37 research outputs found

    Robust Algorithms for Unattended Monitoring of Cardiovascular Health

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    Cardiovascular disease is the leading cause of death in the United States. Tracking daily changes in one’s cardiovascular health can be critical in diagnosing and managing cardiovascular disease, such as heart failure and hypertension. A toilet seat is the ideal device for monitoring parameters relating to a subject’s cardiac health in his or her home, because it is used consistently and requires no change in daily habit. The present work demonstrates the ability to accurately capture clinically relevant ECG metrics, pulse transit time based blood pressures, and other parameters across subjects and physiological states using a toilet seat-based cardiovascular monitoring system, enabled through advanced signal processing algorithms and techniques. The algorithms described herein have been designed for use with noisy physiologic signals measured at non-standard locations. A key component of these algorithms is the classification of signal quality, which allows automatic rejection of noisy segments before feature delineation and interval extractions. The present delineation algorithms have been designed to work on poor quality signals while maintaining the highest possible temporal resolution. When validated on standard databases, the custom QRS delineation algorithm has best-in-class sensitivity and precision, while the photoplethysmogram delineation algorithm has best-in-class temporal resolution. Human subject testing on normative and heart failure subjects is used to evaluate the efficacy of the proposed monitoring system and algorithms. Results show that the accuracy of the measured heart rate and blood pressure are well within the limits of AAMI standards. For the first time, a single device is capable of monitoring long-term trends in these parameters while facilitating daily measurements that are taken at rest, prior to the consumption of food and stimulants, and at consistent times each day. This system has the potential to revolutionize in-home cardiovascular monitoring

    Wearable and Nearable Biosensors and Systems for Healthcare

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    Biosensors and systems in the form of wearables and “nearables” (i.e., everyday sensorized objects with transmitting capabilities such as smartphones) are rapidly evolving for use in healthcare. Unlike conventional approaches, these technologies can enable seamless or on-demand physiological monitoring, anytime and anywhere. Such monitoring can help transform healthcare from the current reactive, one-size-fits-all, hospital-centered approach into a future proactive, personalized, decentralized structure. Wearable and nearable biosensors and systems have been made possible through integrated innovations in sensor design, electronics, data transmission, power management, and signal processing. Although much progress has been made in this field, many open challenges for the scientific community remain, especially for those applications requiring high accuracy. This book contains the 12 papers that constituted a recent Special Issue of Sensors sharing the same title. The aim of the initiative was to provide a collection of state-of-the-art investigations on wearables and nearables, in order to stimulate technological advances and the use of the technology to benefit healthcare. The topics covered by the book offer both depth and breadth pertaining to wearable and nearable technology. They include new biosensors and data transmission techniques, studies on accelerometers, signal processing, and cardiovascular monitoring, clinical applications, and validation of commercial devices

    커프리스 방식의 착용형 연속 혈압 모니터링 시스템에 관한 연구

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    학위논문 (박사)-- 서울대학교 대학원 : 공과대학 협동과정 바이오엔지니어링전공, 2019. 2. 김희찬.고혈압의 조기 진단과 고혈압 환자의 혈압 관리를 위해서는 일상생활에서의 지속적인 혈압 모니터링이 중요하다. 맥파전달시간 (Pulse transit time, PTT) 기반의 혈압 추정 방식이 이를 가능케 하는 방법으로 가장 각광 받고 있지만, 맥파전달시간을 측정하기 위해서는 여러 측정 장치들이 필요하여 일상 생활에서의 사용에 제약이 있으며, 또한 맥파전달시간 만을 이용한 수축기 혈압(Systolic blood pressure, SBP) 추정 능력은 부족함이 있는 것으로 알려져 있다. 본 학위 논문의 첫 번째 목적은 맥파전달시간 측정 시스템을 착용형으로 개발하여 간편하게 맥파전달시간을 측정할 수 있도록 함으로써 일상 생활 중 맥파전달시간을 이용한 연속적인 혈압 모니터링이 가능케 하는 것이다. 이를 위해 광용적맥파 (Photoplethysmogram, PPG) 와 심진도 (Seismocardiogram, SCG)를 동시에 측정하는 가슴 착용형 단일 장치를 개발하여, 심진도로부터 대동맥 판막의 열리는 시점을, 광용적맥파로부터 맥파의 도착 시점을 특정하여 맥파 전달 시간을 측정하였다. 개발된 시스템은 낮은 전력 소모와 소형의 간편한 디자인을 통해 24시간 동안 연속적으로 사용할 수 있도록 설계되었다. 측정된 생체신호로부터 추출된 맥파전달시간 및 기타 혈압 관련 변수들이 기기의 반복 착용에도 변하지 않음을 급간내상관계수(Intra-class correlation, ICC) 분석을 통해 확인하였고 (ICC >0.8), 또한 본 시스템에서 사용된 심진도가 대동맥 판막의 열리는 시점의 레퍼런스가 될 수 있는지도 심저항신호(Impedancecardiogram, ICG)와의 비교를 통해 검증하였다(r=0.79±0.14). 둘째로, 개발된 시스템을 이용하여 기존의 맥파 전달 시간만을 이용한 혈압 추정 방식을 보완하여 수축기 혈압의 추정 능력이 향상된 알고리즘을 개발하였다. 이를 위해, 심진도의 진폭과 맥파 전달 시간을 같이 사용하는 다변수 모델을 수축기 혈압 추정을 위해 제안하였고, 다양한 방법으로 유도된 혈압 변화 상황에서, 기존의 맥파전달시간 혹은 맥파도달시간 (Pulse arrival time, PAT) 만을 이용한 모델과 그 성능을 비교하였다. 또한, 제안된 모델이 간단한 교정절차를 통해 여러 사람에게 적용될 수 있는 가능성을 살펴보았고 더 나아가 일상 생활에서의 사용 가능성에 대해서도 검증하였다. 그 결과로 제안된 모델은 (1) 기존의 맥파전달시간 혹은 맥파도달시간 만을 이용한 모델보다 수축기 혈압 추정 능력 측면에서 더 우수하였고, (각각의 평균절대오차는 4.57, 6.01, 6,11 mmHg 였다.) (2) 간단한 교정절차만을 통해서 여러 사람에게 적용 되었을 때의 추정 능력이 국제 기준에 부합하였으며, (3) 일상 생활에서도 사용자의 아무런 개입이나 제약 없이 지속적인 혈압 모니터링이 가능함을 확인하였다. 결론적으로 본 연구에서 제안하는 착용형 연속 혈압 측정 시스템은 가슴에 부착하는 단일 기기 형태로 그 사용이 간편할 뿐 아니라 일상생활 중에서 맥파전달시간과 심진도의 진폭을 이용하여 향상된 수준의 연속 혈압 모니터링 성능을 제공하였는바, 이를 이용한 모바일 헬스케어 서비스의 가능성을 확인하였다.Continuous blood pressure (BP) monitoring is needed in daily life to enable early detection of hypertension and improve control of BP for hypertensive patients. Although the pulse transit time (PTT)-based BP estimation represents one of most promising approaches, its use in daily life is limited owing to the requirement of multi systems to measure PTT, and its performance in systolic blood pressure (SBP) estimation is not yet satisfactory. The first goal of this study is to develop a wearable system providing convenient measurement of the PTT, which facilitates continuous BP monitoring based on PTT in daily life. A single chest-worn device was developed measuring a photoplethysmogram (PPG) and a seismocardiogram (SCG) simultaneously, thereby obtaining PTT by using the SCG as timing reference of the aortic valve opening and the PPG as timing reference of pulse arrival. The presented device was designed to be compact and convenient to use, and to last for 24h by reducing power consumption of the system. The consistency of BP related parameters extracted from the system including PTT between repetitive measurements was verified by an intra-class correlation analysis, and it was over 0.8 for all parameters. In addition, the use of SCG as timing reference of the aortic valve opening was verified by comparing it with an impedance cardiogram (r = 0.79 ± 0.14). Secondly, the algorithm improving the performance of the SBP estimation was developed by using the presented system. A multivariate model using SCG amplitude (SA) in conjunction with PTT was proposed for SBP estimation, and was compared with conventional models using only PTT or pulse arrival time (PAT) in various interventions inducing BP changes. Furthermore, we validated the proposed model against the general population with a simple calibration process and verified its potential for daily use. The results suggested that (1) the proposed model, which employed SA in conjunction with PTT for SBP estimation, outperformed the conventional univariate model using PTT or PAT (the mean absolute errors were of 4.57, 6.01, and 6.11 for the proposed, PTT, and PAT models, respectively)(2) for practical use, the proposed model showed potential to be generalized with a simple calibrationand (3) the proposed model and system demonstrated the potential for continuous BP monitoring in daily life without any intervention of users or regulations. In conclusion, the presented system provides an improved performance of continuous BP monitoring in daily life by using a combination of PTT and SA with a convenient and compact single chest-worn device, and thus, it can contribute to mobile healthcare services.CONTENTS Abstract i Contents v List of Tables ix List of Figures xi List of Abbreviations xvi Chapter 1 1 General Introduction 1.1. Blood pressure 2 1.2. Pulse transit time 6 1.3. Thesis objective 12 Chapter 2 14 Development of the Wearable Blood Pressure Monitoring System 2.1. Introduction 15 2.2. System overview 17 2.3. Bio-signal instrumentation 21 2.4. Power management 24 2.5. PCB and case design 25 2.6. Software Design 27 2.7. Signal Processing 30 2.8. Experimental setup 34 2.8.1. Repeatability test 34 2.8.2. Verification of SCG-based PEP 35 2.9. Results and Discussion 38 2.9.1. Repeatability test 38 2.9.2. Verification of SCG-based PEP 40 Chapter 3 43 Enhancement of PTT based BP estimation 3.1. Introduction 44 3.2. Method 47 3.2.1. Principle of BP estimation 47 3.2.2. Subjects 49 3.2.3. Study protocol 50 3.2.4. Data collection 56 3.2.5. Data analysis 60 3.2.6. Evaluation standard 64 3.3. Results 67 3.4. Discussion 96 Chapter 4 113 Conclusion 4.1. Thesis Summary and Contributions 114 4.2. Future Direction 116 Bibliography 118 Abstract in Korean 128Docto

    New methods for continuous non-invasive blood pressure measurement

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    Hlavním cílem této práce je nalezení nové metodiky pro měření kontinuálního neinvazivního krevního tlaku na základě rychlosti šíření pulzní vlny v krevním řečišti. Práce se opírá o rešerši zabývající se základním modelem pro stanovení kontinuálního neinvazivního krevního tlaku na základě měření zpoždění pulzní vlny a jeho rozšířením. Z informací získaných z rešerše se upravila metodika měření doby zpoždění pulzní vlny / rychlosti šíření pulzní vlny, aby bylo možné docílit přesnějších výsledků a omezit tak lidský faktor, který způsobuje významnou nepřesnost vlivem nedokonalého rozmístění senzorů. Rešerše se rovněž podrobně zabývá modely pro stanovení kontinuálního neinvazivního krevního tlaku a jejich úprav zajištujících zvýšení přesnosti. Mezi úpravy modelů zejména patří vstupní parametry popisující krevní oběh - systémový cévní odpor, elasticita cév, tuhost cév. Práce se taky zabývá úpravami stávajícího modelu krevního řečiště pro bližší přizpůsobení fyzického modelu k reálnému cévnímu systému lidského těla. Mezi tyto úpravy patří i funkce baroreflexu či simulace různé tvrdosti stěny umělých cévních segmentů. Protože se jedná o simulační model krevního řečiště, důležitým krokem je také měření tlakové a objemové pulzní vlny, kde není možné využít konvenční senzory pro fotopletysmografii kvůli absenci částic pohlcující světlo. Na základě experimentálního měření pro různé nastavení modelu krevního řečiště bylo provedeno měření pulzní vlny pomocí tlakových a kapacitních senzorů s následným zpracováním měřených signálů a detekcí příznaků charakterizující pulzní vlnu. Na základě příznaku byly stanoveny predikční regresní modely, které vykazovaly dostatečnou přesnost jejich určení, a tak následovaly dvě metody pro získání parametru o tvrdosti cévní stěny na základě měřitelných parametrů. První metodou byl predikční regresní model, který vykazoval přesnost 74,1 % a druhou metodou byl adaptivní neuro-fuzzy inferenční systém, který vykazoval přesnost 98,7 %. Tyto stanovení rychlosti pulzní vlny bylo ověřeno dalším přímým měřením pulzní vlny a výsledky byly srovnány. Výsledkem disertační práce je určení rychlosti šíření pulzní vlny s využitím pouze jednoho pletysmografického senzoru bez nutnosti měření na dvou různých místech s přesným měřením vzdálenosti a možnosti aplikace v klinické praxi.The main objective of this work is to find a new methodology for measuring continuous non-invasive blood pressure based on the pulse wave velocity in the vascular system. The work is based on the literature research of the basic model for the determination of non-invasive continuous blood pressure based on the measurement of pulse transit time. From the information obtained from the review, the methodology of measuring the pulse transit time/pulse wave velocity was modified in order to achieve more accurate results and to reduce the human factor that causes significant inaccuracy due to imperfect sensor placement. The review discusses in detail the models for continuous non-invasive blood pressure estimation and their modifications to ensure increased accuracy. In particular, model modifications include input parameters describing blood circulation - systemic vascular resistance, vascular elasticity, and vascular stiffness. The thesis deals with modifications to the existing physical vascular model to more closely mimic the real vascular system of the human body. These modifications include the baroreflex function or the simulation of different wall hardness of artificial arterial segments. As this is a simulation model of the vascular system, the measurement of pressure and volume pulse wave is also an important step, where it is not possible to use photoplethysmography method due to the absence of light absorbing particles. Based on the experimental measurements for different settings of the vascular model, pulse wave measurements were performed using pressure and capacitive sensors with subsequent processing of the measured signals and detection of the pulse wave features. Predictive regression models were established based on the pulse wave features and showed sufficient accuracy in their determination, followed by two methods for obtaining the parameter on the hardness of the vascular wall based on the measurable parameters. The first method was a predictive regression model, which showed an accuracy of 74.1 %, and the second method was an adaptive neuro-fuzzy inference system, which showed an accuracy of 98.7 %. These pulse wave velocity determinations were verified by further direct pulse wave measurements and the results were compared. The dissertation results in the determination of pulse wave propagation velocity using only one plethysmographic sensor without the need for measurements at two different locations with accurate distance measurements and the possibility of application in clinical practice.450 - Katedra kybernetiky a biomedicínského inženýrstvívyhově

    Procesado de señales biomédicas para la estimación de la presión arterial

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    Cada día aumenta más la necesidad de la monitorización de la Presión Sanguínea (BP) de manera mínimamente invasiva en las Enfermedades Cardiovasculares (CVD) o en Trastornos Respiratorios del Sueño (SDB). Este trabajo trata de estimar la Presión Sanguínea Sistólica (SBP) por medio del Tiempo de Tránsito del Pulso (PTT), el cual se puede determinar mediante la detección precisa de diferentes puntos de referencia de las señales del Electrocardiograma (ECG) y Fotopletismograma (PPG). Además, los resultados obtenidos se compararán con un conjunto de valores de referencia de la herramienta SOMNOtouch™, para ver el grado de correlación existente.The need for minimally invasive Blood Pressure (BP) monitoring due to Cardiovascular Diseases and Sleep-Disordered Breathing is increasing greatly. This work focuses on trying to estimate the Systolic Blood Pressure (SBP) using the Pulse Transit Time (PTT), which can be determined by an accurately detection of the reference points of the Electrocardiogram (ECG) and Photoplethysmogram (PPG) signals. In addition, the results will be compared with a set of reference values provided by the SOMNOtouch™ tool, in order to observe the level of existing correlation.Grado en Ingeniería en Tecnologías de Telecomunicació
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