Poincaré Plot of Fingertip Photoplethysmogram Pulse Amplitude Suitable to Assess Diabetes Status

Multiscale entropy (MSE), an estimate of the complexity of physiological signals has been used for assessing diabetes status. This method requires much computation effort. Our study aimed to examine the Poincaré plot, an easier method for computation to differentiate the diabetes status. We selected subjects and divided them into three groups including the non- diabetes (HbA1c ≤ 6.5%, n=22), diabetes with good control (6.5% < HbA1c < 8%, n=23), and diabetes with poor control (HbA1c ≥ 8%, n=17). Poincaré method used consecutive 250 data points of PPG pulse amplitudes from each subject’s right index fingertip. This method resulted in SSR, the standard deviation of the original photoplethysmogram (PPG) pulse amplitude (SD1) and the standard deviation of the interval 1 PPG pulse amplitude (SD2) ratio. The SSR in the three groups of non-diabetes, diabetes with good control and diabetes with poor control were 0.50, 0.28, and 0.23, respectively and differed between groups (P < 0.05).  Our findings suggested that the Poincaré plot of right-hand PPG pulse amplitude may be convenient to evaluate diabetes status

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 /

Advanced analyses of physiological signals and their role in Neonatal Intensive Care

Preterm infants admitted to the neonatal intensive care unit (NICU) face an array of life-threatening diseases requiring procedures such as resuscitation and invasive monitoring, and other risks related to exposure to the hospital environment, all of which may have lifelong implications. This thesis examined a range of applications for advanced signal analyses in the NICU, from identifying of physiological patterns associated with neonatal outcomes, to evaluating the impact of certain treatments on physiological variability. Firstly, the thesis examined the potential to identify infants at risk of developing intraventricular haemorrhage, often interrelated with factors leading to preterm birth, mechanical ventilation, hypoxia and prolonged apnoeas. This thesis then characterised the cardiovascular impact of caffeine therapy which is often administered to prevent and treat apnoea of prematurity, finding greater pulse pressure variability and enhanced responsiveness of the autonomic nervous system. Cerebral autoregulation maintains cerebral blood flow despite fluctuations in arterial blood pressure and is an important consideration for preterm infants who are especially vulnerable to brain injury. Using various time and frequency domain correlation techniques, the thesis found acute changes in cerebral autoregulation of preterm infants following caffeine therapy. Nutrition in early life may also affect neurodevelopment and morbidity in later life. This thesis developed models for identifying malnutrition risk using anthropometry and near-infrared interactance features. This thesis has presented a range of ways in which advanced analyses including time series analysis, feature selection and model development can be applied to neonatal intensive care. There is a clear role for such analyses in early detection of clinical outcomes, characterising the effects of relevant treatments or pathologies and identifying infants at risk of later morbidity

On the prediction of clinical outcomes using Heart Rate Variability estimated from wearable devices

This thesis explores the use of Heart Rate Variability as a tool for predicting health outcomes, focusing on data derived from photoplethysmography (PPG) sensors in wrist-worn wearable devices such as smartwatches. These devices offer a unique opportunity for cost-effective, continuous, and unobtrusive monitoring of heart health. However, PPG data is susceptible to motion artefacts, challenging the reliability of Heart Rate Variability metrics derived from it. A critical finding of this research is the unreliability of specific frequency-domain Heart Rate Variability features, such as the Sympathovagal Balance Index (SVI), due to low signal-to-noise ratio in certain frequency bands. Conversely, the thesis demonstrates that most HRV features, including Root Mean Square of Successive Differences between normal heartbeats (RMSSD) and Standard Deviation of Normal heartbeats (SDNN), can be reliably extracted under conditions of motion, such as during physical activity or recovery from exercise. This is achieved by employing accelerometry data from wearable devices to filter out unreliable PPG data. The thesis also addresses the issue of missing data in Heart Rate Variability analysis, a consequence of motion artefacts and the energy-saving strategies of wearable devices. By exploring different interpolation methods and their effects on Heart Rate Variability features, this research identifies the best approaches for handling missing data. Particularly, it recommends operating on timestamp time-series over duration time-series, contradicting traditional Heart Rate Variability preprocessing practices. Quadratic interpolation in the time domain was identified as the most effective method, introducing minimal error across numerous Heart Rate Variability features, contrary to interpolation in the duration domain. The research presented in this thesis evaluates Heart Rate Variability features derived from ultra-short measurement windows, demonstrating the feasibility of accurately estimating RMSSD and SDNN using 30-second and 1-minute time windows, respectively. This study, unique in assessing the effect of missing values on ultra-short Heart Rate Variability data, reveals that missing values significantly impact SDNN estimations while moderately affecting RMSSD. The analysis highlights that ultra-short inter-beat interval time series limit the assessment of very low frequency (VLF) components, increasing bias in SDNN estimates. This finding is particularly significant in light of the prevalent use of SDNN in commercial wearables, underscoring its importance for continuous heart health monitoring. The study notes that the shorter the measurement window and the greater the amount of missing values, the larger the bias observed in SDNN. A novel aspect of the thesis is the creation of an innovative mathematical model designed to estimate the impact of circadian rhythms on resting heart rate. This model stands out for its computational efficiency, making it particularly suitable for data obtained from wearable devices. It surpasses the single component cosinor model in accuracy, demonstrated by a lower root mean square error (RMSE) in predicting future heart rate values. Additionally, it retains the advantage of providing easily interpretable parameters, such as MESOR, Acrophase, and Amplitude, which are essential for assessing changes in heart activity. The thesis demonstrates that Heart Rate data can accurately estimate SDNN24 (the Standard Deviation of NN intervals over 24 hours), with a difference of about 0.22±11.47 (RMSE = 53.81 and $r^2 = 0.97$). This finding indicates that despite being fragmentary, 24-hour HR data from wrist-worn fitness devices is adequate for estimating SDNN24 and assessing health status, as evidenced by an F1 score of 0.97. The robustness of SDNN24 estimation against noisy data suggests that wrist-worn wearables are capable of reliably monitoring cardiovascular health on a continuous basis, thus facilitating early interventions in response to changes in Sinoatrial Node activity. The final part of the thesis introduces an innovative approach to health outcome prediction, employing Heart Rate Variability data gathered during exercise alongside Electronic Health Record data. Employing Large Language Models to process EHR data and Convolutional AutoEncoders for Heart Rate Variability analysis, this approach reveals the untapped potential of exercise Heart Rate Variability data in health monitoring and prediction. Deep Learning models incorporating Heart Rate Variability data demonstrated enhanced predictive accuracy for cardiovascular diseases (CVD), coronary heart disease (CHD), and Angina, evidenced by higher Area Under the Curve (AUC) scores compared to models using only Electronic Health Records and demographic/behavioural data. The highest AUC scores achieved were 0.71 for CVD, 0.74 for CHD, and 0.73 for Angina. In conclusion, this thesis contributes to the field of biomedical engineering by enhancing the understanding and application of HRV analysis in health outcome prediction using wearable device data. It offers insights for future work in continuous, unobtrusive health monitoring and underscores the need for further research in this rapidly evolving domain

Discrepancies between Conventional Multiscale Entropy and Modified Short-Time Multiscale Entropy of Photoplethysmographic Pulse Signals in Middle- and Old- Aged Individuals with or without Diabetes

Multiscale entropy (MSE) of physiological signals may reflect cardiovascular health in diabetes. The classic MSE (cMSE) algorithm requires more than 750 signals for the calculations. The modified short-time MSE (sMSE) may have inconsistent outcomes compared with the cMSE at large time scales and in a disease status. Therefore, we compared the cMSE of 1500 (cMSE1500) consecutive and 1000 photoplethysmographic (PPG) pulse amplitudes with the sMSE of 500 PPG (sMSE500) pulse amplitudes of bilateral fingertips among middle- to old-aged individuals with or without type 2 diabetes. We discovered that cMSE1500 had the smallest value across scale factors 1–10, followed by cMSE1000, and then sMSE500 in both hands. The cMSE1500, cMSE1000 and sMSE500 did not differ at each scale factor in both hands of persons without diabetes and in the dominant hand of those with diabetes. In contrast, the sMSE500 differed at all scales 1–10 in the non-dominant hand with diabetes. In conclusion, autonomic dysfunction, prevalent in the non-dominant hand which had a low local physical activity in the person with diabetes, might be imprecisely evaluated by the sMSE; therefore, using more PPG signal numbers for the cMSE is preferred in such a situation

Optical Methods in Sensing and Imaging for Medical and Biological Applications

The recent advances in optical sources and detectors have opened up new opportunities for sensing and imaging techniques which can be successfully used in biomedical and healthcare applications. This book, entitled ‘Optical Methods in Sensing and Imaging for Medical and Biological Applications’, focuses on various aspects of the research and development related to these areas. The book will be a valuable source of information presenting the recent advances in optical methods and novel techniques, as well as their applications in the fields of biomedicine and healthcare, to anyone interested in this subject

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

Secondary Analysis of Electronic Health Records

Health Informatics; Ethics; Data Mining and Knowledge Discovery; Statistics for Life Sciences, Medicine, Health Science

A Sensing Platform to Monitor Sleep Efficiency

Sleep plays a fundamental role in the human life. Sleep research is mainly focused on the understanding of the sleep patterns, stages and duration. An accurate sleep monitoring can detect early signs of sleep deprivation and insomnia consequentially implementing mechanisms for preventing and overcoming these problems. Recently, sleep monitoring has been achieved using wearable technologies, able to analyse also the body movements, but old people can encounter some difficulties in using and maintaining these devices. In this paper, we propose an unobtrusive sensing platform able to analyze body movements, infer sleep duration and awakenings occurred along the night, and evaluating the sleep efficiency index. To prove the feasibility of the suggested method we did a pilot trial in which several healthy users have been involved. The sensors were installed within the bed and, on each day, each user was administered with the Groningen Sleep Quality Scale questionnaire to evaluate the user’s perceived sleep quality. Finally, we show potential correlation between a perceived evaluation with an objective index as the sleep efficiency.</p