Respiratory Rate Derived from Pulse Photoplethysmographic Signal by Pulse Decomposition Analysis

A novel technique to derive respiratory rate from pulse photoplethysmographic (PPG) signals is presented. It exploits some morphological features of the PPG pulse that are known to be modulated by respiration: amplitude, slope transit time, and width of the main wave, and time to the first reflected wave. A pulse decomposition analysis technique is proposed to measure these features. This technique allows to decompose the PPG pulse into its main wave and its subsequent reflected waves, improving the robustness against noise and morphological changes that usually occur in long-term recordings. Proposed methods were evaluated with a data base containing PPG and plethysmography-based respiratory signals simultaneously recorded during a paced-breathing experiment. Results suggest that normal ranges of spontaneous respiratory rate (0.1-0.5 Hz) can be accurately estimated (median and interquartile range of relative error less than 5%) from PPG signals by using the studied features

Non-linear analysis of heart rate variability and its application to predict hypotension during spinal anesthesia for cesarean delivery

A non-linear analysis of heart rate variability is carried out through two complexity measures (Correlation Dimension and Pointwise Correlation Dimension) and two regularity measures (Approximate Entropy and Sample Entropy) in order to predict hypotension episodes occurred during spinal anesthesia in cesarean delivery. These methods are applied to RR-interval series, during which woman adopts two alternative positions, one physiologically relaxed (PR) and one physiologically stressed (PS). Results show that women who developed hypotension have significantly higher (p-value = 0.05) complexity measures at PR position, (and significantly lower values for the PS position), than those who did not developed the disease. Regarding the regularity measures, women who developed hypotension have lower values, but not arriving to significance, during PS position than those who did not developed it, whereas those values remain almost constant for PR position

Photoplethysmogram Signal Morphology-Based Stress Assessment

Stress is a healthy natural response to a perceived or actual threat. However, when stress is persistent, it may decrease work productivity, increase the risk of diseases, and affect the quality of life. Stress is reflected in physiological variables, such as heart rate, blood pressure, and pulse wave velocity among others. A photoplethys-mogram (PPG) contains information related to pulse rate and blood pressure. This study analyses parameters derived from PPG signal morphology for mental stress assessment.A low-complexity algorithm is designed using bandpass filtered higher-order derivatives of the PPG signal for estimation of six morphological parameters: the forward pulse wave amplitude A1, the systole and diastole durations T1 and Td, the time delays of reflected waves T12 and T13 from the renal and iliac sites in the central arteries, and the pulse duration Tp. The parameters were investigated on a set of 18 healthy subjects by using a modified Trier Social Stress Test.The results show that the most sensitive PPG morphology parameters to mental stress are the amplitude of forward wave A1, the duration of diastole Td, the time delay of the reflected wave T13, and the pulse-to-pulse interval Tp

Human emotion characterization by heart rate variability analysis guided by respiration

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksDeveloping a tool which identifies emotions based on their effect on cardiac activity may have a potential impact on clinical practice, since it may help in the diagnosing of psycho-neural illnesses. In this study, a method based on the analysis of heart rate variability (HRV) guided by respiration is proposed. The method was based on redefining the high frequency (HF) band, not only to be centered at the respiratory frequency, but also to have a bandwidth dependent on the respiratory spectrum. The method was first tested using simulated HRV signals, yielding the minimum estimation errors as compared to classical and respiratory frequency centered at HF band based definitions, independently of the values of the sympathovagal ratio. Then, the proposed method was applied to discriminate emotions in a database of video-induced elicitation. Five emotional states, relax, joy, fear, sadness and anger, were considered. The maximum correlation between HRV and respiration spectra discriminated joy vs. relax, joy vs. each negative valence emotion, and fear vs. sadness with p-value = 0.05 and AUC = 0.70. Based on these results, human emotion characterization may be improved by adding respiratory information to HRV analysis.Peer ReviewedPostprint (author's final draft

Noninvasive Cardiorespiratory Signals Analysis for Asthma Evolution Monitoring in Preschool Children

OBJECTIVE: Despite its increasing prevalence, diagnosis of asthma in children remains problematic due to their difficulties in producing repeatable spirometric maneuvers. Moreover, low adherence to inhaled corticosteroids (ICS) treatment could result in permanent airway remodeling. The growing interest in a noninvasive and objective way for monitoring asthma, together with the apparent role of autonomic nervous system (ANS) in its pathogenesis, have attracted interest towards heart rate variability (HRV) and cardiorespiratory coupling (CRC) analyses. METHODS: HRV and CRC were analyzed in 70 children who were prescribed ICS treatment due to recurrent obstructive bronchitis. They underwent three different electrocardiogram and respiratory signals recordings, during and after treatment period. After treatment completion, they were followed up during 6 months and classified attending to their current asthma status. RESULTS: Vagal activity, as measured from HRV, and CRC, were reduced after treatment in those children at lower risk of asthma, whereas it kept unchanged in those with a worse prognosis. CONCLUSION: Results suggest that HRV analysis could be useful for the continuous monitoring of ANS anomalies present in asthma, thus contributing to evaluate the evolution of the disease, which is especially challenging in young children. SIGNIFICANCE: Noninvasive ANS assessment using HRV analysis could be useful in the continuous monitoring of asthma in children

BL Lacertae identifications in a ROSAT-selected sample of Fermi unidentified objects

The optical spectroscopic followup of 27 sources belonging to a sample of 30 high-energy objects selected by positionally cross correlating the first Fermi/LAT Catalog and the ROSAT All-Sky Survey Bright Source Catalog is presented here. It has been found or confirmed that 25 of them are BL Lacertae objects (BL Lacs), while the remaining two are Galactic cataclysmic variables (CVs). This strongly suggests that the sources in the first group are responsible for the GeV emission detected with Fermi, while the two CVs most likely represent spurious associations. We thus find an 80% a posteriori probability that the sources selected by matching GeV and X-ray catalogs belong to the BL Lac class. We also show suggestions that the BL Lacs selected with this approach are probably high-synchrotron-peaked sources and in turn good candidates for the detection of ultra-high-energy (TeV) photons from them.Comment: 16 pages, 9 figures, 4 tables, one appendix, accepted for publication on A&A, main journal. Tables 1-3 and Figures 2-6 will only be published in the electronic edition of the journa

Unveiling the nature of INTEGRAL objects through optical spectroscopy. VII. Identification of 20 Galactic and extragalactic hard X-ray sources

Within the framework of our program of assessment of the nature of unidentified or poorly known INTEGRAL sources, we present here spectroscopy of optical objects, selected through positional cross-correlation with soft X-ray detections (afforded with satellites such as Swift, ROSAT, Chandra and/or XMM-Newton) as putative counterparts of hard X-ray sources detected with the IBIS instrument onboard INTEGRAL. Using 6 telescopes of various sizes and archival data from two on-line spectroscopic surveys we are able to identify, either for the first time or independent of other groups, the nature of 20 INTEGRAL hard X-ray sources. Our results indicate that: 11 of these objects are active galactic nuclei (AGNs) at redshifts between 0.014 and 0.978, 7 of which display broad emission lines, 2 show narrow emission lines only, and 2 have unremarkable or no emission lines (thus are likely Compton thick AGNs); 5 are cataclysmic variables (CVs), 4 of which are (possibly magnetic) dwarf novae and one is a symbiotic star; and 4 are Galactic X-ray binaries (3 with high-mass companions and one with a low-mass secondary). It is thus again found that the majority of these sources are AGNs or magnetic CVs, confirming our previous findings. When possible, the main physical parameters for these hard X-ray sources are also computed using the multiwavelength information available in the literature. These identifications support the importance of INTEGRAL in the study of the hard X-ray spectrum of all classes of X-ray emitting objects, and the effectiveness of a strategy of multi-catalogue cross-correlation plus optical spectroscopy to securely pinpoint the actual nature of unidentified hard X-ray sources.Comment: 16 pages, 8 figures, 5 tables. Accepted for publication on Astronomy & Astrophysics, main journal. Slight changes made to match the proof-corrected version; references adde

Baroreflex Sensitivity Measured by Pulse Photoplethysmography

Novel methods for assessing baroreflex sensitivity (BRS) using only pulse photoplethysmography (PPG) signals are presented. Proposed methods were evaluated with a data set containing electrocardiogram (ECG), blood pressure (BP), and PPG signals from 17 healthy subjects during a tilt table test. The methods are based on a surrogate of α index, which is defined as the power ratio of RR interval variability (RRV) and that of systolic arterial pressure series variability (SAPV). The proposed α index surrogates use pulse-to-pulse interval series variability (PPV) as a surrogate of RRV, and different morphological features of the PPG pulse which have been hypothesized to be related to BP, as series surrogates of SAPV. A time-frequency technique was used to assess BRS, taking into account the non-stationarity of the protocol. This technique identifies two time-varying frequency bands where RRV and SAPV (or their surrogates) are expected to be coupled: the low frequency (LF, inside 0.04–0.15 Hz range), and the high frequency (HF, inside 0.15–0.4 Hz range) bands. Furthermore, time-frequency coherence is used to identify the time intervals when the RRV and SAPV (or their surrogates) are coupled. Conventional α index based on RRV and SAPV was used as Gold Standard. Spearman correlation coefficients between conventional α index and its PPG-based surrogates were computed and the paired Wilcoxon statistical test was applied in order to assess whether the indices can find significant differences (p < 0.05) between different stages of the protocol. The highest correlations with the conventional α index were obtained by the α-index-surrogate based on PPV and pulse up-slope (PUS), with 0.74 for LF band, and 0.81 for HF band. Furthermore, this index found significant differences between rest stages and tilt stage in both LF and HF bands according to the paired Wilcoxon test, as the conventional α index also did. These results suggest that BRS changes induced by the tilt test can be assessed with high correlation by only a PPG signal using PPV as RRV surrogate, and PPG morphological features as SAPV surrogates, being PUS the most convenient SAPV surrogate among the studied ones