Revisiting the potential of time-domain indexes in short-term HRV analysis

Balocchi, R.; Cantini, Federico; Varanini, M.; Raimondi, Gianfranco; Legramante, Jacopo M.; Macerata, A.

doi:10.1515/bmt.2006.034

Cited by 45 publications

(38 citation statements)

References 13 publications

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“…The SDNN/RMSSD ratio is, therefore, thought to represent the balance between long-term and short-term variabilities and thus represents the SNS-PSNS balance. 21 The two described measures can be related to one of the most commonly used method for analyzing HRV and PRV, i.e., Poincaré plots. Poincaré plots are graphical illustrations of two consecutive RR intervals and are valuable due to their ability of displaying the nonlinear aspects of HRV and PRV sequences.…”

Section: Introductionmentioning

confidence: 99%

Short-term pulse rate variability is better characterized by functional near-infrared spectroscopy than by photoplethysmography

2016

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Pulse rate variability (PRV) can be extracted from functional near-infrared spectroscopy (fNIRS) (PRV(NIRS)) and photoplethysmography (PPG) (PRV(PPG)) signals. The present study compared the accuracy of simultaneously acquired PRV(NIRS) and PRV(PPG), and evaluated their different characterizations of the sympathetic (SNS) and parasympathetic (PSNS) autonomous nervous system activity. Ten healthy subjects were recorded during resting-state (RS) and respiratory challenges in two temperature conditions, i.e., room temperature (23°C) and cold temperature (4°C). PRV(NIRS) was recorded based on fNIRS measurement on the head, whereas PRV(PPG) was determined based on PPG measured at the finger. Accuracy between PRV(NIRS) and PRV(PPG), as assessed by cross-covariance and cross-sample entropy, demonstrated a high degree of correlation (r > 0.9), which was significantly reduced by respiration and cold temperature. Characterization of SNS and PSNS using frequency-domain, time-domain, and nonlinear methods showed that PRV(NIRS) provided significantly better information on increasing PSNS activity in response to respiration and cold temperature than PRV(PPG). The findings show that PRV(NIRS) may outperform PRV(PPG) under conditions in which respiration and temperature changes are present, and may, therefore, be advantageous in research and clinical settings, especially if characterization of the autonomous nervous system is desired. Abstract. Pulse rate variability (PRV) can be extracted from functional near-infrared spectroscopy (fNIRS) (PRV NIRS ) and photoplethysmography (PPG) (PRV PPG ) signals. The present study compared the accuracy of simultaneously acquired PRV NIRS and PRV PPG , and evaluated their different characterizations of the sympathetic (SNS) and parasympathetic (PSNS) autonomous nervous system activity. Ten healthy subjects were recorded during resting-state (RS) and respiratory challenges in two temperature conditions, i.e., room temperature (23°C) and cold temperature (4°C). PRV NIRS was recorded based on fNIRS measurement on the head, whereas PRV PPG was determined based on PPG measured at the finger. Accuracy between PRV NIRS and PRV PPG , as assessed by cross-covariance and cross-sample entropy, demonstrated a high degree of correlation (r > 0.9), which was significantly reduced by respiration and cold temperature. Characterization of SNS and PSNS using frequency-domain, time-domain, and nonlinear methods showed that PRV NIRS provided significantly better information on increasing PSNS activity in response to respiration and cold temperature than PRV PPG . The findings show that PRV NIRS may outperform PRV PPG under conditions in which respiration and temperature changes are present, and may, therefore, be advantageous in research and clinical settings, especially if characterization of the autonomous nervous system is desired.

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Section: Introductionmentioning

confidence: 99%

Short-term pulse rate variability is better characterized by functional near-infrared spectroscopy than by photoplethysmography

2016

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“…According to Sollers, et al [27] SRR is an efficient biometric index in comparisons with LHR for different healthcare applications. The HRV measurement for time-domain can decrease complexity for computation and also provide resource efficient biometric index than the frequency-domain based index since heart beats of ECG information are recorded in time series [28,29]. In this study, it is verified from a detailed experiment on 44 subjects that SRR can be utilized as a convenient, resource-efficient and accurate biometric index for remote monitoring of OSA affected patients.…”

Section: Efficient Biometric Index For Osa Monitoringmentioning

confidence: 71%

Analysis of Efficient Biometric Index using Heart Rate Variability for Remote Monitoring of Obstructive Sleep Apnea

Pirbhulal¹,

Zhang²,

Wu³

et al. 2017

Neuropsychiatry

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Objective:Obstructive sleep apnea (OSA) associated health problems are undiagnosed due to the expensive and realistic limitations of overnight PSG examination. In this research, an accurate and resource-efficient biometric index is proposed for remote monitoring of the OSA patients having universal property at all body postures. Methods:In this study, the analysis of 44 subjects determines that the Heart Rate Variability (HRV) parameters including time and frequency domains such as ratio of Standard Deviation of NN interval (SDNN) and Root-Mean-Squared of the Successive Differences (RMSSD), termed as SRR; and LHR (ratio between normalized Low to High-Frequency power) can be taken into consideration to develop reasonable accurate and cost-efficient indexes for OSA levels measurement.

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“…Note: The two quantities sd1 and sd2 are different expressions of the variability of the RR series: sd2 contains the overall (sympathetic and parasympathetic) variability, while sd1 retains only the parasympathetic one. The sd2/sd1 ratio (CSI, cardiac sympathetic index) is a time-domain measure of the sympathetic-parasympathetic balance and is analogous, but not identical, to the frequency-domain index LF/HF (Balocchi, Cantini, Varanini, Raimondi, Legramante and Macerata, 2006). Indeed, while HF and sd1 are measures of the parasympathetic variability, LF is a measure of the sympathetic variability not including (at variance with sd2) the frequency components of heart rate variability below 0.04 Hz (Very Low Frequency, VLF).…”

Section: Discussionmentioning

confidence: 99%

Hypnotizability and chronic pain: an ambiguous connection

Carli

Huber

Santarcangelo

2008

Contemporary Hypnosis

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We discuss the role of hypnotizability in the development and treatment of chronic pain, and in the prognosis of its possible cardiovascular consequences. Data indicate that high hypnotic susceptibility is not necessary for the relief of chronic pain obtained through hypnotic treatment. Moreover, and at variance with an earlier hypothesis, being highly susceptible to hypnosis does not represent a higher risk for developing chronic pain; in addition, high hypnotizability may be a favourable protective factor against the possible cardiovascular consequences of chronic pain. However, we cannot exclude that psychological factors such as mindfulness, well-being and pain-catastrophizing differ in 'Highs' versus 'Lows', and these may represent the real agents of the differences between the two groups in pain experience, the development of chronic pain, and possible vascular consequences of chronic pain.

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Revisiting the potential of time-domain indexes in short-term HRV analysis

Cited by 45 publications

References 13 publications

Short-term pulse rate variability is better characterized by functional near-infrared spectroscopy than by photoplethysmography

Short-term pulse rate variability is better characterized by functional near-infrared spectroscopy than by photoplethysmography

Analysis of Efficient Biometric Index using Heart Rate Variability for Remote Monitoring of Obstructive Sleep Apnea

Hypnotizability and chronic pain: an ambiguous connection

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