Assessing the quality of heart rate variability estimated from wrist and finger PPG: A novel approach based on cross-mapping method

The non-invasiveness of photoplethysmographic (PPG) acquisition systems, together with their cost-effectiveness and easiness of connection with IoT technologies, is opening up to the possibility of their widespread use. For this reason, the study of the reliability of PPG and pulse rate variability (PRV) signal quality has become of great scientific, technological, and commercial interest. In this field, sensor location has been demonstrated to play a crucial role. The goal of this study was to investigate PPG and PRV signal quality acquired from two body locations: finger and wrist. We simultaneously acquired the PPG and electrocardiographic (ECG) signals from sixteen healthy subjects (aged 28.5 ± 3.5, seven females) who followed an experimental protocol of affective stimulation through visual stimuli. Statistical tests demonstrated that PPG signals acquired from the wrist and the finger presented different signal quality indexes (kurtosis and Shannon entropy), with higher values for the wrist-PPG. Then we propose to apply the cross-mapping (CM) approach as a new method to quantify the PRV signal quality. We found that the performance achieved using the two sites was significantly different in all the experimental sessions (p < 0.01), and the PRV dynamics acquired from the finger were the most similar to heart rate variability (HRV) dynamics

A preliminary attempt to understand compatibility of photoplethysmographic pulse rate variability with electrocardiogramic heart rate variability

We investigated the difference between heart rate variability (HRV) derived from electrocardiogramic (ECG) signals and pulse rate variability (PRV) derived from photoplethysmographic (PPG) signals. Ten-minute recordings of finger and ear photoplethysmogram (PPG) and Lead I electrocardiogram (ECG) were collected in fourteen healthy subjects. In this study, analyses accounting for time and frequency domain, agreement, correlation coefficient and geometrical distribution were utilized to process the ear pulse rate variability (ePRV) and finger pulse rate variability (fPRV). The agreement analysis showed high degree of agreement (Bland-Altman ratio < 0.1) between ePRV or fPRV of PPG and HRV of ECG for all the parameters except the normal-to-normal (NN) range with a moderate agreement (0.1 < Bland-Altman ratio < 0.2). Highly significant (p < 0.001) correlations (0.97 < r <1) were found between HRV and ePRV or fPRV parameters except in the NN range, where the r values were 0.92 and 0.85, respectively. Also, the experimental results indicated that the frequency-domain parameters appeared inadequate in statistical analysis. Both fPRV and ePRV were acceptable surrogates for time-domain HRV study, especially when the ECG recording was unavailable and inconvenient. Photolethysmography could offer a simple and robust means to fulfill the requirements of rhythmical pulsation assessment

Non-Invasive Detection of Mechanical Alternans Utilizing Photoplethysmography

Background and Significance: Mechanical alternans (MA) is a biomarker associated with mortality and life-threatening arrhythmias in heart failure patients. Despite showing prognostic value, its use is limited by the requirement of measuring continuous blood pressure (BP), which is costly and impractical. Objective: To develop and test, for the first time, non-invasive MA surrogates based on photoplethysmography (PPG). Methods: Continuous BP and PPG were recorded during clinical procedures and tests in 35 patients. MA was induced either by ventricular pacing (Group A, N=19) or exercise (Group B, N=16). MA was categorized as sustained or intermittent if MA episodes were observed in at least 20 or between 12 to 20 consecutive beats, respectively. Eight features characterizing pulse morphology were derived from the PPG and MA surrogates were evaluated. Results: Sustained alternans was observed in 9 patients (47%) from Group A, whereas intermittent alternans was observed in 13 patients (68%) from Group A and in 10 patients (63%) from Group B. The PPG-based MA surrogate showing the highest accuracy, V'M, was based on the maximum of the first derivative of the PPG pulse. It detected both sustained and intermittent MA with 100% sensitivity and 100% specificity in Group A and intermittent MA with 100% sensitivity and 83% specificity in Group B. Furthermore, the magnitudes of MA and its PPG-based surrogate were linearly correlated (R 2 =0.83, p<0.001). Conclusion: MA can be accurately identified non-invasively through PPG analysis. This may have important clinical implications for risk stratification and remote monitoring

Dispositivos médicos na abordagem de doentes com epilepsia

O número crescente de dispositivos médicos desenvolvidos e comercializados para melhorar a gestão de doentes com epilepsia reflete o crescente interesse em traduzir os avanços tecnológicos e o conhecimento sobre epilepsia numa melhor prestação de cuidados de saúde a esta população. O objetivo desta revisão narrativa da literatura é analisar as opções de dispositivos médicos disponíveis para deteção, tratamento e registo de crises epiléticas e a sua possível aplicação clínica. Os artigos incluídos foram selecionados através da base de dados PubMed, utilizando a query "(Epilepsy[MeSH Terms]) AND (SUDEP)) AND (Medical Device)) AND (English[Language])". A deteção de crises epiléticas é essencial para a intervenção precoce e para otimizar a terapêutica de cada doente. No ambulatório, essa deteção é um desafiado devido à sua imprevisibilidade. Tradicionalmente, o eletroencefalograma é o método direto de deteção utilizado em contexto hospitalar. Métodos indiretos de deteção, como eletrocardiograma, fotopletismografia, oxímetro, atividade eletrodérmica, acelerómetro e eletromiografia, mostraram potencial para detetar crises epiléticas em ambulatório. Vários dispositivos médicos foram desenvolvidos com base nos métodos mencionados, com o objetivo de fornecer aos doentes soluções que possam usar no seu dia-a-dia. Alguns dos designs disponíveis são o eletroencefalograma com elétrodos retroauriculares, pulseiras, braçadeiras e sensores de pressão na cama. Equipados com diferentes funções, esses dispositivos podem ajudar na deteção precoce de crises epiléticas e melhorar a qualidade de vida de doentes e cuidadores. Existem também dispositivos disponíveis para o tratamento de crises epiléticas. Por meio de técnicas de neuromodulação, como a estimulação do nervo vago, a estimulação cerebral profunda e a neuroestimulação responsiva, esses dispositivos são apresentados como soluções para doentes com epilepsias refratárias não elegíveis para cirurgia ressetiva. Os doentes com epilepsia têm várias aplicações disponíveis online para o registo adequado de crises epiléticas. Essas aplicações ajudam os médicos na otimização da terapêutica com base na evolução clínica. A ampla gama de dispositivos disponíveis cria a oportunidade de personalizar a abordagem às necessidades específicas do doente. O conhecimento das características de cada dispositivo pode ajudar os médicos a melhorar a abordagem dos doentes com epilepsia.The increasing number of medical devices developed and marketed towards management of patients with epilepsy reflects the growing interest in translating technological advances and knowledge about epilepsy into better healthcare for this population. The objective of this narrative literature review is to analyze the available options of medical devices for detecting, treating, and recording epileptic seizures, and their potential clinical application. The included articles were selected from the PubMed database using the query "(Epilepsy[MeSH Terms]) AND (SUDEP)) AND (Medical Device)) AND (English[Language])" The detection of epileptic seizures is essential for early intervention and to optimize the therapy for each patient. In outpatient settings, this detection is further challenging due to their unpredictability. Traditionally electroencephalography is the direct detection method used in a hospital environment. Indirect methods, such as electrocardiogram, photoplethysmography, oximeter, electrodermal activity, accelerometer, and electromyography, have shown potential for detecting seizures in the outpatient setting. Several medical devices have been developed based on the mentioned methods, with the aim of providing patients with solutions they can use in their daily lives. Behind-the-ear EEG, wristbands, armbands and bed sensors are some of the designs available. Equipped with different features, these devices can answer the need for early seizure detection and improve patients' and caregivers' quality of life. There are also devices available for the treatment of epileptic seizures. Through neuromodulation techniques such as vagus nerve stimulation, deep brain stimulation, and responsive neurostimulation, these devices are presented as solutions for patients with refractory epilepsy not eligible for ressective surgery. Patients with epilepsy have several apps available online for proper recording of seizures. These apps help doctors optimize therapy based on clinical evolution. The wide range of devices available creates the opportunity to personalize the approach to patient's specific needs. Understanding each device's characteristics can help clinicians improve management of patients with epilepsy

A Review of Atrial Fibrillation Detection Methods as a Service

Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it is detected, managing the condition may be challenging. In this paper, we review how the RR interval and Electrocardiogram (ECG) signals, incorporated into a monitoring system, can be useful to track AF events. Were such an automated system to be implemented, it could be used to help manage AF and thereby reduce patient morbidity and mortality. The main impetus behind the idea of developing a service is that a greater data volume analyzed can lead to better patient outcomes. Based on the literature review, which we present herein, we introduce the methods that can be used to detect AF efficiently and automatically via the RR interval and ECG signals. A cardiovascular disease monitoring service that incorporates one or multiple of these detection methods could extend event observation to all times, and could therefore become useful to establish any AF occurrence. The development of an automated and efficient method that monitors AF in real time would likely become a key component for meeting public health goals regarding the reduction of fatalities caused by the disease. Yet, at present, significant technological and regulatory obstacles remain, which prevent the development of any proposed system. Establishment of the scientific foundation for monitoring is important to provide effective service to patients and healthcare professionals

Non-invasive techniques for respiratory information extraction based on pulse photoplethysmogram and electrocardiogram

El objetivo principal de esta tesis es el desarrollo de métodos no invasivos para la extracción de información respiratoria a partir de dos señales biomédicas ampliamente utilizadas en la rutina clínica: el electrocardiograma (ECG) y la señal fotopletismográfica de pulso (PPG). La motivación de este estudio es la conveniencia de monitorizar información respiratoria a partir de dispositivos no invasivos que permita sustituir las técnicas actuales que podrían interferir con la respiración natural y que presentan inconvenientes en algunas aplicaciones como la prueba de esfuerzo y los estudios del sueño. Además, si estos dispositivos no invasivos son los ya utilizados en la rutina clínica, la información respiratoria extraída de ellos representa un valor añadido que permite tener una visión más completa del paciente. DESARROLLO TEÓRICO Esta tesis se divide en 6 capítulos. El Capítulo 1 introduce la problemática, motivaciones y objetivos del estudio. También introduce el origen fisiológico de las señales estudiadas ECG y PPG, y cómo y por qué tienen información autonómica y respiratoria que se puede extraer de ellas. El Capítulo 2 aborda la obtención de información respiratoria a partir del ECG. Se han propuesto varios métodos para la obtención de la respiración a partir del ECG (EDR, del inglés ¿ECG derived respiration?). Su rendimiento se suele ver muy afectado en entornos altamente no estacionarios y ruidosos como la prueba de esfuerzo. No obstante, se han propuesto algunas alternativas, como una basada en el ángulo de rotación del eje eléctrico (obtenido del ECG), que es el que mejor funciona en prueba de esfuerzo según nuestros conocimientos. Este método requiere de tres derivaciones ortogonales y es muy dependiente de cada una de ellas, i.e., el método no es aplicable o su rendimiento se reduce significativamente si hay algún problema en alguna de las derivaciones requeridas. En el Capítulo 2 se propone un método EDR nuevo basado en las pendientes del QRS y el ángulo de la onda R. El Capítulo 3 aborda a obtención de información respiratoria a partir de la señal PPG. Se propone un método nuevo para obtener la tasa respiratoria a partir de la señal PPG. Explota una modulación respiratoria en la variabilidad de anchura de pulso (PWV) relacionada con la velocidad y dispersión de la onda de pulso. El Capítulo 4 aborda la extracción de información respiratoria a partir de señales PPG registradas con smarthpones (SCPPG), mediante la adaptación de los métodos basados en la señal PPG presentados en el Capítulo 3. En el Capítulo 5 se propone un método para el diagnóstico del síndrome de apnea obstructiva del sueño (OSAS) en niños basado únicamente en la señal PPG. El OSAS es una disfunción relacionada con la respiración y el sueño que se diagnostica mediante polisomnografía (PSG). La PSG es el registro nocturno de muchas señales durante el sueño, siendo muy difícil de aplicar en entornos ambulatorios. El método que presenta esta tesis está enfocado a diagnosticar el OSAS en niños utilizando únicamente la señal PPG que permitiría considerar un diagnóstico ambulatorio con sus ventajas económicas y sociales. Finalmente, el Capítulo 6 resume las contribuciones originales y las conclusiones principales de esta tesis, y propone posibles extensiones del trabajo. CONCLUSIÓN El método presentado en el Capítulo 2 para estimar la tasa respiratoria a partir de las pendientes del complejo QRS y el ángulo de la onda R en el ECG demostró ser robusto en entornos altamente no estacionarios y ruidosos y por tanto ser aplicable durante ejercicio incluyendo entrenamiento deportivo. Además, es independiente de un conjunto específico de derivaciones y, por tanto, un problema en alguna de ellas no implica una reducción considerable del rendimiento. El método presentado en el Capítulo 3 para estimar la tasa respiratoria a partir de la PWV extraída de la señal PPG está mucho menos afectada por el tono simpático que otros métodos presentados en la literatura que suelen basarse en la amplitud y/o la tasa de pulso. Esto permite una mayor precisión que otros métodos basados en PPG. Además, se propone un método para combinar información de diferentes señales respiratorias, y se utiliza para estimar la tasa respiratoria a partir de la PWV en combinación con otros métodos basados en la señal PPG, mejorando la precisión de la estimación incluso en comparación con otros métodos en la literatura que requieren el ECG o la presión sanguínea. Los métodos propuestos en el Capítulo 4 para estimar la tasa respiratoria mediante señales SCPPG estimaron de forma precisa la tasa respiratoria en sus rangos espontáneos habituales (0.2-0.4 Hz) e incluso a tasas más altas (hasta 0.5 Hz o 0.6 Hz, dependiendo del dispositivo utilizado). El único requerimiento es que el smartphone tenga un luz tipo flash y una cámara para grabar una yema del dedo sobre ella. La popularidad de los smartphones los convierte en dispositivos de acceso y aceptación r¿apidos. Así, para la población general es potencialmente aceptable un método que funciona en smartphones, pudiendo facilitar la medida de algunas constantes vitales utilizando solo la yema del dedo. El método presentado en el Capítulo 5 para el diagnóstico del OSAS en niños a partir de la PPG obtuvo una precisión suficiente para la clínica, aunque antes de ser aplicado en dicho entorno, el método debería ser validado en una base de datos más grande.The main objective of this thesis is to develop non-invasive methods for respiration information extraction from two biomedical signals which are widely adopted in clinical routine: the electrocardiogram (ECG) and the pulse photoplethysmographic (PPG) signal. This study is motivated by the desirability of monitoring respiratory information from non-invasive devices allowing to substitute the current respiration-monitoring techniques which may interfere with natural breathing and which are unmanageable in some applications such as stress test or sleep studies. Furthermore, if these noninvasive devices are those already used in the clinical routine, the respiratory information obtained from them represents an added value which allows a more complete overview of the patient status. This thesis is divided into 6 chapters. Chapter 1 of this thesis introduces the problematic, motivations and objectives of this study. It also introduces the physiological origin of studied ECG and PPG signals, and why and how they carry autonomic- and respiration-related information which can be extracted from them. Chapter 2 of this thesis addresses the derivation of respiratory information from ECG signal. Several ECG derived respiration (EDR) methods have been presented in literature. Their performance usually decrease considerably in highly non-stationary and noisy environments such as stress test. However, some alternatives aimed to this kind of environments have been presented, such as one based on electrical axis rotation angles (obtained from the ECG), which to the best of our knowledge was the best suited for stress test. This method requires three orthogonal leads, and it is very dependent on each one of those leads, i.e., the performance of the method is significantly decreased if there is any problem at any one of the required leads. A novel EDR method based on QRS slopes and R-wave angle is presented in this thesis. The proposed method demonstrated to be robust in highly non-stationary and noisy environments and so to be applicable to exercise conditions including sports training. Furthermore, it is independent on a specific lead set, and so, a problem at any lead do not imply a significantly reduction of the performance. Chapter 3 addresses the derivation of respiratory information from PPG signals. A novel method for deriving respiratory rate from PPG signal is presented. It exploits respiration-related modulations in pulse width variability (PWV) which is related to pulse wave velocity and dispersion. The proposed method is much less affected by the sympathetic tone than other methods in literature which are usually based on pulses amplitude and/or rate. This leads to highest accuracy than other PPG-based method. Furthermore, a method for combining information from several respiratory signals was developed and used to obtain a respiratory rate estimation from the proposed PWV-based in combination with other known PPG-based methods, improving the accuracy of the estimation and outperforming other methods in literature which involve ECG or BP recording. Chapter 4 addresses the derivation of respiratory information from smartphone- camera-acquired-PPG (SCPPG) signals by adapting the methods for deriving respiratory rate from PPG signal presented in Chapter 3. The proposed method accurately estimates respiratory rate from SCPPG signals at its normal spontaneous ranges (0.2-0.4 Hz) and even at higher rates (up to 0.5 Hz or 0.6 Hz, depending on the used device). The only requirement is that these smartphones and tablets contain a flashlight and a video camera to image a fingertip pressed to it. As smartphones and tablets have become common, they meet the criteria of ready access and acceptance. Hence, a mobile phone/tablet approach has the potential to be widely-accepted by the general population and can facilitate the capability to measure some of the vital signs using only fingertip of the subject. Chapter 5 of this thesis proposes a methodology for obstructive sleep apnea syndrome (OSAS) screening in children just based on PPG signal. OSAS is a sleep-respiration-related dysfunction for which polysomnography (PSG) is the gold standard for diagnosis. PSG consists of overnight recording of many signals during sleep, therefore, it is quite involved and difficult to use in ambulatory scenario. The method presented in this thesis is aimed to diagnose the OSAS in children based just on PPG signal which would allow us to consider an ambulatory diagnosis with both its social and economic advantages. Finally, Chapter 6 summarizes the original contributions and main conclusions of the thesis, and proposes possible extensions of the work

Premature Atrial and Ventricular Contraction Detection using Photoplethysmographic Data from a Smartwatch

We developed an algorithm to detect premature atrial contraction (PAC) and premature ventricular contraction (PVC) using photoplethysmographic (PPG) data acquired from a smartwatch. Our PAC/PVC detection algorithm is composed of a sequence of algorithms that are combined to discriminate various arrhythmias. A novel vector resemblance method is used to enhance the PAC/PVC detection results of the Poincare plot method. The new PAC/PVC detection algorithm with our automated motion and noise artifact detection approach yielded a sensitivity of 86% for atrial fibrillation (AF) subjects while the overall sensitivity was 67% when normal sinus rhythm (NSR) subjects were also included. The specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy values for the combined data consisting of both NSR and AF subjects were 97%, 81%, 94% and 92%, respectively, for PAC/PVC detection combined with our automated motion and noise artifact detection approach. Moreover, when AF detection was compared with and without PAC/PVC, the sensitivity and specificity increased from 94.55% to 98.18% and from 95.75% to 97.90%, respectively. For additional independent testing data, we used two datasets: a smartwatch PPG dataset that was collected in our ongoing clinical study, and a pulse oximetry PPG dataset from the Medical Information Mart for Intensive Care III database. The PAC/PVC classification results of the independent testing on these two other datasets are all above 92% for sensitivity, specificity, PPV, NPV, and accuracy. The proposed combined approach to detect PAC and PVC can ultimately lead to better accuracy in AF detection. This is one of the first studies involving detection of PAC and PVC using PPG recordings from a smartwatch. The proposed method can potentially be of clinical importance as this enhanced capability can lead to fewer false positive detections of AF, especially for those NSR subjects with frequent episodes of PAC/PVC

Imaging photoplethysmography: towards effective physiological measurements

Since its conception decades ago, Photoplethysmography (PPG) the non-invasive opto-electronic technique that measures arterial pulsations in-vivo has proven its worth by achieving and maintaining its rank as a compulsory standard of patient monitoring. However successful, conventional contact monitoring mode is not suitable in certain clinical and biomedical situations, e.g., in the case of skin damage, or when unconstrained movement is required. With the advance of computer and photonics technologies, there has been a resurgence of interest in PPG and one potential route to overcome the abovementioned issues has been increasingly explored, i.e., imaging photoplethysmography (iPPG). The emerging field of iPPG offers some nascent opportunities in effective and comprehensive interpretation of the physiological phenomena, indicating a promising alternative to conventional PPG. Heart and respiration rate, perfusion mapping, and pulse rate variability have been accessed using iPPG. To effectively and remotely access physiological information through this emerging technique, a number of key issues are still to be addressed. The engineering issues of iPPG, particularly the influence of motion artefacts on signal quality, are addressed in this thesis, where an engineering model based on the revised Beer-Lambert law was developed and used to describe opto-physiological phenomena relevant to iPPG. An iPPG setup consisting of both hardware and software elements was developed to investigate its reliability and reproducibility in the context of effective remote physiological assessment. Specifically, a first study was conducted for the acquisition of vital physiological signs under various exercise conditions, i.e. resting, light and heavy cardiovascular exercise, in ten healthy subjects. The physiological parameters derived from the images captured by the iPPG system exhibited functional characteristics comparable to conventional contact PPG, i.e., maximum heart rate difference was <3 bpm and a significant (p < 0.05) correlation between both measurements were also revealed. Using a method for attenuation of motion artefacts, the heart rate and respiration rate information was successfully assessed from different anatomical locations even in high-intensity physical exercise situations. This study thereby leads to a new avenue for noncontact sensing of vital signs and remote physiological assessment, showing clear and promising applications in clinical triage and sports training. A second study was conducted to remotely assess pulse rate variability (PRV), which has been considered a valuable indicator of autonomic nervous system (ANS) status. The PRV information was obtained using the iPPG setup to appraise the ANS in ten normal subjects. The performance of the iPPG system in accessing PRV was evaluated via comparison with the readings from a contact PPG sensor. Strong correlation and good agreement between these two techniques verify the effectiveness of iPPG in the remote monitoring of PRV, thereby promoting iPPG as a potential alternative to the interpretation of physiological dynamics related to the ANS. The outcomes revealed in the thesis could present the trend of a robust non-contact technique for cardiovascular monitoring and evaluation