On the use of fractional calculus to improve the pulse arrival time (PAT) detection when using photoplethysmography (PPG) and electrocardiography (ECG) signals.

The pulse arrival time (PAT) has been considered a surrogate measure for pulse wave velocity (PWV), although some studies have noted that this parameter is not accurate enough. Moreover, the inter-beat interval (IBI) time series obtained from successive pulse wave arrivals can be employed as a surrogate measure of the RR time series avoiding the use of electrocardiogram (ECG) signals. Pulse arrival detection is a procedure needed for both PAT and IBI measurements and depends on the proper fiducial points chosen. In this paper, a new set of fiducial points that can be tailored using several optimization criteria is proposed to improve the detection of successive pulse arrivals. This set is based on the location of local maxima and minima in the systolic rise of the pulse wave after fractional differintegration of the signal. Several optimization criteria have been proposed and applied to high-quality recordings of a database with subjects who were breathing at different rates while sitting or standing. When a proper fractional differintegration order is selected by using the RR time series as a reference, the agreement between the obtained IBI and RR is better than that for other state-of-the-art fiducial points. This work tested seven different traditional fiducial points. For the agreement analysis, the median standard deviation of the difference between the IBI and RR time series is 5.72 ms for the proposed fiducial point versus 6.20 ms for the best-performing traditional fiducial point, although it can reach as high as 9.93 ms for another traditional fiducial point. Other optimization criteria aim to reduce the standard deviation of the PAT (7.21 ms using the proposed fiducial point versus 8.22 ms to 15.4 ms for the best- and worst-performing traditional fiducial points) or to minimize the standard deviation of the PAT attributable to breathing (3.44 ms using the proposed fiducial point versus 4.40 ms to 5.12 ms for best- and worst-performing traditional fiducial points). The use of these fiducial points may help to better quantify the beat-to-beat PAT variability and IBI time series.

A Serious Game to Self-Regulate Heart Rate Variability as a Technique to Manage Arousal Level Through Cardiorespiratory Biofeedback: Development and Pilot Evaluation Study.

BACKGROUND: Heart rate variability biofeedback (HRVB) is an established intervention for increasing heart rate variability (HRV) in the clinical context. Using this technique, participants become aware of their HRV through real-time feedback and can self-regulate it. OBJECTIVE: The aim of this study was 2-fold: first, to develop a serious game that applies the HRVB technique to teach participants to self-regulate HRV and, second, to test the app with participants in a pilot study. METHODS: An HRVB app called the FitLab Game was developed for this study. To play the game, users must move the main character up and down the screen, avoiding collisions with obstacles. The wavelength that users must follow to avoid these obstacles is based on the user's basal heart rate and changes in instantaneous heart rate. To test the FitLab Game, a total of 16 participants (mean age 23, SD 0.69 years) were divided into a control group (n=8) and an experimental group (n=8). A 2 × 2 factorial design was used in each session. Participants in the experimental condition were trained in breathing techniques. RESULTS: Changes in the frequency and time domain parameters of HRV and the game's performance features were evaluated. Significant changes in the average RR intervals and root mean square of differences between adjacent RR intervals (RMSSD) were found between the groups (P=.02 and P=.04, respectively). Regarding performance, both groups showed a tendency to increase the evaluated outcomes from baseline to the test condition. CONCLUSIONS: The results may indicate that playing different levels leads to an improvement in the game's final score by repeated training. The tendency of changes in HRV may reflect a higher activation of the mental system of attention and control in the experimental group versus the control group. In this context, learning simple, voluntary strategies through a serious game can aid the improvement of self-control and arousal management. The FitLab Game appears to be a promising serious game owing to its ease of use, high engagement, and enjoyability provided by the instantaneous feedback.

Agreement between two photoplethysmography-based wearable devices for monitoring heart rate during different physical activity situations: a new analysis methodology.

Wearables are being increasingly used to monitor heart rate (HR). However, their usefulness for analyzing continuous HR in research or at clinical level is questionable. The aim of this study is to analyze the level of agreement between different wearables in the measurement of HR based on photoplethysmography, according to different body positions and physical activity levels, and compared to a gold-standard ECG. The proposed method measures agreement among several time scales since different wearables obtain HR at different sampling rates. Eighteen university students (10 men, 8 women; 22 ± 2.45 years old) participated in a laboratory study. Participants simultaneously wore an Apple Watch and a Polar Vantage watch. ECG was measured using a BIOPAC system. HR was recorded continuously and simultaneously by the three devices, for consecutive 5-min periods in 4 different situations: lying supine, sitting, standing and walking at 4 km/h on a treadmill. HR estimations were obtained with the maximum precision offered by the software of each device and compared by averaging in several time scales, since the wearables obtained HR at different sampling rates, although results are more detailed for 5 s and 30 s epochs. Bland-Altman (B-A) plots show that there is no noticeable difference between data from the ECG and any of the smartwatches while participants were lying down. In this position, the bias is low when averaging in both 5 s and 30 s. Differently, B-A plots show that there are differences when the situation involves some level of physical activity, especially for shorter epochs. That is, the discrepancy between devices and the ECG was greater when walking on the treadmill and during short time scales. The device showing the biggest discrepancy was the Polar Watch, and the one with the best results was the Apple Watch. We conclude that photoplethysmography-based wearable devices are suitable for monitoring HR averages at regular intervals, especially at rest, but their feasibility is debatable for a continuous analysis of HR for research or clinical purposes, especially when involving some level of physical activity. An important contribution of this work is a new methodology to synchronize and measure the agreement against a gold standard of two or more devices measuring HR at different and not necessarily even paces.

Resistive-Based Micro-Kelvin Temperature Resolution for Ultra-Stable Space Experiments.

High precision temperature measurements are a transversal need in a wide area of physical experiments. Space-borne gravitational wave detectors are a particularly challenging case, requiring both high precision and high stability in temperature measurement. In this contribution, we present a design able to reach 1 µK/Hz in most of the measuring band down to 1 mHz, and reaching 20 µK/Hz at 0.1 mHz. The scheme is based on resistive sensors in a Wheatstone bridge configuration which is AC modulated to minimize the 1/f noise. As a part of our study, we include the design of a test bench able to guarantee the high stability environment required for measurements. We show experimental results characterising both the test bench and the read-out, and discuss potential noise sources that may limit our measurement.

Analysis of Gender Differences in HRV of Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Mobile-Health Technology.

In a previous study using mobile-health technology (mHealth), we reported a robust association between chronic fatigue symptoms and heart rate variability (HRV) in female patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). This study explores HRV analysis as an objective, non-invasive and easy-to-apply marker of ME/CFS using mHealth technology, and evaluates differential gender effects on HRV and ME/CFS core symptoms. In our methodology, participants included 77 ME/CFS patients (32 men and 45 women) and 44 age-matched healthy controls (19 men and 25 women), all self-reporting subjective scores for fatigue, sleep quality, anxiety, and depression, and neurovegetative symptoms of autonomic dysfunction. The inter-beat cardiac intervals are continuously monitored/recorded over three 5-min periods, and HRV is analyzed using a custom-made application (iOS) on a mobile device connected via Bluetooth to a wearable cardiac chest band. Male ME/CFS patients show increased scores compared with control men in all symptoms and scores of fatigue, and autonomic dysfunction, as with women in the first study. No differences in any HRV parameter appear between male ME/CFS patients and controls, in contrast to our findings in women. However, we have found negative correlations of ME/CFS symptomatology with cardiac variability (SDNN, RMSSD, pNN50, LF) in men. We have also found a significant relationship between fatigue symptomatology and HRV parameters in ME/CFS patients, but not in healthy control men. Gender effects appear in HF, LF/HF, and HFnu HRV parameters. A MANOVA analysis shows differential gender effects depending on the experimental condition in autonomic dysfunction symptoms and HF and HFnu HRV parameters. A decreased HRV pattern in ME/CFS women compared to ME/CFS men may reflect a sex-related cardiac autonomic dysfunction in ME/CFS illness that could be used as a predictive marker of disease progression. In conclusion, we show that HRV analysis using mHealth technology is an objective, non-invasive tool that can be useful for clinical prediction of fatigue severity, especially in women with ME/CFS.

Resonance frequency is not always stable over time and could be related to the inter-beat interval.

Heart Rate Variability Biofeedback (HRVB) is based on breathing at an optimal rate (or resonance frequency, RF) corresponding to the respiratory sinus arrhythmia (RSA). Our aim is to check whether the RF is a stable factor and analyse the HRV parameters individually per each breathing rate, comparing it with free slow breathing. A sample of 21 participants were trained in a test-retest HRVB protocol. The results indicated that RF changed between Test and Retest sessions in 66.7% of participants. This instability could be related to the average of interbeat interval (IBI). HRV time domain parameters (SDNN and RMSSD) were significantly higher for RF than for other breathing rates, including 6 breath/min and free slow breathing. Free slow breathing showed a lower heart rate averages than RF and other slow breathing rates. Overall, our study suggests the relevance of assessing RF individually and before each HRVB session, because the maximum cardiovascular benefits in terms of increasing HRV were found only at RF. Thus, breathing at the individualized and momentary frequency of resonance increases cardiac variability.

Individual recovery profiles in basketball players.

In the sport context, recovery has been characterized as a multifactor process (physiological, psychological, behavioral, social, etc.). This study takes a multidisciplinary approach to find psychophysiological markers of the stress-recovery process. It aims to determine how athletes' specific recovery actions relate to their perceptions of recovery, and Heart Rate Variability (HRV). A total of 196 assessments were analyzed from 6 players on a men's professional basketball team within the Liga LEB Oro basketball federation (2012/2013 season). Perceptions of recovery, recovery strategies, and HRV were recorded. The results show a pattern of individual differences in behavior related to athletes' recovery actions and HRV profiles throughout the season (p < .05). Moreover, we observed that each player had different recovery needs. In light of these results, we suggest an individualistic approach to evaluating and monitoring recovery to attend more accurately to each player's recovery needs.

Individual recovery profiles in basketball players

In the sport context, recovery has been characterized as a multifactor process (physiological, psychological, behavioral, social, etc.). This study takes a multidisciplinary approach to find psychophysiological markers of the stress-recovery process. It aims to determine how athletes’ specific recovery actions relate to their perceptions of recovery, and Heart Rate Variability (HRV). A total of 196 assessments were analyzed from 6 players on a men’s professional basketball team within the Liga LEB Oro basketball federation (2012/2013 season). Perceptions of recovery, recovery strategies, and HRV were recorded. The results show a pattern of individual differences in behavior related to athletes’ recovery actions and HRV profiles throughout the season (p < .05). Moreover, we observed that each player had different recovery needs. In light of these results, we suggest an individualistic approach to evaluating and monitoring recovery to attend more accurately to each player’s recovery needs (AU)

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An application of fractional differintegration to heart rate variability time series.

Fractional differintegration is used as a new tool to characterize heart rate variability time series. This paper proposes and focuses in two indexes (αc and fnQ) derived from the fractional differintegration operator. Both indexes are applied to fractional Gaussian noise (fGn) and actual RR time series in order to test their behavior. In the analysis of monofractal time series, αc is linearly related with the Hurst exponent and the estimation of the exponent by the proposed index has lower variance than by using Detrended Fluctuation Analysis (DFA) or the periodogram. The other index fnQ quantifies how the time series adjust to a monofractal time series. Age, postural changes and paced breathing cause significant changes on fnQ while αc only shows significant changes due to posture. In the analyzed actual HRV time series, αc shows good correlation with the short term scaling exponent obtained by DFA, LF/HF and RMSSD while no correlations have been found for fnQ.

HRV based health&sport markers using video from the face.

Heart Rate Variability (HRV) is an indicator of health status in the general population and of adaptation to stress in athletes. In this paper we compare the performance of two systems to measure HRV: (1) A commercial system based on recording the physiological cardiac signal with (2) A computer vision system that uses a standard video images of the face to estimate RR from changes in skin color of the face. We show that the computer vision system performs surprisingly well. It estimates individual RR intervals in a non-invasive manner and with error levels comparable to those achieved by the physiological based system.

Errors in the estimation of approximate entropy and other recurrence-plot-derived indices due to the finite resolution of RR time series.

An analysis of the errors due to the finite resolution of RR time series in the estimation of the approximate entropy (ApEn) is described. The quantification errors in the discrete RR time series produce considerable errors in the ApEn estimation (bias and variance) when the signal variability or the sampling frequency is low. Similar errors can be found in indices related to the quantification of recurrence plots. An easy way to calculate a figure of merit [the signal to resolution of the neighborhood ratio (SRN)] is proposed in order to predict when the bias in the indices could be high. When SRN is close to an integer value n, the bias is higher than when near n - 1/2 or n + 1/2. Moreover, if SRN is close to an integer value, the lower this value, the greater the bias is.

Novel indices of ventricular repolarization to screen post myocardial infarction patients.

We propose novel indices of ventricular repolarization intervals, the JTp/JT, Tpe/JTp and Tpe/JT ratios. These indices have been compared with the duration of the ventricular repolarization intervals and other ratios in 17 normal subjects and 17 patients with old myocardial infarction. In the intervals and other ratios, the best separation between groups is obtained with the Tpe/QTp and Tpe/QT ratios with 94% sensitivity and 82% specificity, the proposed ratios increased sensitivity to 100% and specificity to 94%. These indices should be further tested to determine their usefulness in discriminating between OMI patients with and without susceptibility to ventricular arrhythmias.