Sasan Yazdani

Extraction of QRS fiducial points from the ECG using adaptive mathematical morphology

QRS complex detection in the electrocardiogram (ECG) has been extensively investigated over the last two decades. Still, some issues remain pending due to the diversity of QRS complex shapes and various perturbations, notably baseline drift. This is especially true for ECG signals acquired using wearable devices. Our study aims at extracting QRS complexes and their fiducial points using Mathematical Morphology (MM) with an adaptive structuring element, on a beat-to-beat basis. The structuring element is updated based on the characteristics of the previously detected QRS complexes for a more robust and precise detection. The MIT-BIH arrhythmia and Physionet QT databases were respectively used for assessing the detection performance of R-waves and other fiducial points. Furthermore, the proposed method was evaluated on a wearable-device dataset of ECGs during vigorous exercises. Results show comparable or better performance than the state-of-the-art with a 99.87 % sensitivity and 0.22 % detection error rate for the MIT-BIH arrhythmia database. Efficient extraction of QRS fiducial points was achieved against the Physionet QT database. On the wearable-device dataset, an improvement of more than 10 % in QRS complex detection rate compared to classic approaches was obtained. Our study aims at extracting QRS complexes and their fiducial points using a mathematical morphology approach with an adaptive structuring element, on a beat-to-beat basis. The structuring element is updated based on the characteristics of the previously detected QRS complexes for a more precise detection.The adaptive structuring element uses the shape of the QRS complex waveform not only to extract the R-peaks, but also to estimate the location of other fiducial points in the QRS complex, i.e. QRS-onset, QRS-offset, Q-point, and S-point.A comprehensive study was performed and reported on parameter optimization.The proposed method was evaluated on wearable recording technologies with a clear improvement in performance over classical approaches.The proposed method is robust against perturbations such as baseline drift. It uses limited number of parameters while offering low computational cost which makes it a suitable choice for real-time/online scenarios such as body area networks.

A multimodal approach to reduce false arrhythmia alarms in the intensive care unit

As part of the 2015 PhysioNet/CinC Challenge, this work aims at lowering the number of false alarms, which are a persistent concern in the intensive care unit. The multimodal database consists of 1250 life-threatening alarm recordings, each categorized as a bradycardia, tachycardia, asystole, ventricular tachycardia or ventricular flutter/fibrillation arrhythmia. Based on the quality of available signals, heart rate was either estimated from pulsatile waveforms (photoplethysmogram and/or arterial blood pressure) using an adaptive frequency tracking algorithm or computed from ECGs using an adaptive mathematical morphology approach. Furthermore, we introduced a supplementary measure based on the spectral purity of the ECGs to determine if a ventricular tachycardia or flutter/fibrillation arrhythmia has taken place. Finally, alarm veracity was determined based on a set of decision rules on heart rate and spectral purity values. Our method achieved overall scores of 76.11 and 85.04 on the real-time and retrospective subsets, respectively.

False arrhythmia alarms reduction in the intensive care unit: a multimodal approach.

The purpose of this study was to develop algorithms to lower the incidence of false arrhythmia alarms in the ICU using information from independent sources, namely electrocardiogram (ECG), arterial blood pressure (ABP) and photoplethysmogram (PPG). Our approach relies on robust adaptive signal processing techniques in order to extract accurate heart rate (HR) values from the different waveforms. Based on the quality of available signals, heart rate was either estimated from pulsatile waveforms using an adaptive frequency tracking algorithm or computed from ECGs using an adaptive mathematical morphology approach. Furthermore, we developed a supplementary measure based on the spectral purity of the ECGs to determine whether a ventricular tachycardia or flutter/fibrillation arrhythmia has taken place. Finally, alarm veracity was determined based on a set of decision rules on HR and spectral purity values. The proposed method was evaluated on the PhysioNet/CinC Challenge 2015 database, which is composed of 1250 life-threatening alarm recordings, each categorized into either bradycardia, tachycardia, asystole, ventricular tachycardia or ventricular flutter/fibrillation arrhythmia. This resulted in overall true positive rates of 95%/99% and overall true negative rates of 76%/80% on the real-time and retrospective subsets of the test dataset, respectively.

Minimal Window Duration for Accurate HRV Recording in Athletes

Heart rate variability (HRV) is non-invasive and commonly used for monitoring responses to training loads, fitness, or overreaching in athletes. Yet, the recording duration for a series of RR-intervals varies from 1 to 15 min in the literature. The aim of the present work was to assess the minimum record duration to obtain reliable HRV results. RR-intervals from 159 orthostatic tests (7 min supine, SU, followed by 6 min standing, ST) were analyzed. Reference windows were 4 min in SU (min 3–7) and 4 min in ST (min 9–13). Those windows were subsequently divided and the analyses were repeated on eight different fractioned windows: the first min (0–1), the second min (1–2), the third min (2–3), the fourth min (3–4), the first 2 min (0–2), the last 2 min (2–4), the first 3 min (0–3), and the last 3 min (1–4). Correlation and Bland & Altman statistical analyses were systematically performed. The analysis window could be shortened to 0–2 instead of 0–4 for RMSSD only, whereas the 4-min window was necessary for LF and total power. Since there is a need for 1 min of baseline to obtain a steady signal prior the analysis window, we conclude that studies relying on RMSSD may shorten the windows to 3 min (= 1+2) in SU or seated position only and to 6 min (= 1+2 min SU plus 1+2 min ST) if there is an orthostatic test. Studies relying on time- and frequency-domain parameters need a minimum of 5 min (= 1+4) min SU or seated position only but require 10 min (= 1+4 min SU plus 1+4 min ST) for the orthostatic test.

Extracting atrial activations from intracardiac signals during atrial fibrillation using adaptive mathematical morphology

The detection of intracardiac activities is a major issue in the processing of atrial fibrillation signals. we evaluate a method based on mathematical morphology with an adaptive structuring element in order to extract the atrial activations from intracardiac electrograms. The structuring element is continuously updated for each activation based on the morphological characteristics of the previously detected activations. A dataset of recordings from patients with chronic atrial fibrillation who underwent catheter ablation were used in order to evaluate the performance of the proposed method. Results show high performance compared to a dataset manually annotated by an expert. The detection rate, sensitivity and positive prediction value (PPV) were respectively 99.1%, 99.5%, 99.5%. The proposed method is fast and offers low computational cost, which makes it a suitable approach for real-time/online scenarios.

Concealed abnormal atrial phenotype in patients with Brugada syndrome and no history of atrial fibrillation

OBJECTIVES The electrocardiogram (ECG) of patients with BrS in sinus rhythm might reflect intrinsic atrial electrical abnormalities independent from any previous atrial fibrillation (AF). Aim of this study is to investigate the presence of P-wave abnormalities in patients with BrS and no history of AF, and to compare them with those displayed by patients with documented paroxysmal AF and by healthy subjects. METHODS Continuous 5-min 16-lead ECG recordings in sinus rhythm were obtained from 72 participants: 32 patients with a type 1 Brugada ECG, 20 patients with a history of paroxysmal AF and 20 age-matched healthy subjects. Different ECG-based features were computed on the P-wave first principal component representing the predominant morphology across leads and containing the maximal information on atrial depolarization: duration, full width half maximum (FWHM), area under the curve and number of peaks in the wave. RESULTS Patients with BrS and no history of AF (mean age: 53±12years; males: 28 pts., spontaneous type 1 ECG: 20 pts., SCN5A mutation: 10 pts) presented with longer P-wave duration, higher FWHM and wider area under the curve in comparison with the other two groups. Although P-wave features were abnormal in BrS patients, no significant difference was found between patients with spontaneous type 1 ECG and ajmaline-induced type 1 ECG, symptomatic and asymptomatic ones, and between patients with a pathogenic SCNA5 mutation and patients without a known gene mutation. CONCLUSIONS Patients with BrS without previous occurrence of AF present with a concealed abnormal atrial phenotype. In these patients atrial electrical abnormalities can be detected even in the absence of an overt ECG ventricular phenotype, symptoms and a SCN5A mutation.

A Novel Short-Term Event Extraction Algorithm for Biomedical Signals

In this paper, we propose a fast novel nonlinear filtering method named Relative-Energy (Rel-En), for robust short-term event extraction from biomedical signals. We developed an algorithm that extracts short- and long-term energies in a signal and provides a coefficient vector with which the signal is multiplied, heightening events of interest. This algorithm is thoroughly assessed on benchmark datasets in three different biomedical applications, namely ECG QRS-complex detection, EEG K-complex detection, and imaging photoplethysmography (iPPG) peak detection. Rel-En successfully identified the events in these settings. Compared to the state-of-the-art, better or comparable results were obtained on QRS-complex and K-complex detection. For iPPG peak detection, the proposed method was used as a preprocessing step to a fixed threshold algorithm that lead to a significant improvement in overall results. While easily defined and computed, Rel-En robustly extracted short-term events of interest. The proposed algorithm can be implemented by two filters and its parameters can be selected easily and intuitively. Furthermore, Rel-En algorithm can be used in other biomedical signal processing applications where a need of short-term event extraction is present.

AltitudeOmics: Baroreflex Sensitivity During Acclimatization to 5,260 m

Introduction: Baroreflex sensitivity (BRS) is essential to ensure rapid adjustment to variations in blood pressure (BP). Little is known concerning the adaptive responses of BRS during acclimatization to high altitude at rest and during exercise. Methods: Twenty-one healthy sea-level residents were tested near sea level (SL, 130 m), the 1st (ALT1) and 16th day (ALT16) at 5,260 m using radial artery catheterization. BRS was calculated using the sequence method (direct interpretation of causal link between BP and heartrate). At rest, subjects breathed a hyperoxic mixture (250 mmHg O2, end tidal) to isolate the preponderance of CO2 chemoreceptors. End-tidal CO2 varied from 20 to 50 mmHg to assess peripheral chemoreflex. Rebreathing provoked incremental increase in CO2, increasing BP to assess baroreflex. During incremental cycling exercise to exhaustion, subjects breathed room air. Results: Resting BRS decreased in ALT1 which was exacerbated in ALT16. This decrease in ALT1 was reversible upon additional inspired CO2, but not in ALT16. BRS decrease during exercise was greater and occurred at lower workloads in ALT1 compared to SL. At ALT16, this decrease returned toward SL values. Discussion/Conclusion: This study is the first to report attenuated BRS in acute hypoxia, exacerbated in chronic hypoxia. In ALT1, hypocapnia triggered BRS reduction whilst in ALT16 resetting of chemoreceptor triggered BRS reduction. The exercise BRS resetting was impaired in ALT1 but normalized in ALT16. These BRS decreases indicate decreased control of BP and may explain deteriorations of cardiovascular status during exposure to high altitude.