Novel characterization method of impedance cardiography signals using time-frequency distributions

The purpose of this document is to describe a methodology to select the most adequate time-frequency distribution (TFD) kernel for the characterization of impedance cardiography signals (ICG). The predominant ICG beat was extracted from a patient and was synthetized using time-frequency variant Fourier approximations. These synthetized signals were used to optimize several TFD kernels according to a performance maximization. The optimized kernels were tested for noise resistance on a clinical database. The resulting optimized TFD kernels are presented with their performance calculated using newly proposed methods. The procedure explained in this work showcases a new method to select an appropriate kernel for ICG signals and compares the performance of different time-frequency kernels found in the literature for the case of ICG signals. We conclude that, for ICG signals, the performance (P) of the spectrogram with either Hanning or Hamming windows (P¿=¿0.780) and the extended modified beta distribution (P¿=¿0.765) provided similar results, higher than the rest of analyzed kernels.Peer ReviewedPostprint (published version

Advanced bioimpedance signal processing techniques for hemodynamic monitoring during anesthesia

Aplicat embargament des de la data de defensa fins els maig 2020.Cardiac output (CO) defines the blood flow arriving from the heart to the different organs in the body and it is thus a primary determinant of global 02 transport. Cardiac output has traditionally been measured using invasive methods, whose risk sometimes exceeds the advantages of a cardiac output monitoring. In this context, the minimization of risk in new noninvasive technologies for CO monitoring could translate into major advantages for clinicians, hospitals and patients: ease of usage and availability, reduced recovery time, and improved patient outcome. Impedance Cardiography (ICG) is a promising noninvasive technology for cardiac output monitoring but available information on the ICG signals is more scare than other physiological signals such as the electrocardiogram (ECG). The present Doctoral Thesis contributes to the development of signal treatment techniques for the ICG in order to create an innovative hemodynamic monitor. First, an extensive literature review is provided regarding the basics of the clinical background in which cardiac output monitoring is used and concerning the state of the art of cardiac output monitors on the market. This Doctoral Thesis has produced a considerable amount of clinical data which is also explained in detail. These clinical data are also useful to complement the theoretical explanation of patient indices such as heart rate variability, blood flow and blood pressure. In addition, a new method to create synthetic biomedical signals with known time-frequency characteristics is introduced. One of the first analysis in this Doctoral Thesis studies the time difference between peak points of the heart beats in the ECG and the ICG: the RC segment. This RC segment is a measure of the time delay between electrical and mechanical activity of the heart. The relationship of the RC segment with blood pressure and heart interval is analyzed. The concordance of beat durations of both the electrocardiogram and the impedance cardiogram is one of the key results to develop new artefact detection algorithms and the RC could also have an impact in describing the hemodynamics of a patient. Time-frequency distributions (TFDs) are also used to characterize how the frequency content in impedance cardiography signals change with time. Since TFDs are calculated using concrete kernels, a new method to select the best kernel by using synthetic signals is presented. Optimized TFDs of ICG signals are then calculated to extract severa! features which are used to discriminate between different anesthesia states in patients undergoing surgery. TFD-derived features are also used to describe the whole surgical operations. Relationships between TFD-derived features are analyzed and prediction models for cardiac output are designed. These prediction models prove that the TFD-derived features are related to the patients' cardiac output. Finally, a validation study for the qCO monitor is presented. The qCO monitor has been designed using sorne of the techniques which are consequence of this Doctoral Thesis. The main outputs of this work have been protected with a patent which has already been filed. As a conclusion, this Doctoral Thesis has produced a considerable amount of clinical data and a variety of analysis and processing techniques of impedance cardiography signals which have been included into commercial medical devices already available on the market.El gasto cardíaco (GC) define el flujo de sangre que llega desde el corazón a los distintos órganos del cuerpo y es, por tanto, un determinante primario del transporte global de oxígeno. Se ha medido tradicionalmente usando métodos invasivos cuyos riesgos excedían en ocasiones las ventajas de su monitorización. En este contexto, la minimización del riesgo de la monitorización del gasto cardíaco en nuevas tecnologías no invasivas podría traducirse en mayores ventajas para médicos, hospitales y pacientes: facilidad de uso, disponibilidad del equipamiento y menor tiempo de recuperación y mejores resultados en el paciente. La impedancio-cardiografía o cardiografía de impedancia (ICG} es una prometedora tecnología no invasiva para la monitorización del gasto cardíaco. Sin embargo, la información disponible sobre las señales de ICG es más escasa que otras señales fisiológicas como el electrocardiograma (ECG). La presente Tesis Doctoral contribuye al desarrollo de técnicas de tratamiento de señal de ICG para así crear un monitor hemodinámico innovador. En primer lugar, se proporciona una extensa revisión bibliográfica sobre los aspectos básicos del contexto clínico en el que se utiliza la monitorización del gasto cardíaco así como sobre el estado del arte de los monitores de gasto cardíaco que existen en el mercado. Esta Tesis Doctoral ha producido una considerable cantidad de datos clínicos que también se explican en detalle. Dichos datos clínicos también son útiles para complementar las explicaciones teóricas de los índices de paciente de variabilidad cardíaca y el flujo y la presión sanguíneos. Además, se presenta un nuevo método de creación de señales sintéticas biomédicas con características de tiempo-frecuencia conocidas. Uno de los primeros análisis de esta Tesis Doctoral estudia la diferencia temporal entre los picos de los latidos cardíacos del ECG y del ICG: el segmento RC. Este segmento RC es una medida del retardo temporal entre la actividad eléctrica y mecánica del corazón. Se analiza la relación del segmento RC con la presión arterial y el intervalo cardíaco. La concordancia entre la duración de los latidos del ECG y del ICG es uno de los resultados claves para desarrollar nuevos algoritmos de detección de artefactos y el segmento RC también podría ser relevante en la descripción de la hemodinámica de los pacientes. Las distribuciones de tiempo-frecuencia (TFD, por sus siglas en inglés) se utilizan para caracterizar cómo el contenido de las señales de impedancia cardiográfica cambia con el tiempo. Dado que las TFDs deben calcularse usando núcleos (kernels, en inglés) concretos, se presenta un nuevo método para seleccionar el mejor núcleo mediante el uso de señales sintéticas. Las TFDs de ICG optimizadas se calculan para extraer distintas características que son usadas para discriminar entre los diferentes estados de anestesia en pacientes sometidos a procesos quirúrgicos. Las características derivadas de las distribuciones de tiempo-frecuencia también son utilizadas para describir las operaciones quirúrgicas durante toda su extensión temporal. La relación entre dichas características son analizadas y se proponen distintos modelos de predicción para el gasto cardíaco. Estos modelos de predicción demuestran que las características derivadas de las distribuciones tiempo-frecuencia de señales de ICG están relacionadas con el gasto cardíaco de los pacientes. Finalmente, se presenta un estudio de validación del monitor qCO, diseñado con alguna de las técnicas que son consecuencia de esta Tesis Doctoral. Las principales conclusiones de este trabajo han sido protegidas con una patente que ya ha sido registrada. Como conclusión, esta Tesis Doctoral ha producido una considerable cantidad de datos clínicos y una variedad de técnicas de procesado y análisis de señales de cardiografía de impedancia que han sido incluidas en dispositivos biomédicos disponibles en el mercadoPostprint (published version

Advanced bioimpedance signal processing techniques for hemodynamic monitoring during anesthesia

Cardiac output (CO) defines the blood flow arriving from the heart to the different organs in the body and it is thus a primary determinant of global 02 transport. Cardiac output has traditionally been measured using invasive methods, whose risk sometimes exceeds the advantages of a cardiac output monitoring. In this context, the minimization of risk in new noninvasive technologies for CO monitoring could translate into major advantages for clinicians, hospitals and patients: ease of usage and availability, reduced recovery time, and improved patient outcome. Impedance Cardiography (ICG) is a promising noninvasive technology for cardiac output monitoring but available information on the ICG signals is more scare than other physiological signals such as the electrocardiogram (ECG). The present Doctoral Thesis contributes to the development of signal treatment techniques for the ICG in order to create an innovative hemodynamic monitor. First, an extensive literature review is provided regarding the basics of the clinical background in which cardiac output monitoring is used and concerning the state of the art of cardiac output monitors on the market. This Doctoral Thesis has produced a considerable amount of clinical data which is also explained in detail. These clinical data are also useful to complement the theoretical explanation of patient indices such as heart rate variability, blood flow and blood pressure. In addition, a new method to create synthetic biomedical signals with known time-frequency characteristics is introduced. One of the first analysis in this Doctoral Thesis studies the time difference between peak points of the heart beats in the ECG and the ICG: the RC segment. This RC segment is a measure of the time delay between electrical and mechanical activity of the heart. The relationship of the RC segment with blood pressure and heart interval is analyzed. The concordance of beat durations of both the electrocardiogram and the impedance cardiogram is one of the key results to develop new artefact detection algorithms and the RC could also have an impact in describing the hemodynamics of a patient. Time-frequency distributions (TFDs) are also used to characterize how the frequency content in impedance cardiography signals change with time. Since TFDs are calculated using concrete kernels, a new method to select the best kernel by using synthetic signals is presented. Optimized TFDs of ICG signals are then calculated to extract severa! features which are used to discriminate between different anesthesia states in patients undergoing surgery. TFD-derived features are also used to describe the whole surgical operations. Relationships between TFD-derived features are analyzed and prediction models for cardiac output are designed. These prediction models prove that the TFD-derived features are related to the patients' cardiac output. Finally, a validation study for the qCO monitor is presented. The qCO monitor has been designed using sorne of the techniques which are consequence of this Doctoral Thesis. The main outputs of this work have been protected with a patent which has already been filed. As a conclusion, this Doctoral Thesis has produced a considerable amount of clinical data and a variety of analysis and processing techniques of impedance cardiography signals which have been included into commercial medical devices already available on the market.El gasto cardíaco (GC) define el flujo de sangre que llega desde el corazón a los distintos órganos del cuerpo y es, por tanto, un determinante primario del transporte global de oxígeno. Se ha medido tradicionalmente usando métodos invasivos cuyos riesgos excedían en ocasiones las ventajas de su monitorización. En este contexto, la minimización del riesgo de la monitorización del gasto cardíaco en nuevas tecnologías no invasivas podría traducirse en mayores ventajas para médicos, hospitales y pacientes: facilidad de uso, disponibilidad del equipamiento y menor tiempo de recuperación y mejores resultados en el paciente. La impedancio-cardiografía o cardiografía de impedancia (ICG} es una prometedora tecnología no invasiva para la monitorización del gasto cardíaco. Sin embargo, la información disponible sobre las señales de ICG es más escasa que otras señales fisiológicas como el electrocardiograma (ECG). La presente Tesis Doctoral contribuye al desarrollo de técnicas de tratamiento de señal de ICG para así crear un monitor hemodinámico innovador. En primer lugar, se proporciona una extensa revisión bibliográfica sobre los aspectos básicos del contexto clínico en el que se utiliza la monitorización del gasto cardíaco así como sobre el estado del arte de los monitores de gasto cardíaco que existen en el mercado. Esta Tesis Doctoral ha producido una considerable cantidad de datos clínicos que también se explican en detalle. Dichos datos clínicos también son útiles para complementar las explicaciones teóricas de los índices de paciente de variabilidad cardíaca y el flujo y la presión sanguíneos. Además, se presenta un nuevo método de creación de señales sintéticas biomédicas con características de tiempo-frecuencia conocidas. Uno de los primeros análisis de esta Tesis Doctoral estudia la diferencia temporal entre los picos de los latidos cardíacos del ECG y del ICG: el segmento RC. Este segmento RC es una medida del retardo temporal entre la actividad eléctrica y mecánica del corazón. Se analiza la relación del segmento RC con la presión arterial y el intervalo cardíaco. La concordancia entre la duración de los latidos del ECG y del ICG es uno de los resultados claves para desarrollar nuevos algoritmos de detección de artefactos y el segmento RC también podría ser relevante en la descripción de la hemodinámica de los pacientes. Las distribuciones de tiempo-frecuencia (TFD, por sus siglas en inglés) se utilizan para caracterizar cómo el contenido de las señales de impedancia cardiográfica cambia con el tiempo. Dado que las TFDs deben calcularse usando núcleos (kernels, en inglés) concretos, se presenta un nuevo método para seleccionar el mejor núcleo mediante el uso de señales sintéticas. Las TFDs de ICG optimizadas se calculan para extraer distintas características que son usadas para discriminar entre los diferentes estados de anestesia en pacientes sometidos a procesos quirúrgicos. Las características derivadas de las distribuciones de tiempo-frecuencia también son utilizadas para describir las operaciones quirúrgicas durante toda su extensión temporal. La relación entre dichas características son analizadas y se proponen distintos modelos de predicción para el gasto cardíaco. Estos modelos de predicción demuestran que las características derivadas de las distribuciones tiempo-frecuencia de señales de ICG están relacionadas con el gasto cardíaco de los pacientes. Finalmente, se presenta un estudio de validación del monitor qCO, diseñado con alguna de las técnicas que son consecuencia de esta Tesis Doctoral. Las principales conclusiones de este trabajo han sido protegidas con una patente que ya ha sido registrada. Como conclusión, esta Tesis Doctoral ha producido una considerable cantidad de datos clínicos y una variedad de técnicas de procesado y análisis de señales de cardiografía de impedancia que han sido incluidas en dispositivos biomédicos disponibles en el mercad

Investigation of heart rate variability during sleep apnea

Sleep apnea is a disorder, where there are repetitive pauses in respiratory flow of at least 10 seconds or longer duration, and which occur more than five times per hour. Apnea has strong modulating effects on the autonomic nervous system, with prominent heart rate variation. It can be assumed that during sleep, internal influences (sympathetic and parasympathetic nervous system activities) dominate the autonomic nervous system; in addition repetitive apneas are accompanied by a pronounced increase in average heart rate. The aim of this study was to investigate the heart rate variability using spectral analysis and time-frequency analysis during sleep apnea. A total of 22 subjects (18 males and 4 females, 49 ± 20 years) were studied who were experiencing both obstructive sleep apnea and central sleep apnea in whom sleep-disordered breathing was diagnosed. In addition 6 control subjects were studied where sleep apnea was not expected. Spectral and wavelet analysis were used to investigate the heart rate variability from the sleep apnea subjects and control subjects. The results of the wavelet analysis gave information about the parasympathetic (HF) and sympatho-vagal balance (LF: HF) changes as a function of time and frequency. The spectral parameters LF, HF and LF/HF confirmed reduced parasympathetic activity in patients with sleep apnea compared to normal subjects. In addition the repetitive apneas are accompanied by a pronounced increased cyclic variation of heart rate

Non-Invasive Hemodynamic Parameters Assessment using Optoelectronic Devices

Tese de doutoramento em Engenharia Biomédica, apresentada à Faculdade de Medicina da Universidade de CoimbraA grande incidência das doenças cardiovasculares no mundo estimulou a procura de novas soluções que permitam a deteção precoce de processos patológicos associados a este tipo de doenças. Especial ênfase foi dada a métodos que permitem a monitorização da pressão arterial e da forma de onda de pressão arterial, que fornecem uma ferramenta precisa que complementa o diagnóstico baseado em múltiplos parâmetros. Da análise das características da forma de onda da pressão arterial, e da sua velocidade de propagação, podem ser extraídas importantes parâmetros clínicos de modo a avaliar o risco cardiovascular, a adaptação vascular e a eficácia terapêutica. O uso de múltiplos parâmetros permite minimizar erros na estimação de um dos parâmetros. As soluções emergentes para a monitorização cardiovascular têm-se afastado de tecnologias invasivas e caras para soluções não invasivas e sem contacto. Neste sentido, os sistemas ópticos apresentam uma grande vantagem devido ao grande progresso tecnológico sofrido nas últimas décadas. A natureza de não contacto desta tecnologia permite a medição sem distorção da forma da onda arterial ultrapassando as limitações dos aparelhos comerciais usados para este tipo de avaliação. O principal objetivo deste trabalho consistia em demonstrar que é possível adquirir através do uso de uma metodologia óptica, a forma da onda de pressão arterial sem contacto, com uma configuração que permite medir a velocidade onda de pulso (VOP) local e determinar os principais parâmetros usando algoritmos dedicados. Foram desenvolvidos quatro protótipos: três baseados em luz não-coerente e um em luz coerente. As sondas foram desenvolvidas usando uma configuração comum, composta por dois fotodetectores distanciados de 2 cm, o que garante a deteção da onda de pulso em dois pontos distintos e permite uma determinação rigorosa do tempo de trânsito. Nas sondas de luz não-coerente foram testados três fotodetectores: fotodíodos de avalanche, fotodíodos planares, e fotodíodos de efeito lateral (LEP). Os componentes do sistema óptico (protótipos das sondas e caixa de aquisição) foram desenhados com as características físicas que permitem o uso clínico, como a portabilidade, o tamanho compacto, leves, de baixo consumo e com materiais de baixo custo, ergonómicas para o operador e confortáveis para o paciente, de modo a serem consideradas uma solução interessante para a comercialização. Os testes in vivo permitiram a seleção da melhor combinação sonda/algoritmo para a determinação da PWV, usando o método da correlação e a sonda baseada em fotodíodos planares que demonstrou ser mais eficiente para a aquisição de sinais em humanos. O sistema óptico desenvolvido mostrou boa reprodutibilidade na avaliação inter e intra-operador. Um estudo alargado foi desenvolvido em 131 sujeitos jovens, com um valor médio PWV de 33.33±0.72 ms-1, confirmando o seu aumento com a idade. O teste comparativo entre a onda de distensão medida com o sistema óptico na carótida e o perfil da onda de pressão adquirida invasivamente por um cateter intra-arterial mostrou uma grande correlação entre as duas ondas (valor médio de 0.958), validando a capacidade das sondas ópticas para estimar a forma da onda de pulso de modo não-invasivo e sem contacto. A sonda óptica baseada em luz coerente foi testada em combinação com algoritmos de processamento de sinal baseados nos métodos short time Fourier transform e empirical mode decomposition, demonstrando ser capaz de determinar os pontos característicos da forma de onda com baixo erro (menor que 5ms). Uma configuração alternativa foi testada usando um fotodetector com uma maior área que permitiu obter o efeito de self-mixing fora da cavidade laser. Esta característica abriu a possibilidade de construir uma nova sonda adaptada a esta nova técnica de modo a melhorar a qualidade do sinal e permitir uma aplicação biomédica. Globalmente, os resultados obtidos para a metodologias desenvolvidas (protótipos e ferramentas de processamento de sinal associados) mostraram ser possível de medir a onda de pulso arterial na carótida, para determinar vários parâmetros clínicos e avaliar a condição cardiovascular.The world wide incidence of cardiovascular diseases (CVDs), has spurred the research efforts targeting new solutions that may be able to perform an early detection of the pathological processes associated with these diseases. Special emphasis has been given to the methods that allow the monitoring of the blood pressure and the arterial pulse waveform, thus providing a more precise tool to complement the diagnosis process based on a multi-parameter assessment approach. From the analysis of arterial pulse pressure waveform features, and its propagation velocity, important clinical parameters can be extracted in order to evaluate the CVD risk, the vascular adaptation and the therapeutic efficacy. The use of multiple parameters allows to minimize the error when compared to the approach where a subject is classified solely based on a single parameter. Emerging trends in cardiovascular monitoring are moving away from invasive and costly technologies towards non-invasive and low-cost solutions. In this sense, optical solutions represent a great advantage due to the immense technological progresses observed in the recent decades. The truly non-contact nature of optical techniques allows measurements without distortion in the shape of the pulse curve, which is one of the main limitations of the current commercial devices used in hemodynamic parameters assessment. The main objective of this work consists in demonstrating that with an optical system it is possible to acquire the arterial pulse waveform with a configuration that allows the local pulse wave velocity (PWV) measurement and the determination of the most important clinical parameters using dedicated algorithms, without physical contact with the skin of the patient. Four prototypes were developed: three based in non-coherent light and one with coherent light. All the developed optical probes have a common design structure. They include two identical photodetectors placed 2 cm apart from each other to guarantee accurate determination of local pulse transit time. Relatively to the non-coherent light probes three different probes base on photodetectors were tested: an avalanche photodiode, a planar photodiode and a lateral effect photodiode (LEP). The optical system components (probe prototypes and acquisition box) were designed to meet specific requirements that allow the clinical use, such as portability, compact size and low weight, low cost, limited power consumption, ergonomics and easy user-interface in order to be considered as an interesting solution for commercial purposes. The in vivo tests allowed the selection of the best algorithm and probe combination to determine PWV: cross-correlation algorithm and the probe with planar photodiodes demonstrated to be the most efficient. This system showed good reproducibility, as evaluated by both inter-operator and intra-operator analysis. A large study was performed in 131 young subjects, obtaining a mean value for PWV of 3.33±0.72 ms-1, thus confirming its significant increase with age. A comparative test between the distension waveform measured with the optical probe at the carotid artery and the invasive profile of the pulse pressure acquired by an intra arterial catheter showed a strong correlation (mean value of 0.958), and validates the ability of this non-invasive device to estimate the arterial pulse waveform. Also a coherent light probe was developed and tested using several processing techniques based on the short time Fourier transform and empirical mode decomposition algorithm. This approach demonstrated the ability to determine the main feature points in the waveform with low error in the pulse transit time determination (less than 5ms). An alternative configuration for the Doppler effect-based probe was tested, using a photodetector with a larger area in order to obtain the self-mixing effect outside the laser cavity. This feature opened the possibility to improve the quality of the signal which may foresee potential future biomedical applications. Globally, the results obtained with the developed methodologies (prototypes and associated algorithmic tools) proved that it is possible to measure the arterial pulse waveform in the carotid artery, to determine several clinical parameters and assess the cardiovascular condition with optical technology.Fundação para a Ciência e Tecnologia - SFRH / BD / 79334 / 201

Modeling the pulse signal by wave-shape function and analyzing by synchrosqueezing transform

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, {and} based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features