Enabling cardiovascular multimodal, high dimensional, integrative analytics

While traditionally the understanding of cardiovascular morbidity relied on the acquisition and interpretation of health data, the advances in health technologies has enabled us to collect far larger amount of health data. This thesis explores the application of advanced analytics that utilise powerful mechanisms for integrating health data across different modalities and dimensions into a single and holistic environment to better understand different diseases, with a focus on cardiovascular conditions. Different statistical methodologies are applied across a number of case studies supported by a novel methodology to integrate and simplify data collection. The work culminates in the different dataset modalities explaining different effects on morbidity: blood biomarkers, electrocardiogram recordings, RNA-Seq measurements, and different population effects piece together the understanding of a person morbidity. More specifically, explainable artificial intelligence methods were employed on structured datasets from patients with atrial fibrillation to improve the screening for the disease. Omics datasets, including RNA-sequencing and genotype datasets, were examined and new biomarkers were discovered allowing a better understanding of atrial fibrillation. Electrocardiogram signal data were used to assess the early risk prediction of heart failure, enabling clinicians to use this novel approach to estimate future incidences. Population-level data were applied to the identification of associations and temporal trajectory of diseases to better understand disease dependencies in different clinical cohorts

Interdisciplinary application of nonlinear time series methods

This paper reports on the application to field measurements of time series methods developed on the basis of the theory of deterministic chaos. The major difficulties are pointed out that arise when the data cannot be assumed to be purely deterministic and the potential that remains in this situation is discussed. For signals with weakly nonlinear structure, the presence of nonlinearity in a general sense has to be inferred statistically. The paper reviews the relevant methods and discusses the implications for deterministic modeling. Most field measurements yield nonstationary time series, which poses a severe problem for their analysis. Recent progress in the detection and understanding of nonstationarity is reported. If a clear signature of approximate determinism is found, the notions of phase space, attractors, invariant manifolds etc. provide a convenient framework for time series analysis. Although the results have to be interpreted with great care, superior performance can be achieved for typical signal processing tasks. In particular, prediction and filtering of signals are discussed, as well as the classification of system states by means of time series recordings.Comment: 86 pages, 26 figure

Intelligent Biosignal Processing in Wearable and Implantable Sensors

This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brain–machine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine

Expression and function of the connexin43G138R mutation in mice causing oculodentodigital dyplasia (ODDD) in human

The Cx43G13R expressing mice present a new conditional mouse model for ODDD, carrying the human G138R point mutation. The main findings of this study are the occurrence of all common phenotypes of the human-inherited disease ODDD, like syndactylies, craniofacial anomalies, enamel hypoplasia, and the heart related mortality of Cx43G138R heterozygously mutated mice. The mortality of the mice is likely due to the strongly decreased gap junctional function, supporting the proarrhythmic action of the G138R-mutated Cx43 protein. This appears to be associated with a strongly diminished phosphorylation (P2 band) of this protein. The expression of the mutant Cx43 in HeLa and ES cell as well as the use of primary cardiomyocytes derived from mutant embryonic hearts revealed besides a strong decrease of Cx43 mediated gap junctional coupling and increased activity of ATP releasing channels. The physiological relevance of both effects could be ascertained in vivo. </p

Study on the non-linear metrics contribution to estimate atrial fibrillation organization from the surface electrocardiogram

[EN] Atrial fibrillation (AF) is the most frequently diagnosed arrhythmia, characterized by an uncoordinated atrial electrical activation, thus causing the atria to be unable to pump blood effectively. The prevalence of AF is expected to increase significantly in the next decades as the population ages. However, both the knowledge and the treatment of this arrhythmia still have to experiment a significant progress. Previous studies have reported that AF organization, which can be defined as the repetitiveness degree of the atrial activity pattern, correlates with the arrhythmia status as well as with the therapy outcome. Thus, estimating AF organization from surface electrocardiographic (ECG) recordings constitutes a very interesting approach because ECG recordings are easy and cheap to obtain. The objective of this doctoral thesis is to assess the use of a variety of nonlinear indices in the estimation of AF organization from single-lead noninvasive ECG recordings. Apart from the most common noninvasive AF organization estimators, such as Sample Entropy (SampEn) and the dominant atrial frequency (DAF), the following nonlinear indices have been studied: Fuzzy Entropy, Spectral Entropy, Lempel-Ziv Complexity and Hurst Exponents. Moreover, since the presence of noise and ventricular residuals affects the performance of nonlinear methods, the application of a strategy aimed at reducing these nuisances has been evaluated. Therefore, the application of these metrics over the atrial activity fundamental waveform, named the main atrial wave (MAW), has been proposed. In this doctoral thesis, the following scenarios involving AF organization have been considered: the prediction of paroxysmal AF spontaneous termination, the study of the earlier signs anticipating AF termination and the classification between paroxysmal and persistent AF from short ECG recordings. Firstly, the performance of the studied metrics discriminating events related to AF organization was tested making use of a reference database aimed at predicting AF spontaneous termination. In this study, most of the proposed indices provided higher accuracy than traditional AF organization estimators. Accuracy values higher than 90% were obtained with several indices. In particular, the generalized Hurst exponents of order 1 and 2, H(1) and H(2), achieved outstanding results, thus being selected for later studies in this thesis. Furthermore, the computation of H(2) depends on two critical parameters, namely, the analyzed interval length (L) and the maximum search window for self-similarities (tau). Hence, a study with 660 combinations on these two parameters was performed, together with the sampling frequency (fs) of the recording, in order to obtain their optimal combination in computing AF organization. On the other hand, previous works analyzing the spontaneous termination of AF have been only focused on the last 2 minutes preceding the termination. In contrast, a different scenario considering longer recordings to detect the earlier signs anticipating paroxysmal AF termination has been analyzed for the first time in this thesis. H(2) was selected for the study because of its highest accuracy in AF termination prediction. Additionally, the DAF and SampEn were also computed as references. Through this study it has been corroborated that AF organization only varies significantly within the last 3 minutes before spontaneous termination. As a consequence, the early prediction of paroxysmal AF spontaneous termination does not seem feasible through the current signal analysis tools. Finally, H(2) was applied in the classification between paroxysmal and persistent AF from short ECG recordings, achieving a higher diagnostic accuracy than DAF and SampEn. This result suggests that the analysis of ambulatory ECG recordings through H(2) could be a future alternative to the use of Holter ECG recordings in the classification between paroxysmal and persistent AF.[ES] La fibrilación auricular (FA) es la arritmia más frecuente y se caracteriza por una actividad auricular descoordinada, que impide que las aurículas bombeen sangre de manera eficaz. Se espera que la prevalencia de la FA aumente significativamente en las próximas décadas debido al envejecimiento de la población. Sin embargo, tanto el conocimiento relativo a esta arritmia como su tratamiento son todavía mejorables. Estudios previos han relacionado la organización de la FA, que se puede definir como el grado de repetitividad de la actividad auricular, con el estado de la arritmia o su respuesta al tratamiento. Además, la estimación de la organización de la FA a partir de registros electrocardiográficos (ECG) de superficie resulta especialmente interesante porque su obtención es sencilla y barata. El objetivo de esta tesis doctoral es evaluar el uso de distintos índices no lineales para estimar la organización de la FA a partir del ECG. Además de los estimadores no invasivos de organización más comunes, como la entropía muestral (SampEn) y la frecuencia auricular dominante (DAF), se han estudiado los siguientes métodos no lineales: la entropía borrosa, la entropía espectral, la complejidad Lempel-Ziv y los exponentes de Hurst. Además, se ha estudiado el uso de una estrategia destinada a la reducción del ruido y los residuos de actividad ventricular para mejorar el desempeño de métodos no lineales. Así, los índices estudiados también se han aplicado sobre la forma de onda fundamental de la actividad auricular, conocida como la onda auricular principal (MAW). Se han considerado los siguientes escenarios relacionados con la organización de la FA: la predicción de la terminación espontánea de la FA paroxística, el estudio de los primeros indicios de terminación espontánea de la FA y la clasificación entre FA paroxística y FA persistente a partir de registros ECG de corta duración. Primero, se estudió la capacidad de los índices estudiados para distinguir eventos relacionados con la organización de la FA mediante el análisis de una base de datos de referencia para la predicción de su terminación espontánea. La mayoría de los índices propuestos consiguieron una mayor precisión que los estimadores tradicionales de organización. Así, varios de los índices obtuvieron una precisión superior al 90% en la predicción de la terminación espontánea de la FA. En particular, los exponentes de Hurst generalizados de orden 1 y 2, H(1) y H(2), lograron los mejores resultados de clasificación. Puesto que el cálculo de H(2) depende de dos parámetros críticos, la longitud del intervalo analizado (L) y el tamaño máximo de la ventana donde buscar similitudes (tau), se llevó a cabo un estudio con 660 combinaciones de esos dos parámetros junto con la frecuencia de muestreo (fs) del registro para determinar el uso óptimo de este índice. Por otra parte, los trabajos previos que han estudiado la terminación espontánea de la FA se han centrado en los últimos 2 minutos antes de la terminación. Por contra, en esta tesis doctoral se han estudiado por primera vez registros de mayor duración para detectar los primeros indicios de la terminación de la FA. Para ello, se eligió el uso de H(2) por su alta precisión en la predicción de la terminación de la FA. Además, la DAF y SampEn se calcularon como referencias. En este estudio se ha comprobado que la organización de la FA solamente presenta variaciones significativas en los últimos 3 minutos antes de su terminación espontánea. Por ello, la predicción temprana de la terminación no parece posible con los medios actuales de análisis de la señal. Por último, se aplicó H(2) para clasificar entre FA paroxística y FA persistente a partir de ECGs de corta duración, obteniendo una mayor precisión diagnóstica que la DAF y SampEn. Este resultado sugiere que el análisis de ECGs ambulatorios por medio de H(2) puede ser en el futuro una alte[CA] La fibril·lació auricular (FA) és l'arítmia més freqüent i es caracteritza per una activitat auricular descoordinada, que impedix que les aurícules bomben sang de manera eficaç. S'espera que la prevalença de la FA augmente significativament en les pròximes dècades a causa de l'envelliment de la població. No obstant això, tant el coneixement relatiu a esta arítmia com el seu tractament són encara millorables. Estudis previs han relacionat l'organització de la FA, que es pot definir com el grau de repetitivitat de l'activitat auricular, amb l'estat de l'arítmia o la seua resposta al tractament. A més, l'estimació de l'organització de la FA a partir de registres electrocardiogràfics (ECG) de superfície resulta especialment interessant perquè la seua obtenció és senzilla i barata. L'objectiu d'esta tesi doctoral és avaluar l'ús de distints índexs no lineals en l'estimació de l'organització de la FA a partir de l'ECG de superfície. A més dels estimadors no invasius d'organització més comuns, com l'entropia mostral (SampEn) i la freqüència auricular dominant (DAF), s'han estudiat els següents mètodes no lineals: l'entropia borrosa, l'entropia espectral, la complexitat Lempel-Ziv i els exponents de Hurst. A més, s'ha estudiat l'ús d'una estratègia destinada a la reducció del soroll i els residus d'activitat ventricular per a millorar la seua capacitat d'estimar l'organització. Així, doncs, els índexs estudiats també s'han aplicat sobre la forma d'onda fonamental de l'activitat auricular, coneguda com l'onda auricular principal (MAW). S'han considerat els següents escenaris relacionats amb l'organització de la FA: la predicció de la terminació espontània de la FA paroxística, l'estudi dels primers indicis de terminació espontània de la FA i la classificació entre FA paroxística i FA persistent a partir de registres ECG de curta duració. Primer, es va estudiar la capacitat dels índexs estudiats per a distingir esdeveniments relacionats amb l'organització de la FA per mitjà de l'anàlisi d'una base de dades de referència per a la predicció de la seua terminació espontània. La majoria dels índexs proposats van aconseguir una major precisió que els estimadors tradicionals d'organització de la FA. Així, alguns dels índexs van obtindre una precisió superior al 90% en la predicció de la terminació espontània de la FA. En particular, els exponents de Hurst generalitzats d'orde 1 i 2, H(1) i H(2), van aconseguir els millors resultats de classificació. Com el càlcul de H(2) depén de dos paràmetres crítics, la longitud de l'interval analitzat (L) i la grandària màxima de la finestra on buscar similituds (tau), es va dur a terme un estudi amb 660 combinacions d'eixos dos paràmetres junt amb la freqüència de mostratge (fs) del registre per a determinar la combinació òptima de valors per a estimar l'organització de la FA. D'altra banda, els treballs previs que han estudiat la terminació espontània de la FA s'han centrat en els últims 2 minuts abans de la terminació. Per contra, en esta tesi doctoral s'han estudiat per primera vegada registres de major duració amb l'objectiu de detectar els primers indicis de la terminació de la FA. Es va triar l'ús de H(2) per a este estudi per la seua alta precisió en la predicció de la terminació de la FA. A més, la DAF i SampEn es van calcular com a referències. En este estudi s'ha comprovat que l'organització de la FA només presenta variacions significatives en els últims 3 minuts abans de la seua terminació espontània. Per això, la predicció primerenca de la terminació no pareix possible amb els mitjans actuals d'anàlisi del senyal. Finalment, es va aplicar H(2) per a classificar entre FA paroxística i FA persistent a partir d'ECGs de curta duració, obtenint una millor precisió diagnòstica que amb la DAF i SampEn. Este resultat suggerix que l'anàlisi d'ECGs ambulatoris per mitjà de H(2) pot ser en eJulián Seguí, M. (2015). Study on the non-linear metrics contribution to estimate atrial fibrillation organization from the surface electrocardiogram [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/56150TESI

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 145

This bibliography lists 301 reports, articles, and other documents introduced into the NASA scientific and technical information system in August 1975

Responses of Healthy Subjects to Stresses of Selected Athletic Events Final Report, Jan. 1963 - Jul. 1964

Physiological responses of athletes to stress of sports event

Aerospace medicine and biology: A cumulative index to the continuing bibliography of the 1973 issues

A cumulative index to the abstracts contained in Supplements 112 through 123 of Aerospace Medicine and Biology A Continuing Bibliography is presented. It includes three indexes: subject, personal author, and corporate source

Aerospace Medicine and Biology: A cumulative index to the 1974 issues of a continuing bibliography

This publication is a cumulative index to the abstracts contained in supplements 125 through 136 of Aerospace Medicine and Biology: A Continuing Bibliography. It includes three indexes--subject, personal author, and corporate source

Novel approaches for quantitative electrogram analysis for rotor identification: Implications for ablation in patients with atrial fibrillation

University of Minnesota Ph.D. dissertation. May 2017. Major: Biomedical Engineering. Advisor: Elena Tolkacheva. 1 computer file (PDF); xxviii, 349 pages + 4 audio/video filesAtrial fibrillation (AF) is the most common sustained cardiac arrhythmia that causes stroke affecting more than 2.3 million people in the US. Catheter ablation with pulmonary vein isolation (PVI) to terminate AF is successful for paroxysmal AF but suffers limitations with persistent AF patients as current mapping methods cannot identify AF active substrates outside of PVI region. Recent evidences in the mechanistic understating of AF pathophysiology suggest that ectopic activity, localized re-entrant circuit with fibrillatory propagation and multiple circuit re-entries may all be involved in human AF. Accordingly, the hypothesis that rotor is an underlying AF mechanism is compatible with both the presence of focal discharges and multiple wavelets. Rotors are stable electrical sources which have characteristic spiral waves like appearance with a pivot point surrounded by peripheral region. Targeted ablation at the rotor pivot points in several animal studies have demonstrated efficacy in terminating AF. The objective of this dissertation was to develop robust spatiotemporal mapping techniques that can fully capture the intrinsic dynamics of the non-stationary time series intracardiac electrogram signal to accurately identify the rotor pivot zones that may cause and maintain AF. In this thesis, four time domain approaches namely multiscale entropy (MSE) recurrence period density entropy (RPDE), kurtosis and intrinsic mode function (IMF) complexity index and one frequency domain approach namely multiscale frequency (MSF) was proposed and developed for accurate identification of rotor pivot points. The novel approaches were validated using optical mapping data with induced ventricular arrhythmia in ex-vivo isolated rabbit heart with single, double and meandering rotors (including numerically simulated data). The results demonstrated the efficacy of the novel approaches in accurate identification of rotor pivot point. The chaotic nature of rotor pivot point resulted in higher complexity measured by MSE, RPDE, kurtosis, IMF and MSF compared to the stable rotor periphery that enabled its accurate identification. Additionally, the feasibility of using conventional catheter mapping system to generate patient specific 3D maps for intraprocedural guidance for catheter ablation using these novel approaches was demonstrated with 1055 intracardiac electrograms obtained from both atria’s in a persistent AF patient. Notably, the 3D maps did not provide any clinically significant information on rotor pivot point identification or the presence of rotors themselves. Validation of these novel approaches is required in large datasets with paroxysmal and persistent AF patients to evaluate their clinical utility in rotor identification as potential targets for AF ablation