Novel Diagnostic Model for the Deficient and Excess Pulse Qualities

The deficient and excess pulse qualities (DEPs) are the two representatives of the deficiency and excess syndromes, respectively. Despite its importance in the objectification of pulse diagnosis, a reliable classification model for the DEPs has not been reported to date. In this work, we propose a classification method for the DEPs based on a clinical study. First, through factor analysis and Fisher's discriminant analysis, we show that all the pulse amplitudes obtained at various applied pressures at Chon, Gwan, and Cheok contribute on equal orders of magnitude in the determination of the DEPs. Then, we discuss that the pulse pressure or the average pulse amplitude is appropriate for describing the collective behaviors of the pulse amplitudes and a simple and reliable classification can be constructed from either quantity. Finally, we propose an enhanced classification model that combines the two complementary variables sequentially

Active force generation contributes to the complexity of spontaneous activity and to the response to stretch of murine cardiomyocyte cultures.

Monolayer cultures of cardiac cells exhibit spontaneous electrical and contractile activity, as in a natural cardiac pacemaker. Beating variability in these preparations recapitulates the power-law behavior of heart rate variability in vivo. However, the effects of mechano-electrical feedback on beating variability are not yet fully understood. Using stretchable microelectrode arrays, we examined the effects of the contraction uncoupler blebbistatin and the non-specific stretch activated channel blocker streptomycin on beating variability and on stretch-induced changes of beat rate. Without stretch, blebbistatin decreased the spatial complexity of beating variability, while streptomycin had no effects. Both stretch and release transiently increased beat rate; blebbistatin attenuated the increase of beat rate upon stretch, while streptomycin had no effects. Active force generation contributes to the complexity of spatiotemporal patterns of beating variability and to the increase of beat rate upon mechanical deformation. Our study contributes to understanding how mechano-electric feedback influences heart rate variability. Cardiomyocyte cultures exhibit spontaneous electrical and contractile activity, as in a natural cardiac pacemaker. In such preparations, beat rate variability exhibits features similar to those of heart rate variability in vivo. Mechanical deformations and forces feedback on the electrical properties of cardiomyocytes, but it is not fully elucidated how this mechano-electrical interplay affects beating variability in such preparations. Using stretchable microelectrode arrays, we assessed the effects of the myosin inhibitor blebbistatin and the nonselective stretch-activated channel blocker streptomycin on beating variability and on the response of neonatal or foetal murine ventricular cell cultures against deformation. Spontaneous electrical activity was recorded without stretch and upon predefined deformation protocols (5% uniaxial and 2% equibiaxial strain, applied repeatedly for 1 min every 3 min). Without stretch, spontaneous activity originated from the edge of the preparations, and its site of origin switched frequently in a complex manner across the cultures. Blebbistatin did not change mean beat rate, but it decreased the spatial complexity of spontaneous activity. In contrast, streptomycin did not exert any manifest effects. During the deformation protocols, beat rate transiently increased upon stretch, but paradoxically also upon release. Blebbistatin attenuated the response to stretch, while this response was not affected by streptomycin. Therefore, our data support the notion that in a spontaneously firing network of cardiomyocytes, active force generation, rather than stretch-activated channels, is mechanistically involved in the complexity of the spatiotemporal patterns of spontaneous activity and in the stretch-induced acceleration of beating. Abstract figure legend Mechano-electric feedback modulates myocardial electrical function, including pacemaking. By growing monolayer cultures of spontaneously active murine cardiac cells on stretchable microelectrode arrays, we examined whether active contractions influence the spatiotemporal characteristics of beating variability and the effects of stretching on beat rate. Under control conditions (no stretch and no pharmacological agent), the origin of the electrical activity changed frequently. After blocking contractions with blebbistatin, the spatiotemporal pattern of electrical activity became less variable and less complex. Under control conditions (no pharmacological agent), stretching (and also releasing) the cardiomyocyte monolayers transiently increased beat rate. Blebbistatin attenuated the acceleration of beating upon stretch. In contrast, streptomycin had no detectable effects. Thus, active force generation is involved in determining beating variability in spontaneously active cardiac tissue. Possible mechanisms may include cellular processes that sense contraction and chemical messengers. Our study contributes to understanding how mechano-electric feedback influences heart rate variability. This article is protected by copyright. All rights reserved

Complexity of Atrial Fibrillation Electrograms Through Nonlinear Signal Analysis: In Silico Approach

Identification of atrial fibrillation (AF) mechanisms could improve the rate of ablation success. However, the incomplete understanding of those mechanisms makes difficult the decision of targeting sites for ablation. This work is focused on the importance of EGM analysis for detecting and modulating rotors to guide ablation procedures and improve its outcomes. Virtual atrial models are used to show how nonlinear measures can be used to generate electroanatomical maps to detect critical sites in AF. A description of the atrial cell mathematical models, and the procedure of coupling them within two‐dimensional and three‐dimensional virtual atrial models in order to simulate arrhythmogenic mechanisms, is given. Mathematical modeling of unipolar and bipolar electrogramas (EGM) is introduced. It follows a discussion of EGM signal processing. Nonlinear descriptors, such as approximate entropy and multifractal analysis, are used to study the dynamical behavior of EGM signals, which are not well described by a linear law. Our results evince that nonlinear analysis of EGM can provide information about the dynamics of rotors and other mechanisms of AF. Furthermore, these fibrillatory patterns can be simulated using virtual models. The combination of features using machine learning tools can be used for identifying arrhythmogenic sources of AF

Design, construction and validation of a registering and analysis system for the electrophysiological properties of an isolated porcine heart model

Cardiac fibrillation is as a relevant subject of study in cardiovascular diseases. Its initiation mechanisms, maintenance and interruption processes are still partially misunderstood. Quantifying the complexity of electrocardiographic signals allows researchers to objectify induced modifications by a particular therapeutic treatment. With the aim to study alterations in the cardiac substrate, the objective of this project is to design, build and validate a real-time registering and analysis system for the electrophysiological properties of the epicardial and endocardial tissue of an isolated porcine heart model. We propose a functional computer user interface. We designed and implemented a platform capable of real-time quantifying electrocardiographic signals. The corresponding methodology consists of the use of a combination of time and frequency domain analysis algorithms divided in separate blocks that work together. While the first block detects the heart rhythm and ECG features according to a Pan and Tompkins based algorithm, the second block detects the fundamental frequency of the myocardial activations based on frequency analysis; and the third one detects ventricular fibrillation episodes based on a phase-space reconstruction of the signal. This system was tested by developing an electrocardiographic waveform simulator. We performed five ex-vivo experiments for validation of the platform using isolated porcine hearts in a Langendorff bioreactor, by means of a controlled backward perfusion of the coronary arteries. Whole-heart optical mapping was carried out as the gold standard, and comparisons between the off-line analysis of the optical recordings and real-time results obtained with the developed platform were made. Results showed that electrical signals registered with the developed platform were in accordance with dominant frequency maps obtained from the off-line analysis of the corresponding optical recordings. The developed platform was able to real-time differentiate onset of ventricular fibrillation events from sinus rhythm episodes, as well as automatically detect myocardial rhythm and fundamental frequency of myocardial activations. We conclude that the proposed system is a versatile tool that allows us to easily, quickly and automatically real-timely quantify in a reproducible way electrocardiographic recordings of isolated hearts in a Langendorff bioreactor. This, in turn, would help in the performance of various clinical applications: from ex-vivo studies of the cardiac substrate to the testing of potential antiarrhythmic drugs.Ingeniería Biomédic

Novel Framework for Nonlinear HRV Analysis and its Physiological Interpretation

La inclusión de métodos no lineales aplicados a señales de variabilidad del ritmo cardiaco (HRV, del inglés Heart Rate Variability) proporciona una nueva visión en la caracterización de anomalías en el contexto de las enfermedades cardiacas o patologías como la insuficiencia cardiaca o la fibrilación auricular, por nombrar algunas. Se ha demostrado que alteraciones en el sistema nervioso autónomo (ANS, del inglés Autonomic Nervous System), el cuál modula el ritmo cardiaco, conllevan a cambios en los patrones no lineales de la HRV. Sin embargo, la incertidumbre, todavía presente, en los mecanismos que subyacen a variaciones fisiológicas o patofisiológicas en los índices no lineales de la HRV, junto con el alto tiempo que requieren los algoritmos para la estimación de estos índices, representan el cuello de botella para su aplicación en la práctica clínica.Después de una breve introducción sobre los temas abordados en esta la tesis en el capítulo 1, el segundo capítulo, el capítulo 2, está dedicado a la primera gran contribución de esta tesis, que consiste en la propuesta y desarrollo de una metodología con el fin de reducir el coste computacional asociado a la caracterización no lineal de la HRV. El esquema propuesto es muy eficaz, reduciendo el tiempo de cálculo a unos pocos segundos para el análisis no lineal de señales de HRV de corta longitud (5 minutos). Con respecto a la interpretación del análisis no lineal de la HRV, es importante señalar que hay una serie de factores que afectan a su cálculo y deben tenerse en cuenta al comparar diferentes estudios de la literatura. Las características de las series de HRV, como la frecuencia de muestreo, así como la selección de valores de parámetros en los métodos no lineales, tienen un impacto en los resultados de los índices no lineales de la HRV y, en algunas circunstancias, pueden dar lugar a interpretaciones erróneas. Uno de los principales objetivos del capítulo 3 es estudiar la influencia de la tasa de muestreo en los índices no lineales de la HRV y proponer alternativas para atenuar esta influencia. Los métodos propuestos incluyen, por una parte, la corrección de la frecuencia cardiaca de las estimaciones de la HRV mediante fórmulas de regresión individuales o basadas en la población y, por otra, el preprocesamiento de las series temporales de HRV mediante modelos de interpolación o de point-process. El capítulo 4 se centra en investigar el efecto de la selección del valor de los parámetros requeridos para el cálculo de ciertos índices no lineales de la HRV (por ejemplo, la entropía aproximada) y proponiendo un nuevo índice independiente de la definición del valor de éstos parámetros a-priori. Este novedoso índice se denomina entropía multidimensional aproximada. El análisis no lineal de la HRV, incluido el nuevo índice propuesto, se aplica al estudio de afecciones asociadas a alteraciones de la modulación cardiaca del ANS, como el envejecimiento y la insuficiencia cardiaca congestiva (CHF, del inglés Congestive Heart Failure). Por un lado, todos los índices no lineales de la HRV evaluados ven disminuidos significativamente sus valores en las personas mayores en comparación con los jóvenes ambos grupos en condiciones de reposo en posición de decubito supino. Por otro lado, los pacientes con insuficiencia cardiaca muestran valores más altos de los índices no lineales significativamente con respecto al grupo de sujetos sanos, en ambos casos analizando el período nocturno. Además, el análisis no lineal de la HRV es evaluada en respuesta a provocaciones simpáticas, inducidas por el cambio de la posición supina a la posición de pie o por la administración de atropina, donde se observa una disminución en todos los índicesno lineales estimados.El capítulo 5 está dedicado a la evaluación del rendimiento del análisis no lineal de la HRV en el triaje de la administración profiláctica con el fin de prevenir los episodios de hipotension causados por la anestesia espinal durante el parto por cesárea. El estudio se realiza en colaboración con el Servicio de Anestesia del Hospital Universitario Miguel Servet (Zaragoza, España). Debido a que la profilaxis puede producir efectos secundarios en el feto, el desafío consiste en predecir los casos normotensos para los cuales se puede prescindir del tratamiento profilactico. La hipótesis de esta tesis se basa en el hecho de que la alteración de la regulación del ANS causada por el último período de embarazo y la proximidad a la cirugía podría reflejarse en los índices no lineales de la HRV, lo que podría ayudar a predecir los casos que deriven en hipotension y normotension con mayor precisión que cuando se utilizan solamente variables demográficas. Es importante destacar que las propuestas metodológicas para el análisis no lineal de la HRV desarrolladas en la tesis se aplican en la caracterización de otras señales cardiovasculares, como la señal fotopletismografica de pulso. Las series temporales derivadas de esta señal, que incluyen información del sistema vascular periférico, se incorporan en un clasificador basado en la regresión logística junto con los índices no lineales de la HRV. El clasificador propuesto alcanza un 76,5% de sensibilidad y un 72,2% de precisión en la detección de los casos normotensos, proporcionando así información pertinente y objetiva respaldando la decisión final del equipo médico.En el capítulo 6 se presentan las principales conclusiones derivadas de la tesis y se consideran futuras ampliaciones en base a las investigaciones llevadas a cabo. Se hace hincapié en la contribución de la tesis al desarrollo de metodologías novedosas para caracterizar de manera más robusta los índices no lineales de la HRV e interpretar con fiabilidad los resultados correspondientes. Basándose en las metodologías desarrolladas, se investigan las condiciones o patologías asociadas con alteraciones en la modulación autonómica de la actividad cardiaca y se destaca la contribución del análisis no lineal de la HRV para su caracterización. En conclusión, entre los objetivos metodológicos desarrollados en esta tesis se encuentran: i) la propuesta de un esquema de trabajo para incrementar la fiabilidad de la estimación de la dimensión de correlación, usando un algoritmo que reduce la carga computacional, facilitando su aplicabilidad en la práctica clínica; ii) el desarrollo de métodos alternativos para atenuar la dependencia de los índices no lineales de la HRV con el ritmo cardiaco medio; iii) la propuesta de un índice no lineal de la HRV multidimensional independiente de la definición a priori de parámetros para su estimación. Además, los objetivos relacionados con la aplicación clínica de lascontribuciones metodológicas son: i) la caracterización del efecto del envejecimiento en los índices no lineales de la HRV; ii) la evaluación de la complejidad e irregularidad del ritmo cardiaco en pacientes que sufren de insuficiencia cardiaca comparada con sujetos sanos; iii) la mejora de la eficacia de la profilaxis para la prevención de eventos de hipotensión después de anestesia espinal durante parto programado por cesárea.<br /

Automated Cardiac Rhythm Diagnosis for Electrophysiological Studies, an Enhanced Classifier Approach

INTRODUCTION Heart function can be impaired by rhythm disturbances (cardiac arrhythmia), illustrated by electrocardiogram (ECG) recordings. Computerised arrhythmia diagnosis is well established for ECG’s but less for intracardiac electrophysiological (EP) testing. Accurate diagnosis is pre-requisite for delivering appropriate treatment to patients however existing algorithms misdiagnose a proportion of arrhythmias. Studies suggested artificial intelligence (AI) classifiers are accurate using ECG and intracardiac electrogram features and reviews suggested new features might augment diagnosis. This study aimed to develop an accurate cardiac rhythm diagnostic algorithm for electrophysiological (EP) studies with potential application as a generic rhythm classifier. METHOD An ethically approved prospective clinical study collected clinical history, right atrial and right ventricular intracardiac electrograms, beat-to-beat cardiac stroke volume, body motion and body temperature data during EP studies. An iterative system development life-cycle was used, including knowledge management and classifier development sub-processes. Domain expert knowledge and clinical arrhythmia diagnosis were modelled, synthesised as AI classifiers and used to classify cardiac rhythms. RESULTS Data collected from 65 patients was pre-processed into instances for classifier inputs. Decision tree, naïve Bayes, neural network, support vector machine and inference engine classifiers developed using Matlab showed good performance and were combined as a production system in a mixture-of-experts multi-classifier system. 18 different rhythms were classified, with the naïve Bayes classifier used to classify 11 rhythms, decision tree 4 rhythms, neural network and support vector machine one each, unclassified instances by the inference engine classifier and final class allocation using decision rule. Production system showed overall correct clasification rate 0.960; error 0.040; mean sensitivity 0.855; mean specificity 0.977; mean κ 0.767; mean positive predictive value 0.792; mean negative predictive value 0.975; mean Pearson’s phi 0.787, with P 0.9 for sinus node dysfunction and atrio-ventricular nodal/ junctional tachycardias. Temperature, accelerometry and QT interval were assessed as features by a comparison of algorithm performances with each feature removed and found not to affect classification performance. An evaluation showed 10 beat analysis performed better than 5 beat analysis. CONCLUSIONS Modelling of the clinical diagnosis process produced an AI based mixture-of-experts multi-classifier system, which accurately diagnosed different 18 cardiac rhythms. The naïve Bayes classifier performed best and classified 11 rhythms. Features for clinical symptoms and predisposing factors, atrial electrogram morphology and changes in stroke volume were found to influence rhythm classification. High performances encourage further development and potential future improvements include: a larger sample dataset; inclusion of His and coronary sinus electrograms; data mining for unknown features with significant influence on diagnosis; binary classification. The aim to classify rhythm using artificial intelligence suitable for use during EP studies was satisfied and the research hypothesis that it outperformed current algorithms was accepted. The system was likely to be able to accept updates but needs conversion as a precursor to use in a live clinical environment

Libro de actas. XXXV Congreso Anual de la Sociedad Española de Ingeniería Biomédica

596 p.CASEIB2017 vuelve a ser el foro de referencia a nivel nacional para el intercambio científico de conocimiento, experiencias y promoción de la I D i en Ingeniería Biomédica. Un punto de encuentro de científicos, profesionales de la industria, ingenieros biomédicos y profesionales clínicos interesados en las últimas novedades en investigación, educación y aplicación industrial y clínica de la ingeniería biomédica. En la presente edición, más de 160 trabajos de alto nivel científico serán presentados en áreas relevantes de la ingeniería biomédica, tales como: procesado de señal e imagen, instrumentación biomédica, telemedicina, modelado de sistemas biomédicos, sistemas inteligentes y sensores, robótica, planificación y simulación quirúrgica, biofotónica y biomateriales. Cabe destacar las sesiones dedicadas a la competición por el Premio José María Ferrero Corral, y la sesión de competición de alumnos de Grado en Ingeniería biomédica, que persiguen fomentar la participación de jóvenes estudiantes e investigadores

Arrhythmic Pulses Detection Using Lempel-Ziv Complexity Analysis

Computerized pulse analysis based on traditional Chinese medicine (TCM) is relatively new in the field of automatic physiological signal analysis and diagnosis. Considerable researches have been done on the automatic classification of pulse patterns according to their features of position and shape, but because arrhythmic pulses are difficult to identify, until now none has been done to automatically identify pulses by their rhythms. This paper proposes a novel approach to the detection of arrhythmic pulses using the Lempel-Ziv complexity analysis. Four parameters, one lemma, and two rules, which are the results of heuristic approach, are presented. This approach is applied on 140 clinic pulses for detecting seven pulse patterns, not only achieving a recognition accuracy of 97.1% as assessed by experts in TCM, but also correctly extracting the periodical unit of the intermittent pulse.</p