Model-Based Evaluation of Methods for Respiratory Sinus Arrhythmia Estimation

Morales, John; Moeyersons, Jonathan; Armanac, Pablo; Orini, Michele; Faes, Luca; Overeem, Sebastiaan; Gilst, Merel M van; Dijk, Hans van; Huffel, Sabine Van; Bailón, Raquel; Varon, Carolina

doi:10.1109/tbme.2020.3028204

Cited by 14 publications

(13 citation statements)

References 43 publications

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“…However, the indices with best performance were the ones also computed here, namely , and . Interestingly, the study in 34 analyses the best methods for CPC estimation in a simulation study, and concludes that the same three parameters used in this work are the best estimators for CPC assessment.…”

Section: Discussionmentioning

confidence: 77%

“…Different methods exist to quantify the strength of the RSA for CPC assessment, among which the following stand out 34 : analysis of the HRV in the High Frequency (HF) band 35 , Time Frequency Coherence (TFC) 36 , Information Dynamics (ID) 37 , Orthogonal Subspace Projections (OSP) 38 , Bivariate Phase Rectified Signal Averaging 39 , Pole Specific Spectral Causality 40 , and Cardiopulmonary Phase Synchronization 41 . The performance of these estimators of CPC is studied in 34 , and the indices derived from TFC, ID and OSP outperformed the others, which are the ones also used in this work.…”

Section: Introductionmentioning

confidence: 99%

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Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation

Armañac-Julián

Hernando

Lázaro

et al. 2021

Sci Rep

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The ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients’ readiness, there is still around 15–20% of predictive failure rate. This work is a proof of concept focused on adding new value to the prediction of the weaning outcome. Heart Rate Variability (HRV) and Cardiopulmonary Coupling (CPC) methods are evaluated as new complementary estimates to assess weaning readiness. The CPC is related to how the mechanisms regulating respiration and cardiac pumping are working simultaneously, and it is defined from HRV in combination with respiratory information. Three different techniques are used to estimate the CPC, including Time-Frequency Coherence, Dynamic Mutual Information and Orthogonal Subspace Projections. The cohort study includes 22 patients in pressure support ventilation, ready to undergo the SBT, analysed in the 24 h previous to the SBT. Of these, 13 had a successful weaning and 9 failed the SBT or needed reintubation –being both considered as failed weaning. Results illustrate that traditional variables such as heart rate, respiratory frequency, and the parameters derived from HRV do not differ in patients with successful or failed weaning. Results revealed that HRV parameters can vary considerably depending on the time at which they are measured. This fact could be attributed to circadian rhythms, having a strong influence on HRV values. On the contrary, significant statistical differences are found in the proposed CPC parameters when comparing the values of the two groups, and throughout the whole recordings. In addition, differences are greater at night, probably because patients with failed weaning might be experiencing more respiratory episodes, e.g. apneas during the night, which is directly related to a reduced respiratory sinus arrhythmia. Therefore, results suggest that the traditional measures could be used in combination with the proposed CPC biomarkers to improve weaning readiness.

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Section: Discussionmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation

Armañac-Julián

Hernando

Lázaro

et al. 2021

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the indices with best performance were the ones presented here, namely P m r , C E r↔m and C T HF . Interestingly,the study in 50 analyses the best methods for RSA estimation in a simulation study, and concludes that the same three parameters are the best estimators of the CPC.…”

Section: Discussionmentioning

confidence: 99%

“…Different approaches exist to quantify the strength of the RSA for CPC assessment, among which the following stand out: analysis of the HRV in the High Frequency (HF) band 43 , Time Frequency Coherence Analysis (TFC) 44 , Information Dynamics (ID) 45 , Orthogonal Subspace Projections (OSP) 46 , Bivariate Phase Rectified Signal Averaging 47 , Pole Specific Spectral Causality 48 , and Cardiopulmonary Phase Synchronization 49 . The performance of these estimators of CPC is studied in 50 , and the indices derived from TFC, ID and OSP are the ones used in this work.…”

Section: Introductionmentioning

confidence: 99%

Weaning from Mechanical Ventilation: On the Improvement of the Prediction of Patients' Readiness with Cardiopulmonary Coupling Indices

Armañac-Julián

Hernando

Lázaro

et al. 2020

Preprint

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The ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation (MV) at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients’ readiness, there is still around 15-20% of predictive failure rate. This work explores both Heart Rate Variability (HRV) and Cardiopulmonary Coupling (CPC) estimates as complementary information for readiness prediction. The CPC is related to how the mechanisms regulating respiration and cardiac pumping are working simultaneously, and it is defined from HRV in combination with respiratory information. Three different techniques are used to measure CPC, including Orthogonal Subspace Projections, Dynamic Mutual Information and Time-Frequency Coherence. 22 patients undergoing SBT in pressure support ventilation are analysed in the 24 hours previous to the SBT. 13 had a successful weaning and 9 failed the SBT or needed reintubation –being both considered as failed weaning. Results illustrate that traditional variables such as heart rate, respiratory frequency, and the parameters derived from HRV do not differ in patients with successful or failed weaning. However, significant statistical differences are found for the novel CPC parameters, throughout the whole recordings, comparing the values of the two groups. In addition, the night prior to SBT is the moment where differences are higher, probably because patients with failed weaning might be experiencing more respiratory episodes, e.g. apneas during the night, which is directly related to a reduced RSA. Therefore, results suggest that the traditional measures could be used in combination with these novel CPC biomarkers to help clinicians better predict if patients are ready to be weaned.

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“…The reason to use two different sampling frequencies was to observe the effect that this has on the TE RESP− →HR estimation. Previous works have found that the sampling frequency might influence the estimation of cardio-respiratory interactions [40], while other studies have found an effect of filtering and downsampling electrophysiological data on the estimation of TE between different brain areas [41].…”

Section: Application On Real Datamentioning

confidence: 99%

Benchmarking Transfer Entropy Methods for the Study of Linear and Nonlinear Cardio-Respiratory Interactions

Rozo

Morales

Moeyersons

et al. 2021

Entropy

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Transfer entropy (TE) has been used to identify and quantify interactions between physiological systems. Different methods exist to estimate TE, but there is no consensus about which one performs best in specific applications. In this study, five methods (linear, k-nearest neighbors, fixed-binning with ranking, kernel density estimation and adaptive partitioning) were compared. The comparison was made on three simulation models (linear, nonlinear and linear + nonlinear dynamics). From the simulations, it was found that the best method to quantify the different interactions was adaptive partitioning. This method was then applied on data from a polysomnography study, specifically on the ECG and the respiratory signals (nasal airflow and respiratory effort around the thorax). The hypothesis that the linear and nonlinear components of cardio-respiratory interactions during light and deep sleep change with the sleep stage, was tested. Significant differences, after performing surrogate analysis, indicate an increased TE during deep sleep. However, these differences were found to be dependent on the type of respiratory signal and sampling frequency. These results highlight the importance of selecting the appropriate signals, estimation method and surrogate analysis for the study of linear and nonlinear cardio-respiratory interactions.

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Model-Based Evaluation of Methods for Respiratory Sinus Arrhythmia Estimation

Cited by 14 publications

References 43 publications

Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation

Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation

Weaning from Mechanical Ventilation: On the Improvement of the Prediction of Patients' Readiness with Cardiopulmonary Coupling Indices

Benchmarking Transfer Entropy Methods for the Study of Linear and Nonlinear Cardio-Respiratory Interactions

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