La Recerca en bioenginyeria cardíaca i pulmonar a l'Institut de Cibernètica

En aquesta ponència presentem els treballs de recerca duts a terme els darrers anys a l'Institut de Cibernètica en el camp de la bioenginyeria. Cal destacar la simulació en computador híbrid del sistema càrdio-vascular, l'anàlisi i caracterització de pròtesis valvulars cardíaques i el processament automàtic de l'electrocardiograma del feix de His, dins l'àrea de la bioenginyeria cardíaca. La recerca en bioenginyeria pulmonar ha estat centrada en el disseny d'equips que col•laboren en 1'exploració funcional pulmonar.This paper presents the bioengineering research carried out at the Institut de Cibernètica the last years. We can remark the cardiovascular system simulation by hybrid computer, the prosthetic cardiac valves characterization, the His bundle electrogram on-line processing and different devices developed to explore the pulmonary function

Validity of the Polar V800 monitor for measuring heart rate variability in mountain running route conditions

PURPOSE: This study was conducted to test, in mountain running route conditions, the accuracy of the Polar V800 monitor as a suitable device for monitoring the heart rate variability (HRV) of runners. METHOD: Eighteen healthy subjects ran a route that included a range of running slopes such as those encountered in trail and ultra-trail races. The comparative study of a V800 and a Holter SEER 12 ECG Recorder included the analysis of RR time series and short-term HRV analysis. A correction algorithm was designed to obtain the corrected Polar RR intervals. Six 5-min segments related to different running slopes were considered for each subject. RESULTS: The correlation between corrected V800 RR intervals and Holter RR intervals was very high (r = 0.99, p  0.05) and were well correlated (r ≥ 0.96, p < 0.001). CONCLUSION: Narrow limits of agreement, high correlations and small effect size suggest that the Polar V800 is a valid tool for the analysis of heart rate variability in athletes while running high endurance events such as marathon, trail, and ultra-trail races. KEYWORDS: HRV; Open field running conditions; Polar V800 heart rate monitor; Validatio

Detrended fluctuation analysis of heart rate by means of symbolic series

Detrended fluctuation analysis (DFA) has been shown to be a useful tool for diagnosis of patients with cardiac diseases. The scaling exponents obtained with DFA are an indicator of power-law correlations in signal fluctuation, independently of signal amplitude and external trends. In this work, an approach based on DFA was proposed for analyzing heart rate variability (HRV) by means of RR series. The proposal consisted on transforming consecutive RR increments to symbols, according to an adapted symbolic-quantization. Three scaling exponents were calculated, αHF, αLF and αVLF, which correspond to the well known VLF, LF and HF frequency bands in the power spectral of the HRV. This DFA approach better characterized high and low risk of cardiac mortality in ischemic cardiomyiopathy patients than DFA applied to RR time series or RR increment series.Peer ReviewedPostprint (published version

Validity of the Polar V800 monitor for measuring heart rate variability in mountain running route conditions

PURPOSE: This study was conducted to test, in mountain running route conditions, the accuracy of the Polar V800 monitor as a suitable device for monitoring the heart rate variability (HRV) of runners. METHOD: Eighteen healthy subjects ran a route that included a range of running slopes such as those encountered in trail and ultra-trail races. The comparative study of a V800 and a Holter SEER 12 ECG Recorder included the analysis of RR time series and short-term HRV analysis. A correction algorithm was designed to obtain the corrected Polar RR intervals. Six 5-min segments related to different running slopes were considered for each subject. RESULTS: The correlation between corrected V800 RR intervals and Holter RR intervals was very high (r = 0.99, p  0.05) and were well correlated (r ≥ 0.96, p < 0.001). CONCLUSION: Narrow limits of agreement, high correlations and small effect size suggest that the Polar V800 is a valid tool for the analysis of heart rate variability in athletes while running high endurance events such as marathon, trail, and ultra-trail races. KEYWORDS: HRV; Open field running conditions; Polar V800 heart rate monitor; Validatio

Segmented Symbolic Dynamics for Risk Stratification in Patients with Ischemic Heart Failure, Cardiovascular Engineering and Technology

Chronic heart failure (CHF) is recognized as major and escalating public health problem. Approximately 69% of CHF patients suffer from cardiac death within 5 years after the initial diagnosis. Until now, no generally accepted ECG risk predictors in CHF patients are available. The objective of this study was to investigate the suitability of the new developed non-linear method segmented symbolic dynamics (SSD) for risk stratification in patients with ischemic cardiomyopathy (ICM) in comparison to other indices from time and frequency domain, non-linear dynamics, and clinical markers. Twenty-four hour Holter ECGs were recorded from 256 ICM patients. Heart rate variability (HRV) was analyzed from the filtered beat-to-beat interval time series. For calculating SSD, NN interval time series were segmented in 1 min overlapping windows with a window length of 30 min. For each window a symbol- and word-transformation was performed and probabilities of word type occurrences were calculated. Several indices from frequency domain and non-linear dynamics revealed high univariate significant differences (p<0.01) discriminating low (n = 221) and high risk ICM patients (n = 35). For multivariate risk stratification in ICM patients the two optimal mixed parameter sets consisting of either two clinical and three non-clinical indices (two from SSD) or three clinical and two non-clinical indices (one from SSD) achieved 74 and 75% sensitivity and 79 and 76% specificity, respectively. These results suggest that the new SSD enhances considerably risk stratification in ICM patients. The multivariate analysis including SSD leads to an optimum accuracy of 81%.Peer Reviewe

Segmented Symbolic Dynamics for Risk Stratification in Patients with Ischemic Heart Failure, Cardiovascular Engineering and Technology

Chronic heart failure (CHF) is recognized as major and escalating public health problem. Approximately 69% of CHF patients suffer from cardiac death within 5 years after the initial diagnosis. Until now, no generally accepted ECG risk predictors in CHF patients are available. The objective of this study was to investigate the suitability of the new developed non-linear method segmented symbolic dynamics (SSD) for risk stratification in patients with ischemic cardiomyopathy (ICM) in comparison to other indices from time and frequency domain, non-linear dynamics, and clinical markers. Twenty-four hour Holter ECGs were recorded from 256 ICM patients. Heart rate variability (HRV) was analyzed from the filtered beat-to-beat interval time series. For calculating SSD, NN interval time series were segmented in 1 min overlapping windows with a window length of 30 min. For each window a symbol- and word-transformation was performed and probabilities of word type occurrences were calculated. Several indices from frequency domain and non-linear dynamics revealed high univariate significant differences (p<0.01) discriminating low (n = 221) and high risk ICM patients (n = 35). For multivariate risk stratification in ICM patients the two optimal mixed parameter sets consisting of either two clinical and three non-clinical indices (two from SSD) or three clinical and two non-clinical indices (one from SSD) achieved 74 and 75% sensitivity and 79 and 76% specificity, respectively. These results suggest that the new SSD enhances considerably risk stratification in ICM patients. The multivariate analysis including SSD leads to an optimum accuracy of 81%.Peer ReviewedPostprint (published version

Detrended fluctuation analysis of heart rate by means of symbolic series

Detrended fluctuation analysis (DFA) has been shown to be a useful tool for diagnosis of patients with cardiac diseases. The scaling exponents obtained with DFA are an indicator of power-law correlations in signal fluctuation, independently of signal amplitude and external trends. In this work, an approach based on DFA was proposed for analyzing heart rate variability (HRV) by means of RR series. The proposal consisted on transforming consecutive RR increments to symbols, according to an adapted symbolic-quantization. Three scaling exponents were calculated, αHF, αLF and αVLF, which correspond to the well known VLF, LF and HF frequency bands in the power spectral of the HRV. This DFA approach better characterized high and low risk of cardiac mortality in ischemic cardiomyiopathy patients than DFA applied to RR time series or RR increment series.Peer Reviewe

Heart rate variability characterized by refined multiscale entropy applied to cardiac death in ischemic cardiomyopathy patients

In this work, Refined Multiscale Entropy (RMSE) was applied to characterize risk of cardiac death in ischemic cardiomyopathy patients, analyzing heart rate variability (HRV) by means of RR series during daytime and nighttime. RMSE approach measures an entropy rate in different time scales of a series, giving a multiscale characterization of complexity of that series. RMSE showed statistically significant differences (p<0.05) during daytime and nighttime only in middle time scales (t=4-15 and t=3-16, respectively). For these scales, RMSE was higher in low risk (SV) than in high risk (CM) group of cardiac death, indicating a reduction of the entropy-based complexity in CM when it was compared with SV. No statistical differences between risk groups were presented at time scale t=1 (unfiltered original RR series). It can be concluded that the dynamics in middle time scales should be considered to better describe the HRV of patients with cardiac death.Peer ReviewedPostprint (published version

Heart rate variability characterized by refined multiscale entropy applied to cardiac death in ischemic cardiomyopathy patients

In this work, Refined Multiscale Entropy (RMSE) was applied to characterize risk of cardiac death in ischemic cardiomyopathy patients, analyzing heart rate variability (HRV) by means of RR series during daytime and nighttime. RMSE approach measures an entropy rate in different time scales of a series, giving a multiscale characterization of complexity of that series. RMSE showed statistically significant differences (p<0.05) during daytime and nighttime only in middle time scales (t=4-15 and t=3-16, respectively). For these scales, RMSE was higher in low risk (SV) than in high risk (CM) group of cardiac death, indicating a reduction of the entropy-based complexity in CM when it was compared with SV. No statistical differences between risk groups were presented at time scale t=1 (unfiltered original RR series). It can be concluded that the dynamics in middle time scales should be considered to better describe the HRV of patients with cardiac death.Peer Reviewe