Open-source software for respiratory rate estimation using single-lead electrocardiograms.

Respiratory rate (RR) is a critical vital sign used to assess pulmonary function. Currently, RR estimating instrumentation is specialized and bulky, therefore unsuitable for remote health monitoring. Previously, RR was estimated using proprietary software that extract surface electrocardiogram (ECG) waveform features obtained at several thoracic locations. However, developing a non-proprietary method that uses minimal ECG leads, generally available from mobile cardiac monitors is highly desirable. Here, we introduce an open-source and well-documented Python-based algorithm that estimates RR requiring only single-stream ECG signals. The algorithm was first developed using ECGs from awake, spontaneously breathing adult human subjects. The algorithm-estimated RRs exhibited close linear correlation to the subjects' true RR values demonstrating an R2 of 0.9092 and root mean square error of 2.2 bpm. The algorithm robustness was then tested using ECGs generated by the ischemic hearts of anesthetized, mechanically ventilated sheep. Although the ECG waveforms during ischemia exhibited severe morphologic changes, the algorithm-determined RRs exhibited high fidelity with a resolution of 1 bpm, an absolute error of 0.07 ± 0.07 bpm, and a relative error of 0.67 ± 0.64%. This optimized Python-based RR estimation technique will likely be widely adapted for remote lung function assessment in patients with cardiopulmonary disease.

Distinct Electrogram Features and Ventricular Arrhythmia Induction Modes Between Repolarization and Conduction Heterogeneities.

BACKGROUND: Recent clinical studies have indicated the presence of localized electrical abnormalities in idiopathic ventricular fibrillation and J-wave syndrome patients. OBJECTIVES: This study aims to characterize the specific electrical signatures of localized repolarization and conduction heterogeneities and their respective role in vulnerability to arrhythmias. METHODS: Optical mapping was performed in porcine right ventricles with local: 1) repolarization shortening; 2) conduction slowing; or 3) structural heterogeneity induced by locally perfusing: 1) pinacidil (20 µmol/L, n = 13); or 2) flecainide (2 µmol/L, n = 13) via an epicardial catheter; or 3) by local epicardial tissue destruction (9 radiofrequency lesions n = 12). Electrograms were recorded (n = 5 in each group) and spontaneous and induced arrhythmias were quantified and optically mapped. RESULTS: Electrograms were normal in (1) but showed local fragmentation in 40% of preparations in (2) with greater effects observed at high pacing frequencies dependent on the wavefront direction. In (3), the structural substrate alone increased the width and number of peaks in the electrograms, and addition of flecainide induced pronounced fragmentation (≥3 peaks and ≥70 ms) in all cases. Occurrence of spontaneous arrhythmias was significantly increased in (1) and (2) (P < 0.0001 and 0.05, respectively, vs baseline) and were triggered by ectopies. Vulnerability to arrhythmias at high pacing frequencies (≥2 Hz) was the lowest in (1) and greatest in (2). CONCLUSIONS: Microstructural substrates have the most pronounced impact on electrograms, especially when combined with sodium channel blockers, whereas local action potential duration shortening does not lead to electrogram fragmentation even though it is associated with the highest prevalence of spontaneous arrhythmias.