarization.

Thermal diagnostics front-end electronics for LISA Pathfinder.

Precision temperature measurements are required in the LTP, the LISA technology package, for various diagnostics objectives. In this article, we describe in detail the front-end electronics design and the associated temperature sensors to achieve the LTP requirements: noise equivalent temperature of 10 microK Hz(-12) in the frequency range from 1 to 30 mHz at room temperature. We designed an ac Wheatstone bridge and a subsequent digital demodulation to minimize 1/f noise. We show experimental results where the required sensitivity in the measurement bandwidth is fulfilled.

Estimation of the uncertainty in time domain indices of RR time series.

A method for estimating the uncertainty in time-domain indices of RR time series is described. The method relies on the central limit theorem that states that the distribution of a sample average of independent samples has an uncertainty that asymptotically approaches to the sample standard deviation divided by the square root of the number of samples. Because RR time series cannot be characterized by a set of independent samples, we propose to estimate the uncertainty of indices by computing them in blocks that satisfy that the obtained partial indices are independent. We propose a methodology to search sets of independent partial indices and apply this methodology to the estimation of the uncertainty in the mean RR, SDRR, and r-msDD indices. The results show that the uncertainty can be higher than the 10% of the index for the SDRR and even higher for the r-msDD. Moreover, a statistical test for the difference of two indices is proposed.

Síndrome de Lemierre / Lemierre syndrome

La sepsis postanginal o síndrome de Lemierre es una enfermedad rara en nuestros tiempos que ocurre después de una infección orofaríngea y se manifiesta por una tromboflebitis séptica de la vena yugular interna e infecciones metastásicas. Es producida por microorganismos anaerobios, siendo el Fusobacterium necrophorum el más frecuente. Para su diagnóstico, a parte del aislamiento microbiológico del germen, son fundamentales las pruebas de imagen como la ecografía doppler y la tomografía axial computarizada (TAC). El tratamiento consiste en antibioterapia precoz, prolongada, a dosis altas y en ocasiones la excisión quirúrgica de las venas yugulares

Postanginal sepsis or Lemierre syndrome is a rare disease in our times that occurs after an oropharyngeal infection and is manifested by septic thrombophlebitis of the internal jugular vein and metastatic infections. It is produced by anaerobic germs, Fusobacterium necrophorum being the most frequent. Besides the microbiological isolation of the germ, image tests such as Doppler ultrasound and computed-tomography (CT) scan are fundamental for its diagnosis. Treatment consists in early, prolonged antibiotic treatment at high doses and sometimes surgical excision of the jugular veins. We present the case of an adolescent who had serious septic shock that evolved to multiorganic failure after being diagnosed of this syndrome. As a special finding, we discovered the presence of thrombosis in the left external jugular vein

Traumatismo abdominal cerrado con sección pancreática / Pancreatic lesions in closed abdominal trauma

Las lesiones traumáticas del páncreas son poco frecuentes pero se acompañan de una gran morbimortalidad, sobre todo si se demora el diagnóstico y consecuentemente el tratamiento, cosa relativamente habitual dada su escasa sintomatología. Por tanto, es muy importante valorar el mecanismo lesional que nos hará sospechar este tipo de lesión. La tomografía computarizada (TC) helicoidal es de gran utilidad diagnóstica. La actitud terapéutica está condicionada por la integridad o no del conducto pancreático. Presentamos el caso de un paciente con trauma abdominal cerrado en el que la TC de ingreso fue normal a pesar de tener una sección pancreática que se visualizó tres días después. Se complicó con una disfunción multiorgánica que evolucionó favorablemente

Traumatic lesions of the pancreas are not very common but accompanied by a high morbimortality rate, especially if diagnosis and subsequent treatment are delayed, which is relatively common given its poor symptomology. It is, therefore, very important to evaluate the lesional mechanism which would lead one to suspect this type of lesion. Spiral CAT is very useful diagnostic tool. Therapeutic approach is conditioned on pancreatic duct integrity. Herein is presented the case of a patient with closed abdominal trauma whose CT at admittance was normal in spite of having had a pancreatic lesion being observed three days later. It was further complicated by a multiorgan dysfunction which evolved favorably

Bias and uncertainty in heart rate variability spectral indices due to the finite ECG sampling frequency.

Spectral analysis of the heart rate variability is becoming a usual tool as a marker of the autonomic nervous system. The final output of the spectral analysis is a set of indices that are always estimators due to technical limitations. In this work, the bias and the uncertainty in the VLF, LF, HF and LF/HF indices due to the finite sampling frequency of the ECG are analysed. The results indicate that for low sampling frequency (125 Hz), the bias and uncertainty in the HF and LF/HF indices can blur the results of the analysis, especially if the RR time series has low variability. The HF index is overestimated and, accordingly, the LF/HF index is underestimated. Then, results from RR time series with low sampling frequency must be used with care. The uncertainty of the spectral indices is proportional to the inverse of the sampling frequency and the bias is proportional to the inverse of the square sampling frequency.

A new index for the analysis of heart rate variability dynamics: characterization and application.

A new index for the analysis of the heart rate variability (HRV) dynamics is presented. The proposed index (acceleration change index (ACI)) characterizes the sign of the differences of a time series. A theoretical study shows an expression that relates ACI and the autocorrelation function of the time series. This formula is tested and validated with different simulated time series (uncorrelated noise, sinusoidal and fractional Brownian motion). Next, ACI is applied to RR time series from healthy subjects showing that ACI decreases with periodic controlled breathing, increases during exercise, and it has a lower value at night than during the day. In a preliminary study, ACI has been shown to be lower in healthy subjects than in patients who had suffered a myocardial infarction one month previously. ACI can be employed as a fast and robust new marker of the HRV dynamics.