Staff member

Daniel Romero Pérez

Postdoctoral Researcher
Biomedical Signal Processing and Interpretation
+34 934015685
Staff member publications

Romero, D., Jané, R., (2020). Hypoxia-induced effects on ECG depolarization by time warping analysis during recurrent obstructive apnea Engineering in Medicine & Biology Society (EMBC) 42nd Annual International Conference of the IEEE , IEEE (Montreal, Canada) , 2626-2629

In this work, we evaluated a non-linear approach to estimate morphological variations in ECG depolarization, in the context of intermittent hypoxia (IH). Obstructive apnea sequences were provoked for 15 minutes in anesthetized Sprague-Dawley rats, alternating with equal periods of normal breathing, in a recurrent obstructive sleep apnea (OSA) model. Each apnea episode lasted 15 s, while the frequency used for each sequence was randomly selected. Average heartbeats obtained before the start and at the end of each episode, were delineated to extract only the QRS wave. Then, the segmented QRS waves were non-linearly aligned using the dynamic time warping (DWT) algorithm. Morphological QRS changes in both the amplitude and temporal domains were estimated from this alignment procedure. The hypoxic and basal segments were analyzed using ECG (lead I) recordings acquired during the experiment. To assess the effects of IH over time, the changes relative to the basal QRS wave were determined, in the intervals prior to each successive events until the end of the experiment. The results showed a progressive increase in the amplitude and time-domain morphological markers of the QRS wave along the experiment, which were strongly correlated with the changes in traditional QRS markers (r ≈ 0.9). Significant changes were found between pre-apnea and hypoxic measures only for the time-domain analysis (p<0.001), probably due to the short duration of the simulated apnea episodes.Clinical relevance Increased variability in ECG depolarization morphology during recurrent hypoxic episodes would be closely related to the expression of cardiovascular dysfunction in OSA patients.

Keywords: Electrocardiography, Rats, Heart rate variability, Sleep apnea, Protocols, Heuristic algorithms

Romero, D., Lázaro, J., Jané, R., Laguna, P., Bailón, R., (2020). A quaternion-based approach to estimate respiratory rate from the vectorcardiogram Computers in Cardiology (CinC) 2020 Computing in Cardiology , IEEE (Rimini, Italy) 47, 1-4

A novel ECG-derived respiration (EDR) approach is presented to efficiently estimate the respiratory rate. It combines spatial rotations and magnitude variations of the heart's electrical vector due to respiration. Orthogonal leads X, Y and Z from 10 volunteers were analyzed during a tilt table test. The largest vector magnitude (VM) within each QRS loop was assessed, and its 3D coordinates were converted into unit quaternion qb. Angular distances between these quaternions and the axes of the reference coordinate system, θ x , θ y and θ z , were then computed as EDR signals to track their relative variations caused by respiration. The respiratory rate was estimated on the spectrum of individual EDR signals obtained from the angular distances and VM time-series, but also on EDR signals obtained by principal component analysis (PCA). Relative errors (eR) to the reference respiratory signal exhibited relatively low values. The combination of EDR signals' spectrum {θ X ,θ Y, θ Z , VM} (eR=0.63±4.15%) and individual signals derived from θ X (e R =0.46±8.22%) and PCA (eR=0.36±6.58%) achieved the overall best results. The proposed method represents a computationally efficient alternative to other EDR approaches, but its robustness should be further investigated. The method could be enhanced if combined with other features tracking morphological changes induced by respiration.

Keywords: Heart, Three-dimensional displays, Quaternions, Robustness, Computational efficiency, Cardiology, Principal component analysis

Blanco-Almazan, D., Romero, D., Groenendaal, W., Lijnen, L., Smeets, C., Ruttens, D., Catthoor, F., Jané, R., (2020). Relationship between heart rate recovery and disease severity in chronic obstructive pulmonary disease patients Computers in Cardiology (CinC) 2020 Computing in Cardiology , IEEE (Rimini, Italy) 47, 1-4

Chronic obstructive pulmonary disease (COPD) patients exhibit impaired autonomic control which can be assessed by heart rate variability analysis. The study aims to evaluate the cardiac autonomic responses of COPD patients after completing a conventional six-minute walk test (6MWT). Fifty COPD patients were included in the study, for which an ECG signal (lead II) was acquired by a wearable device, before, during, and after the test. We used the heart rate (HR) time-series to assess the heart rate dynamic during recovery. The heart rate recovery (HRR) marker was evaluated every 5 s after the 6MWT and showed different dynamic trends among severity groups. We compared the HRR among patient groups classified according to the GOLD standard. Significantly larger normalized HRR values (nHRR) were found in mild COPD patients (n=23, GOLD={1,2}; nHRR 1 =14.B±7.5 %, nHRR 2 =18.6±8.1 %) compared to those with more disease severity (n=23, GOLD={3,4}; nHRR 1 =9.3±5.8 %, p=0.002; and nHRR 2 = 13.7±6.7%, p=0.041). The largest differences were observed around the first 30 s of the recovery phase (nHRR=10.8±6.6 % vs. nHRR=5.6±4 % p=0.001). Our results showed a slower recovery for the severest patients, suggesting that cardiac parameters like the ones we propose here, may provide valuable information for a better characterization of COPD severity.

Keywords: Pulmonary diseases, Wearable computers, Electrocardiography, Market research, Cardiology, Heart rate variability

Calvo, M., Le Rolle, V., Romero, D., Béhar, N., Gomis, P., Mabo, P., Hernández, A. I., (2019). Recursive model identification for the analysis of the autonomic response to exercise testing in Brugada syndrome Artificial Intelligence in Medicine 97, 98-104

This paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a recursive evolutionary algorithm. After parameter identification, a close match between experimental and simulated signals (mean error = 0.81%) was observed. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge, enabling to observe the expected autonomic changes induced by exercise testing. In particular, symptomatic patients presented a significantly higher parasympathetic activity during exercise, and an autonomic imbalance was observed in these patients at peak effort and during post-exercise recovery. A higher vagal modulation during exercise, as well as an increasing parasympathetic activity at peak effort and a decreasing vagal contribution during post-exercise recovery could be related with symptoms and, thus, with a worse prognosis in BS. This work proposes the first evaluation of the sympathetic and parasympathetic responses to exercise testing in patients suffering from BS, through the recursive identification of computational models; highlighting important trends of clinical relevance that provide new insights into the underlying autonomic mechanisms regulating the cardiovascular system in BS. The joint analysis of the extracted autonomic parameters and classic electrophysiological markers could improve BS risk stratification.

Keywords: Autonomic nervous system, Brugada syndrome, Computational model, Recursive identification

Romero, D., Jané, R., (2019). Non-linear HRV analysis to quantify the effects of intermittent hypoxia using an OSA rat model Engineering in Medicine and Biology Society (EMBC) 41st Annual International Conference of the IEEE , IEEE (Berlín, Germany) , 4994-4997

In this paper, a non-linear HRV analysis was performed to assess fragmentation signatures observed in heartbeat time series after intermittent hypoxia (IH). Three markers quantifying short-term fragmentation levels, PIP, IALS and PSS, were evaluated on R-R interval series obtained in a rat model of recurrent apnea. Through airway obstructions, apnea episodes were periodically simulated in six anesthetized Sprague-Dawley rats. The number of apnea events per hour (AHI index) was varied during the first half of the experiment while apnea episodes lasted 15 s. For the second part, apnea episodes lasted 5, 10 or 15 s, but the AHI index was fixed. Recurrent apnea was repeated for 15-min time intervals in all cases, alternating with basal periods of the same duration. The fragmentation markers were evaluated in segments of 5 minutes, selected at the beginning and end of the experiment. The impact of the heart and breathing rates (HR and BR, respectively) on the parameter estimates was also investigated. The results obtained show a significant increase (from 5 to 10%, p <; 0.05) in fragmentation measures of heartbeat time series after IH, indicating a clear deterioration of the initial conditions. Moreover, there was a strong linear relationship (r > 0.9) between these markers and BR, as well as with the ratio given by HR/BR. Although fragmentation may be impacted by IH, we found that it is highly dependent on HR and BR values and thus, they should be considered during its calculation or used to normalize the fragmentation estimates.

Keywords: Rats, Time series analysis, Radio access technologies, Protocols, Heart beat