Publications (17) View all
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Article: Characterization of Dynamic Interactions Between Cardiovascular Signals by Time-Frequency Coherence.
IEEE Trans. Biomed. Engineering. 01/2012; 59:663-673. -
Article: Synthesis of HRV signals characterized by predetermined time-frequency structure by means of time-varying ARMA models
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ABSTRACT: a b s t r a c t In this paper we present two methodologies to generate heart rate variability (HRV) signals character-ized by controlled and real-like time-frequency (TF) structure to be used to assess different methods of non-stationary HRV analysis. The synthesized signals are stochastic processes whose TF structure is predetermined by choosing either the time-course of the instantaneous frequencies and powers or the shape of the TF model function. They consist of three steps: (a) choice of the desired TF structure of the signals by choosing a set of design parameters; (b) automatic identification of the parameters of the cor-responding models via simple closed-form expressions; (c) synthesis of the desired stochastic signals. Two measures to evaluate the goodness of the simulated signals are also given. Using this framework we were able to model the wide range of non-stationarities observed in heart rate modulation during exercise stress testing and experiments of music-induced emotions. We used the proposed methodology to assess the capability of the smoothed pseudo Wigner–Ville distribution (SPWVD) to quantify HRV pat-terns. We observed that the SPWVD followed the temporal evolution of the spectral components even when sudden and sharp transitions occur.Biomedical Signal Processing and Control 01/2012; 7:141-150. · 1.00 Impact Factor -
Article: Time-frequency phase differences and phase locking to characterize dynamic interactions between cardiovascular signals.
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ABSTRACT: In this paper cross time-frequency (TF) analysis is used to estimate the phase differences and the phase locking between cardiovascular signals. Phase differences give a measure of the changes in the synchronization between two oscillations, while phase locking measures the degree of similarity of these changes across subjects. The methodology is based on the smoothed pseudo Wigner-Ville distribution and includes coherence analysis. In a simulation study involving R-R variability (RRV) signals, this methodology provided accurate estimates of phase differences, with an error characterized by interquartile ranges lower than 2% and 10% for SNR of 20 dB and 0 dB, respectevely. A comparative study showed that the proposed estimator outperformed an estimator based on the integration of the difference between the instantaneous frequencies of the signal spectral component. The presented methodology was used to characterize the interactions between RRV and systolic arterial pressure variability during tilt table test. Head-up tilt caused the phase differences (time delay) to change about 0.48 rad (361 ms) in HF range [0.15, 0.5 Hz]. The phase locking, which decreased immediately after the head-up tilt, was restored in about 2 minutes.Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:4689-92. -
Article: The integral pulse frequency modulation model with time-varying threshold: application to heart rate variability analysis during exercise stress testing.
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ABSTRACT: In this paper, an approach for heart rate variability analysis during exercise stress testing is proposed based on the integral pulse frequency modulation (IPFM) model, where a time-varying threshold is included to account for the nonstationary mean heart rate. The proposed technique allows the estimation of the autonomic nervous system (ANS) modulating signal using the methods derived for the IPFM model with constant threshold plus a correction, which is shown to be needed to take into account the time-varying mean heart rate. On simulations, this technique allows the estimation of the ANS modulation on the heart from the beat occurrence time series with lower errors than the IPFM model with constant threshold (1.1% ± 1.3% versus 15.0% ± 14.9%). On an exercise stress testing database, the ANS modulation estimated by the proposed technique is closer to physiology than that obtained from the IPFM model with constant threshold, which tends to overestimate the ANS modulation during the recovery and underestimate it during the initial rest.IEEE transactions on bio-medical engineering 03/2011; 58(3):642-52. · 2.15 Impact Factor -
Article: A method for continuously assessing the autonomic response to music-induced emotions through HRV analysis.
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ABSTRACT: Interest in therapeutic applications of music has recently increased, as well as the effort to understand the relationship between music features and physiological patterns. In this study, we present a methodology for characterizing music-induced effects on the dynamics of the heart rate modulation. It consists of three steps: (i) the smoothed pseudo Wigner-Ville distribution is performed to obtain a time-frequency representation of HRV; (ii) a parametric decomposition is used to robustly estimate the time-course of spectral parameters; and (iii) statistical population analysis is used to continuously assess whether different acoustic stimuli provoke different dynamic responses. Seventy-five healthy subjects were repetitively exposed to pleasant music, sequences of Shepard tones with the same tempo as the pleasant music and unpleasant sounds overlaid with the same sequences of Shepard tones. Results show that the modification of HRV parameters are characterized by an early fast transient phase (15-20 s), followed by an almost stationary period. All kinds of stimuli provoked significant changes compared to the resting condition, while during listening to pleasant music the heart and respiratory rates were higher (for more than 80% of the duration of the stimuli, p < 10(-5)) and the power of the HF modulation was lower (for more than 70% of the duration of the stimuli, p < 0.05) than during listening to unpleasant stimuli.Medical & Biological Engineering 03/2010; 48(5):423-33. · 1.76 Impact Factor
