Análisis de un algoritmo para la clasificación semiautomática de latidos en ECG

En este trabajo se presenta un algoritmo para la clasificación de latidos en la señal deECG, que puede operar tanto de manera automática como asistida. El mismo se compone porun clasificador automático previamente validado, y un algoritmo de clustering. Tanto elclasificador automático como el algoritmo de clustering utilizan características descrciptivasdel ritmo de los latidos y de su morfología. Mediante la integración de las decisiones de ambosalgoritmos, el algoritmo presentado puede desempeñarse de manera automática o condiversos grados de asistencia, dependiendo de la idoneidad del usuario. El algoritmo fueevaluado en la base de datos de arritmias del MIT‐BIH con el propósito de comparar surendimiento. En el modo automático de funcionamiento, el algoritmo propuesto ha obtenidoun rendimiento ligeramente superior al clasificador automático original; pero con solo 5 latidosanotados manualmente en 22 registros, se ha obtenido una mejora del 5% en exactitud (A),sensibilidad (S) y valor predictivo positivo (P^{+}) globales. Para el modo completamenteasistido, este algoritmo ha igualado el rendimiento de referencia con 55 veces menos esfuerzomanual y lo ha superado con 42. Estos resultados representan una mejora en el estado delarte, concluyendo que el rendimiento de un clasificador automático puede mejorarsemediante el uso eficiente de la ayuda provista por un experto

Heartbeat Classification in Wearables Using Multi-layer Perceptron and Time-Frequency Joint Distribution of ECG

Heartbeat classification using electrocardiogram (ECG) data is a vital assistive technology for wearable health solutions. We propose heartbeat feature classification based on a novel sparse representation using time-frequency joint distribution of ECG. Fundamental to this is a multi-layer perceptron, which incorporates these signatures to detect cardiac arrhythmia. This approach is validated with ECG data from MIT-BIH arrhythmia database. Results show that our approach has an average 95.7% accuracy, an improvement of 22% over state-of-the-art approaches. Additionally, ECG sparse distributed representations generates only 3.7% false negatives, reduction of 89% with respect to existing ECG signal classification techniques.Comment: 6 pages, 7 figures, published in IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE

Selective beat averaging to evaluate ventricular repolarization adaptation to deconditioning after 5 days of head-down bed rest

The study of QT/RR relationship is important for the clinical evaluation of possible risk of ventricular tachyarrhythmia. Our aim was to assess the effects of 5-days of head-down (-6 degrees) bed-rest (HDBR) on ventricular repolarization. High fidelity 12-leads Holter ECG was acquired before (PRE), the last day of HDBR (HDT5), and five days after its conclusion (POST). X, Y, Z leads were derived (inverse Dower matrix) and vectorcardiogram computed. Selective beat averaging applied to the night period resulted in averages preceded by the same stable heart rate (for each 10 msec bin amplitude, in the range 900-1200 msec). For each template (i.e., one for each bin), T-wave maximum amplitude (Tmax), T wave area, R-Tapex and R-Tend were computed. Results (in 8 male volunteers) showed that, compared to PRE, at HDT5 both R-Tapex and R-Tend resulted significantly shortened (-5% and -3%, respectively), together with a decrease in T-wave area (-7%), while Tmax was unchanged. At POST, duration parameters showed a trend towards their control values (-1.5% and -3%, respectively) while amplitude parameters resulted restored. Despite the short-term BR, cardiac adaptation to deconditioning affected ventricular repolarization during the night period. © 2012 CCAL

On the behavior of rainfall maxima at the eastern Andes

In this study, we detect high percentile rainfall events in the eastern central Andes, based on Tropical Rainfall Measuring Mission (TRMM) with a spatial resolution of 0.25 × 0.25°, a temporal resolution of 3 h, and for the duration from 2001 to 2018. We identify three areas with high mean accumulated rainfall and analyze their atmospheric behaviour and rainfall characteristics with specific focus on extreme events. Extreme events are defined by events above the 95th percentile of their daily mean accumulated rainfall. Austral summer (DJF) is the period of the year presenting the most frequent extreme events over these three regions. Daily statistics show that the spatial maxima, as well as their associated extreme events, are produced during the night. For the considered period, ERA-Interim reanalysis data, provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) with 0.75° x0.75° spatial and 6-hourly temporal resolutions, were used for the analysis of the meso- and synoptic-scale atmospheric patterns. Night- and day-time differences indicate a nocturnal overload of northerly and northeasterly low-level humidity flows arriving from tropical South America. Under these conditions, cooling descending air from the mountains may find unstable air at the surface, giving place to the development of strong local convection. Another possible mechanism is presented here: a forced ascent of the low-level flow due to the mountains, disrupting the atmospheric stratification and generating vertical displacement of air trajectories. A Principal Component Analysis (PCA) in T-mode is applied to day- and night-time data during the maximum and extreme events. The results show strong correlation areas over each subregion under study during night-time, whereas during day-time no defined patterns are found. This confirms the observed nocturnal behavior of rainfall within these three hotspots.Fil: Hierro, Rodrigo Federico. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Austral. Facultad de Ingeniería; ArgentinaFil: Burgos Fonseca, Yuditsabet. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Ramezani Ziarani, M.. Universitat Potsdam; Alemania. German Research Centre for Geosciences; AlemaniaFil: Llamedo Soria, Pablo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Austral. Facultad de Ingeniería; ArgentinaFil: Schmidt, T.. German Research Centre for Geosciences; AlemaniaFil: de la Torre, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Austral. Facultad de Ingeniería; ArgentinaFil: Alexander, Pedro Manfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentin

Tropospheric Products from High-Level GNSS Processing in Latin America

ARTÍCULO PUBLICADO EN REVISTA EXTERNA. The present geodetic reference frame in Latin America and the Caribbean is given by a network of about 400 continuously operating GNSS stations. These stations are routinely processed by ten Analysis Centres following the guidelines and standards set up by the International Earth Rotation and Reference Systems Service (IERS) and International GNSS Service (IGS). The Analysis Centres estimate daily and weekly station positions and station zenith tropospheric path delays (ZTD) with an hourly sampling rate. This contribution presents some attempts aiming at combining the individual ZTD estimations to generate consistent troposphere solutions over the entire region and to provide reliable time series of troposphere parameters, to be used as a reference. The study covers ZTD and IWV series for a time-span of 5 years (2014–2018). In addition to the combination of the individual solutions, some advances based on the precise point positioning technique using BNC software (BKG NTRIP Client) and Bernese GNSS Software V.5.2 are presented. Results are validated using the IGS ZTD products and radiosonde IWV data. The agreement was evaluated in terms of mean bias and rms of the ZTD differences w.r.t IGS products (mean bias 1.5 mm and mean rms 6.8 mm) and w.r.t ZTD from radiosonde data (mean bias 2 mm and mean rms 7.5 mm). IWV differences w.r.t radiosonde IWV data (mean bias 0.41 kg/m2 and mean rms 3.5 kg/m2).Sitio de la revista: https://link.springer.com/chapter/10.1007/1345_2020_12

Analysis of Multidomain Features for ECG Classification

In this work we studied the classification performance of models based on intervals, angles and amplitudes. These features were extracted from both ECG leads and different scales of the wavelet decomposition. The MIT-BIH Arrhythmia database was used, following AAMI recommendations for class labeling and results presentation. The training and testing set and any cross-validation division of the database was made patient-oriented. A floating feature selection algorithm was used to obtain best performing models in the training set. This model was evaluated in the test set obtaining a global accuracy of 90%; for normal beats, sensitivity (Se) 92%, positive predictive value (+P) 85%; for supraventricular beats, Se 88%, +P 93%; for ventricular beats Se 90%, +P 92%. This classifier model based on multidomain features performs better than other state of the art methods, with a fraction of the features. 1