Eduardo Gil

Photoplethysmography pulse rate variability as a surrogate measurement of heart rate variability during non-stationary conditions

In this paper we assessed the possibility of using the pulse rate variability (PRV) extracted from the photoplethysmography signal as an alternative measurement of the HRV signal in non-stationary conditions. The study is based on analysis of the changes observed during a tilt table test in the heart rate modulation of 17 young subjects. First, the classical indices of HRV analysis were compared to the indices from PRV in intervals where stationarity was assumed. Second, the time-varying spectral properties of both signals were compared by time-frequency (TF) and TF coherence analysis. Third, the effect of replacing PRV with HRV in the assessment of the changes of the autonomic modulation of the heart rate was considered. Time-invariant HRV and PRV indices showed no statistically significant differences (p > 0.05) and high correlation (>0.97). Time-frequency analysis revealed that the TF spectra of both signals were highly correlated (0.99 +/- 0.01); the difference between the instantaneous power, in the LF and HF bands, obtained from HRV and PRV was small (<10(-3) s(-2)) and their temporal patterns were highly correlated (0.98 +/- 0.04 and 0.95 +/- 0.06 in the LF and HF bands, respectively) and TF coherence in the LF and HF bands was high (0.97 +/- 0.04 and 0.89 +/- 0.08, respectively). Finally, the instantaneous power in the LF band was observed to significantly increase during head-up tilt by both HRV and PRV analysis. These results suggest that although some differences in the time-varying spectral indices extracted from HRV and PRV exist, mainly in the HF band associated with respiration, PRV could be used as a surrogate of HRV during non-stationary conditions, at least during the tilt table test.

Detection of decreases in the amplitude fluctuation of pulse photoplethysmography signal as indication of obstructive sleep apnea syndrome in children

Abstract In this paper, a methodology for using pulse photoplethysmography (PPG) signal to automatically detect sleep apnea is proposed. The hypothesis is that decreases in the amplitude fluctuations of PPG (DAP), are originated by discharges of the sympathetic branch of autonomic nervous system, related to arousals caused by apnea. To test this hypothesis, an automatic system to detect DAP events is proposed. The detector was evaluated using real signals, and tested on a clinical experiment. The overall data set used in the studies includes the polysomnographic records of 26 children which were further subdivided depending on the evaluation of interest. For real signals, the sensitivity and positive predictive value of the DAP detector were 76% and 73%, respectively. An apnea detector has been developed to analyze the relationship between apneas and DAP, indicating that DAP events increase by about 15 % when an apnea occurs compared to when apneas do not occur. A clinical study evaluating the diagnostic power of DAP in sleep apnea in children was carried out. The DAP per hour ratio r DAP was statistically significant ( p = 0.033 ) in classifying children as either normal r DAP = 13.5 ± 6.35 (mean ± S.D.) or pathologic r DAP = 21.1 ± 8.93 . These results indicate a correlation between apneic events and DAP events, which suggests that DAP events could provide relevant information in sleep studies. Therefore, PPG signals might be useful in the diagnosis of OSAS.

PTT Variability for Discrimination of Sleep Apnea Related Decreases in the Amplitude Fluctuations of PPG Signal in Children

In this paper, an analysis of pulse transit time variability (PTTV) during decreases in the amplitude fluctuations of pulse photoplethysmography signal (PPG) (DAP) events for obstructive sleep apnea syndrome (OSAS) screening is presented. The temporal evolution of time-frequency PTTV parameters during DAP was analyzed. The results show an increase in the sympathetic activity index low-frequency component (LF) during DAP for PTTV (85%) significantly higher than for heart rate variability (HRV) (33%), (¿ < 10^-13). However, decreases in parasympathetic activity produce lower decrements in high-frequency component (HF) indexes for PTTV (18%) than for HRV (22%). Thus, PTTV reflects sympathetic changes more clearly than HRV. A clinical study was carried out. DAP events were classified as apneic or nonapneic using a linear discriminant analysis from the PTTV indexes. The ratio of DAP events per hour <i>r</i> _DAP, the ratio after filtering based on HRV indexes <i>r</i> ^HRV _DAP, or on PTTV indexes <i>r</i> ^PTTV _DAP, were computed. The results show an accuracy of 75% for <i>r</i> ^PTTV _DAP (14% increase with respect to <i>r</i> _DAP and 5% increase with respect to <i>r</i> ^HRV _DAP), a sensitivity of 81.8%, and a specificity of 73.9% when classifying 1-h polysomnographic excerpts as OSAS or normal. These results suggest that the combination of DAP and PTTV could be better alternative for sleep apnea screening using PPG with the added benefit of its low cost and simplicity.

Discrimination of Sleep-Apnea-Related Decreases in the Amplitude Fluctuations of PPG Signal in Children by HRV Analysis

In this paper, an analysis of heart rate variability (HRV) during decreases in the amplitude fluctuations of photopletysmography (PPG) [decreases in the amplitude fluctuations of photopletysmography (DAP)] events for obstructive sleep apnea syndrome (OSAS) screening is presented. Two hundred and sixty-eight selected signal segments around the DAP event were extracted and classified in five groups depending on SaO2 and respiratory behavior. Four windows around each DAP are defined and temporal evolution of time-frequency HRV parameters was analyzed for OSAS screening. Results show a significant increase in sympathetic activity during DAP events, which is higher in cases associated with apnea. DAP events were classified as apneic or nonapneic using a linear discriminant analysis from the HRV indexes. The ratio of DAP events per hour r DAP and the ratio of apneic DAP events per hour r alpha DAP were computed. Results show an accuracy of 79% for r alpha DAP (12% increase with respect to r DAP), a sensitivity of 87.5%, and a specificity of 71.4% when classifying 1-h polysomnographic excerpts. As for clinical subject classification, an accuracy of 80% (improvement of 6.7% ), a sensitivity of 87.5%, and a specificity of 71.4% are reached. These results suggest that the combination of DAP and HRV could be an improved alternative for sleep apnea screening from PPG with the added benefit of its low cost and simplicity.

Pulse Rate Variability Analysis for Discrimination of Sleep-Apnea-Related Decreases in the Amplitude Fluctuations of Pulse Photoplethysmographic Signal in Children

A technique for ambulatory diagnosis of the obstructive sleep apnea syndrome (OSAS) in children based on pulse photoplethysmographic (PPG) signal is presented. Decreases in amplitude fluctuations of the PPG signal (DAP) events have been proposed as OSAS discriminator, since they are related to vasoconstriction associated to apnea. Heart rate variability (HRV) analysis during these DAP events has been proposed to discriminate between DAP events related or unrelated to an apneic event. The use of HRV requires electrocardiogram (ECG) as an additional recording, meaning a disadvantage that takes more relevance in sleep studies context where the number of sensors is tried to be minimized in order not to affect the physiological sleep. This study proposes the use of pulse rate variability (PRV) extracted from the PPG signal instead of HRV. Polysomnographic registers from 21 children (aged 4.47 ±2.04 years) were studied. The subject classification based on DAP events and PRV analysis obtained an accuracy of 86.67% which represents an improvement of 6.67% with respect to the HRV analysis. These results suggest that PRV can be used in apnea detectors based on DAP events, to discriminate apneic from nonapneic events avoiding the need for ECG recordings.

On Arousal from Sleep: Time-Frequency Analysis

Time-frequency analysis of the heart rate variability during arousal from sleep, with and without EMG activation, coming from five obese healthy subjects was performed. Additionally, a comparative analysis of three time-frequency distributions, smooth pseudo Wigner–Ville (SPWVD), Choi–Williams (CWD) and Born–Jordan distribution (BJD) is presented in this study. SPWVD showed higher capacity for eliminating the cross terms independently of the signal. After applying Hilbert transformation to real signals BJD and CWD lost some important mathematic properties as marginals, on the contrary PSWVD remains unchanged. BJD showed results comparable with CWD. During arousal episodes, analogous energy distribution and spectral indexes were obtained by the three time-frequency representations. Arousals with chin activity presented stronger changes in RR intervals and LF (related to sympathetic activity) component, being statistically different with respect to arousal without chin activity, only around the period of maximum change in β activity on the EEG. These results suggest a more evident stress for the heart when an arousal is related to external muscular activity.

Heart Rate Turbulence Analysis Based on Photoplethysmography

The goal of this paper is to determine whether the photoplethysmography (PPG) can replace the ECG-based detection of heart rate turbulence. Using the PPG, classification of ventricular premature beats (VPBs) is accomplished with a linear classifier. The two conventional parameters turbulence onset and slope are studied together with a recently introduced parameter characterizing turbulence shape. Performance is studied on a dataset with 4131 VPBs, recorded from a total of 27 patients in different clinical contexts (hemodialysis treatment, intensive care monitoring, and electrophysiological study). The sensitivity/specificity of VPB classification was found to be 90.5/99.9%, with an accuracy of 99.3%, suggesting that classification of VPBs can be reliable made from the PPG. The main difference between the two types of turbulence analysis stems from the fact that the pulse transit time varies largely immediately after the VPB. Out of the 22 patients which had a sufficient number of VPBs, the outcome of the ECG- and PPG-based analysis was identical in 21. It is concluded that the PPG may serve as a surrogate technique for the ECG in turbulence analysis.

Noninvasive Techniques for Prevention of Intradialytic Hypotension

Episodes of hypotension during hemodialysis treatment constitutes an important clinical problem which has received considerable attention in recent years. Despite the fact that numerous approaches to reducing the frequency of intradialytic hypotension (IDH) have been proposed and evaluated, the problem has not yet found a definitive solution-an observation which, in particular, applies to episodes of acute, symptomatic hypotension. This overview covers recent advances in methodology for predicting and preventing IDH. Following a brief overview of well-established hypotension-related variables, including blood pressure, blood temperature, relative blood volume, and bioimpedance, special attention is given to electrocardiographic and photoplethysmographic (PPG) variables and their significance for IDH prediction. It is concluded that cardiovascular variables which reflect heart rate variability, heart rate turbulence, and baroreflex sensitivity are important to explore in feedback control hemodialysis systems so as to improve their performance. The analysis of hemodialysis-related changes in PPG pulse wave properties hold considerable promise for improving prediction.

Inclusion of Respiratory Frequency Information in Heart Rate Variability Analysis for Stress Assessment

Respiratory rate and heart rate variability (HRV) are studied as stress markers in a database of young healthy volunteers subjected to acute emotional stress, induced by a modification of the Trier Social Stress Test. First, instantaneous frequency domain HRV parameters are computed using time-frequency analysis in the classical bands. Then, the respiratory rate is estimated and this information is included in HRV analysis in two ways: 1) redefining the high-frequency (HF) band to be centered at respiratory frequency; 2) excluding from the analysis those instants where respiratory frequency falls within the low-frequency (LF) band. Classical frequency domain HRV indices scarcely show statistical differences during stress. However, when including respiratory frequency information in HRV analysis, the normalized LF power as well as the LF/HF ratio significantly increase during stress (p-value <; 0.05 according to the Wilcoxon test), revealing higher sympathetic dominance. The LF power increases during stress, only being significantly different in a stress anticipation stage, while the HF power decreases during stress, only being significantly different during the stress task demanding attention. Our results support that joint analysis of respiration and HRV obtains a more reliable characterization of autonomic nervous response to stress. In addition, the respiratory rate is observed to be higher and less stable during stress than during relax (p-value <; 0.05 according to the Wilcoxon test) being the most discriminative index for stress stratification (AUC = 88.2%).

Pulse Photopletismography Amplitude Decrease Detector for Sleep Apnea Evaluation in Children

A method for automatic detection of sleep apnea using pulse photoplethysmography signal (PPG) is proposed. This method is based on a detection of decreases on PPG amplitude fluctuations. The proposed detector is composed of three stages: pre-processing, envelope detection, based on root mean square series or Hilbert transform, and decision algorithm based on an adaptive threshold. The detector has been evaluated using simulated and real signals. Sensibility and positive predictive value of the detector where 76% and 73% for real signals. A clinical study to sleep apnea diagnosis in children based on this detector has been carried out. PPG attenuation events per hour ratio E h has statistical significance (p < 0.05) to classify children as normal 13.5 plusmn 6.35 Eh (mean plusmn SD) or pathologic 21.1 plusmn 8.93 Eh