超音波、動脈硬化、心電図などの複合器

超音波、動脈硬化、心電図などの複合器

ポータブル ホルタ型 動脈硬化計測

2017年9月26日火曜日

ローレンツプロット解析機能

ハンガリ国ラブテック社製心電図ホルターの解析機能 ローレンツプロット解析機能がHRV Analysisに含まれています。 ご参考用;ローレンツプロット解析機能が引用されている最近の文献から、 Analysis for Atrial Fibrillation using economical and accurate technology and the algorithm employ methods including Lorenz Plots and Shannon Entropy. Deterministic analysis was performed as Poincare plot analysis, also known as Lorenz plot analysis. T-wave morphology changes in Holter ECG and Lorenz plot of long term respiratory signals for elderly persons are analyzed. The algorithm uses Lorenz plots to evaluate beat-to-beat variations in the heart rhythm in several min time intervals. When autonomic nervous system disorders occur, angina or myocardial infarction might be painless, which greatly increases the risk of cardiovascular disease events. Therefore, cardiac autonomic dysfunction is usually considered to be a risk factor for cardiovascular disease, and a major cause of morbidity and mortality in diabetes. Non-linear indices include the Lorenz plot, complexity degree and approximate entropy. When devices with validated algorithms (i.e., Lorenz plots) for AF detection were utilized, a high prevalence of occult AF was detected. Etc.

2017年7月27日木曜日

Acoustic Detection of Coronary Occlusions

Acoustic Detection of Coronary Occlusions before and after Stent Placement Using an Electronic Stethoscope Andrei Dragomir 1, Allison Post 1, Yasemin M. Akay 1, Hani Jneid 2,3, David Paniagua 2,3,Ali Denktas 2,3, Biykem Bozkurt 2,3 and Metin Akay 1,*1 Department of Biomedical Engineering, University of Houston, Houston, TX 77204, USA; Andrei.Drag@gmail.com (A.D.); Allison.Post@central.uh.edu (A.P.); ymakay@uh.edu (Y.M.A.)2 Winters Center for Heart Failure Research, The Michael E. DeBakey VA Medical Center, Houston, TX 77030,USA; jneid@bcm.edu (H.J.); dpaniagua@bcm.edu (D.P.); ali.denktas@bcm.edu (A.D.);bbozkurt@bcm.edu (B.B.) 3 Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA * Correspondence: makay@uh.edu; Tel.: +1-832-842-8860 Academic Editors: Raúl Alcaraz Martínez and Kevin H. Knuth Received: 27 April 2016; Accepted: 23 July 2016; Published: 29 July 2016 Abstract: More than 370,000 Americans die every year from coronary artery disease (CAD).Early detection and treatment are crucial to reducing this number. Current diagnostic and disease-monitoring methods are invasive, costly, and time-consuming. Using an electronic stethoscope and spectral and nonlinear dynamics analysis of the recorded heart sound, we investigated the acoustic signature of CAD in subjects with only a single coronary occlusion before and after stent placement, as well as subjects with clinically normal coronary arteries. The CAD signature was evaluated by estimating power ratios of the total power above 150 Hz over the total power below 150 Hz of the FFT of the acoustic signal. Additionally, approximate entropy values were estimated to assess the differences induced by the stent placement procedure to the acoustic signature of the signals in the time domain. The groups were identified with this method with 82% sensitivity and 64% specificity (using the power ratio method) and 82% sensitivity and 55% specificity (using the approximate entropy). Power ratios and approximate entropy values after stent placement are not statistically different from those estimated from subjects with no coronary occlusions. Our approach demonstrates that the effect of stent placement on coronary occlusions can be monitored using an electronic stethoscope.

2017年7月26日水曜日

Shimmer Sensing

A wearable chemical–electrophysiological hybrid biosensing system for real-time health and fitness monitoring Somayeh Imani , Amay J. Bandodkar , A. M. Vinu Mohan , Rajan Kumar , Shengfei Yu , Joseph Wang  & Patrick P. Mercie Abstract Flexible, wearable sensing devices can yield important information about the underlying physiology of a human subject for applications in real-time health and fitness monitoring. Despite significant progress in the fabrication of flexible biosensors that naturally comply with the epidermis, most designs measure only a small number of physical or electrophysiological parameters, and neglect the rich chemical information available from biomarkers. Here, we introduce a skin-worn wearable hybrid sensing system that offers simultaneous real-time monitoring of a biochemical (lactate) and an electrophysiological signal (electrocardiogram), for more comprehensive fitness monitoring than from physical or electrophysiological sensors alone. The two sensing modalities, comprising a three-electrode amperometric lactate biosensor and a bipolar electrocardiogram sensor, are co-fabricated on a flexible substrate and mounted on the skin. Human experiments reveal that physiochemistry and electrophysiology can be measured simultaneously with negligible cross-talk, enabling a new class of hybrid sensing devices. Introduction Wearable sensors present an exciting opportunity to measure human physiology in a continuous, real-time and non-invasive manner1,2. Recent advances in hybrid fabrication techniques have enabled the design of wearable sensing devices in thin, conformal form factors that naturally comply with the smooth curvilinear geometry of human skin, thereby enabling intimate contact necessary for robust physiological measurements1,3,4. Development of such epidermal electronic sensors has enabled devices that can monitor respiration rate5,6,7, heart rate8,9, electrocardiograms4,10,11,12, blood oxygenation13, skin temperature14,15, bodily motion16,17,18,19,20, brain activity21,22,23 and blood pressure24,25. To date, most systems have targeted only a single measurement at a time, and most such sensors measure only physical and electrophysiological parameters, significantly limiting monitoring and diagnostic opportunities. For example, the human body undergoes complex physiological changes during physical activities such as exercise26,27, and monitoring the physiologic effect of physical activity can be important for a wide variety of subjects ranging from athletes to the elderly28,29,30. However, current wearable devices that only measure heart rate, motion and electrocardiogram provide an incomplete picture of the complex physiological changes taking place. As a result, further progress in the area of wearable sensors must include new, relevant sensing modalities, and must integrate these different modalities into a single platform for continuous, simultaneous sensing of multiple parameters relevant to a wide range of conditions, diseases, health and performance states

Shimmer Sensing

Knitted Strain Sensor Textiles of Highly Conductive All-Polymeric Fibers Shayan Seyedin†‡, Joselito M. Razal*†‡, Peter C. Innis†, Ali Jeiranikhameneh†, Stephen Beirne†, and Gordon G. Wallace*† † Intelligent Polymer Research Institute, ARC Centre of Excellence for Electromaterials Science, AIIM Facility, Innovation Campus, University of Wollongong, Wollongong, New South Wales 2522, Australia ‡ Institute for Frontier Materials, Deakin University, Geelong, Victoria 3216, Australia ACS Appl. Mater. Interfaces, 2015, 7 (38), pp 21150–21158 Abstract A scaled-up fiber wet-spinning production of electrically conductive and highly stretchable PU/PEDOT:PSS fibers is demonstrated for the first time. The PU/PEDOT:PSS fibers possess the mechanical properties appropriate for knitting various textile structures. The knitted textiles exhibit strain sensing properties that were dependent upon the number of PU/PEDOT:PSS fibers used in knitting. The knitted textiles show sensitivity (as measured by the gauge factor) that increases with the number of PU/PEDOT:PSS fibers deployed. A highly stable sensor response was observed when four PU/PEDOT:PSS fibers were co-knitted with a commercial Spandex yarn. The knitted textile sensor can distinguish different magnitudes of applied strain with cyclically repeatable sensor responses at applied strains of up to 160%. When used in conjunction with a commercial wireless transmitter, the knitted textile responded well to the magnitude of bending deformations, demonstrating potential for remote strain sensing applications. The feasibility of an all-polymeric knitted textile wearable strain sensor was demonstrated in a knee sleeve prototype with application in personal training and rehabilitation following injury.

Shimmer Sensing

SHIMMER PARTNERS WITH HARVARD'S WYSS INSTITUTE TO ADVANCE THE FIELD OF REMOTE PATIENT MONITORING USING WEARABLE SENSING TECHNOLOGY DUBLIN, 13 June 2016 - Shimmer Sensing, a leading provider of medical grade wearable wireless sensors, announced today a partnership with the Wyss Institute for Biologically Inspired Engineering at Harvard University in support of ongoing research focused on remote patient monitoring using wearable sensing technology. The research is led by Paolo Bonato, Ph.D., who is an Associate Faculty Member at the Wyss Institute and an Associate Professor in the Department of Physical Medicine and Rehabilitation at Harvard Medical School. "Partnering with Shimmer Sensing will allow us to further develop our remote patient monitoring platform called MercuryLive," said Bonato. MercuryLive is a platform designed to support clinicians’ remote monitoring of patients – who, for example, could have Parkinson’s disease or be stroke survivors, traumatic brain injury survivors, or children with cerebral palsy – via live streaming of wearable sensor data and an interactive video feed. Bonato’s team at the Wyss Institute is developing the latest version of the MercuryLive platform, which enables the integration of a variety of wireless devices.Shimmer’s financial support of the research and its technical expertise in wireless medical sensors will accelerate the development of MercuryLive towards applications in remote patient monitoring. Among other clinical applications, the platform being developed will allow clinicians to remotely monitor patients with knee osteoarthritis using a knee sleeve with embedded wireless sensors and observe older adults in their home using wearable sensors and a mobile robot designed to navigate the environment and reach the subject in case of an emergency. “The Wyss Institute is renowned for taking academic innovation to the next level, and partnering with physicians and the industry to bring new technologies to the bedside. We are very enthusiastic about the opportunity to support Prof. Bonato's research team and their work toward the development of the next generation of remote clinical monitoring systems,” commented Patrick White, the CEO of Shimmer Sensing. “Wearable patient monitoring systems represent the future of ambulatory medicine, and we are excited to help catalyze collaborations between engineers, clinicians and industrial partners to make this a reality,” said Wyss Institute Founding Director Donald Ingber, M.D., Ph.D., who is also the Judah Folkman Professor of Vascular Biology at Boston Children's Hospital and Harvard Medical School and Professor of Bioengineering at the Harvard John A. Paulson School of Engineering and Applied Science.

Labtech, Cardiospy

Abstract of PhD Thesis Intelligent Data Processing and Its Applications Aniko Szilvia Vanger 1 Introduction Nowadays the rapidly increasing performance of hardware and the efficient intelligent scientific algorithms enable us to store and process big data. This tendency will cover more opportunities to get more and more information from the large amount of data. My thesis is only a precursor of this topic, because I did not have sufficient hardware and I had only a little data to be processed. However, all the topics of my thesis belong to the intelligent data processing. In Chapter 2 of my thesis I introduce a new clustering algorithm named GridOPTICS, whose goal is to accelerate the well-known OPTICS density clustering technique. The density-based clustering techniques are capable of recognizing arbitrary-shaped clusters in a point set. The DBSCAN results in only one cluster set, but the OPTICS generates a reachability plot from which a lot of cluster sets can be read as a result without having to execute the whole algorithm again. I experienced that it is very slow for large data sets, so I wanted to nd a solution to accelerate it. I wanted to see that the speed of the GridOptics is better than OPTICS, so I executed both the algorithms on several point sets. In Chapter 3 of my thesis I introduce two new modules of the Cardiospy system of Labtech Ltd. On these two projects I worked together with Istvan Juhasz, Laszlo Farkas, Peter Toth, and 4 students of the university, Jozsef Kuk, Adam Balazs,Bela Vamosi, and David Angyal.Bela Kincs, who was the executive of the Labtech Ltd., wanted the Cardiospy system to be improved. He and his team surveyed what the demand of the users are in this area and how their software could be better. The Labtech Ltd. And the University of Debrecen worked together in two projects. In both cases theLabtech had early solutions for the algorithms, but they were insufficient and slow, the results could not be validated, or they gave insufficient results. Moreover, there were no visualization tools for either problems. The tasks of the team of the University of Debrecen were to give a quick algorithm and to create an interactive visualization interface for each problem. The goal of the first module of Cardiospy is to cluster and visualize the long (up to 24-hours) recordings of ECG signals, because the manual evaluation of long recordings is a lengthy and tedious task. During this project I recognized that it is a very interesting topic to find out how the OPTICS can be accelerated with a grid clustering method independently, without any ECG signals. The goal of the second module of Cardiospy is to calculate and visualize the steps of the blood pressure measurement and the values of blood pressure. The recordings (which can contain a sequence of measurements) are collected by a microcontroller, but this module runs on a PC. With the help of the application the physicians can recognize the types of errors on the measurements and they can also find the noisy measurements. In Chapter 4 I introduce how I applied an active learning method in a subject whose topic is database programming. I taught Oracle SQL and PL/SQL in the Advanced DBMS 1 subject, and I saw that the students do not practice at home. The prerequirements of this subject are the Programming language and the Database systems courses, so they are not absolute beginners in the field. I wanted to force the students to try out the programming tools independently, but with the help of the teacher. To support the active learning method, an application had to be built. The application helps the teacher organize and monitor the tasks and their solutions of the students. Moreover the application can verify the syntax of the solutions before the students upload them. If the syntax is wrong, the student cannot upload it. This feature makes the task of the teacher easier. To demonstrate whether the active learning method is good or not, I gathered and examined the results of the students during the 3 years when I used this method. New results The abstract of the thesis presents new results grouped into four main statements. The first statement deals with a clustering method, the second one demonstrates an application of this clustering method, namely clustering of ECG signals, which can be considered as an application of the GridOPTICS clustering method. The third statement introduces the visualization of the steps of the blood pressure measurement, whereas the last statement demonstrates how the solutions of the students can easily be managed during an active learning method for database programming. 2.1 A clustering algorithm Cluster analysis is an important research field of data mining, which is applied on many other disciplines, such as pattern recognition, image processing, machine learning, bioinformatics, information retrieval, artificial intelligence, marketing, psychology, etc. The density-based clustering approach is capable of finding arbitrarily shaped clusters, but they have a disadvantage, namely it is hard to choose parameter values in order that the algorithm gives an appropriate result (Gan et al., 2007). The OPTICS (Ankerst et al., 1999) clustering algorithm gives not only one result but a set of the results. It builds a reachability plot, namely it orders the input points, and it assigns a reachability distance to an input point. Based on the reachability plot, the algorithm can produce a lot of clustering results. Building the reachability plot is slow, but reading the clusters from the reachability plot is fast. The OPTICS has a limitation, namely it has high complexity, which means that it is very slow for large datasets. (Yue et al., 2007) (Schneider and Vlachos, 2013) Statement A - The GridOPTICS clustering algorithm: I introduced a new clustering algorithm named GridOPTICS which is a combination of a grid clustering technique and the OPTICS algorithm. For a large input point sets the GridOPTICS algorithm works with insignificant information loss and provides even one or more order of magnitude faster than the OPTICS algorithm. (Vagner, in press) The main idea of the GridOPTICS algorithm is to reduce the number of input points with a grid technique and then to execute the OPTICS algorithm on the grid structure. Based on the reachability plot, the clusters of the grid structure can be determined. In the end, the input points can be assigned to the clusters. The experimental results show that the execution time can be faster with more orders of magnitude than OPTICS, which is very useful for large data sets. However, they also show that the GridOPTICS algorithm is less accurate than OPTICS. 2.2 Cardiology information system for ECG signals The big data problem also appears in the medical area. Without intelligent information systems, the physicians cannot eOne of its modules is the ECG clustering module. Statement B - Clustering and visualization of ECG signals: We developed the ECG clustering and visualization module of Cardiospy software. The goal of the module is to cluster and visualize the long (up to 24-hours) recordings of ECG signals. In this way the cardiologists can easier find the heart beats which morphologically differ from the normal beats. (Vagner et al., 2011 A) On this project I worked together with Laszlo Farkas (Labtech Ltd.), Istvan Juhasz (Faculty of Informatics, University of Debrecen), and two students from the Faculty of Informatics, University of Debrecen, Jozsef Kuk and Adam Balazs. My contribution to this project was to implement the clustering algorithm and make it fast. The clustering algorithm is a special simpler version of the GridOPTICS algorithm. I also contributed to 2.3 Cardiology information system for blood pressure measurement In the public health care it is very common that a microcontroller calculates the result of oscillometric blood pressure measurements. It has only limited resources, such as memory and processor, moreover it can give only a little feedback about the measurement. This means that the result can be imprecise; it does not inform the patient and the physician appropriately. (Sorvoja, 2006) Cardiospy software has another module, the blood pressure measurement module. It receives the recordings collected by the microcontroller. The recording can contain only one measurement or sequence of measurements created during 24 hours. Cardiospy runs on a PC, in this way the algorithm can use more resources (memory and processor), which means that it is faster and more precise. Additionally, it can visualize the whole process of the measurement. Statement C { Visualization of o-line processing of blood pressure measurements: We developed the blood pressure measurement module of Cardiospy software. The goal of the blood pressure measurement module is to calculate and visualize the values of blood pressure. (Vagner et al., 2014) The module determines the values of the blood pressure based on an oscillometric blood pressure measurement algorithm. The application visualizes the result of each step of the algorithm. The algorithm decides whether the result is acceptable and authentic based on the characteristic of the measurement. The other part of the application helps in the validation process. It executes the blood pressure measurement algorithm on mass of the measurements each of which has reference blood pressure values. The application shows the differences between the results of the algorithm and the values of reference and it helps to qualify the algorithm according to the international standards. On this project I worked together with Peter Toth (Labtech Ltd.), Istvan Juhasz (Faculty of Informatics, University of Debrecen), and two students from the Faculty of Informatics, University of Debrecen, Bela Vamosi and David Angyal. My contribution to this project was to construct and implement a signal processing algorithm which produces the blood pressure values and the pulse values of a measurement. 2.4 Education of database programming finding out how we can characterize the morphology of a heart beat using only a few features. In the education field you can also find intelligent data processing problems. If the teachers use an active learning method, they have to verify every single solution of the students. But a student will give not only one solution to a task, which means that the teacher can have a lot of duties. A software application can support the duties of the teacher who uses an active learning method in organizing the students, the tasks and the solutions, moreover, in following the performance of the students. In the case of education of programming the application can also help in the syntactic verification and it may also help in a kind of semantic verification. I used active learning method during the Advanced Database Management Systems 1 course at the Faculty of Informatics, University of Debrecen. It is one of the subjects related to the database systems for Software Engineering BSc students. The students learn advanced SQL and PL/SQL in Oracle environment. The course consists of a 100 minute lecture and 100 minute laboratory practice per week. In the lecture the students get acquainted with the features of the Oracle database management system (DBMS). In the laboratory they practice the new material which they have learnt in the lecture. The "learning by doing" or active learning method is well-known and applied in many fields in education. It works also in the education of computer science. Gogoulou et al. (2009) used a software application for exploratory and collaborative learning in the education of programming. Drake (2012) deals with experimental learning, but he points out that the active learning is not proper for every educational situation. In the area of database systems Ramakrishna (2000) describes an experimental education survey of the undergraduate education. His results show that his students prefer the experimental learning over the traditional tutorials. Moore et al. (2002) describe a relational database management system course at Texas A & M University Corpus Christi that uses experimental learning. They receive a very good feedback from the students participating. Mason (2013) also presents experimental learning for teaching of database administration and software development at Regis University. His students indicated that the course was a successful experience that helped them to fine tune their technical skills and to develop new soft skills. To support the active learning method in the subject I used a software application. Statement D { Active learning method for database programming: I applied the "learning by doing" or active learning method in the education of advanced knowledge of database systems in Software Engineering BSc program in Hungary. To support the active learning method we developed a software system which helps administer the solutions, automatically verifies the syntax of them and helps the teacher to evaluate them. The laboratory results of the students are better if the teacher uses the active learning method, moreover, the results of voluntary survey show us that students like the active learning method and they would like it at other subjects, too. (Vagner, 2014), (Vagner, 2015) The first goal of the active learning method is to enable the students to use the PL/SQL and SQL as a skill, namely they will get a practical competence which can be immediately used in business. I as a teacher can rely on the previous programming and database knowledge of the students. In the lecture, the students get to know the material then they independently practice it in the laboratory. They get feedback for all their activities from the teacher. The software system administrates the tasks given to the students and the solutions made by them, it helps both the teacher and the students to follow to performance of the students, and it checks whether the syntax of an uploaded solution is correct or not. I summarized the results of three semesters when efficiently analyze mass data. The recent information technology has developed various techniques which can make the diagnosis faster. (Sornmo and Laguna, 2005) The Labtech Ltd. offers solutions for cardiologists. It possesses an information system named Cardiospy, which is used by many hospitals in Hungary and other countries. Most of its modules process medical signals. It has many functions which help recognize and manage cardiovascular illnesses (Labtech, 2015). I used the active learning method. In a year, I compared the active learning method with the traditional method. I asked the students in a voluntary survey about the active learning method. On the software, I worked together with Jozsef Kanyasi, who was one of my students. The idea, the design and the model of the software was mine and I implemented most part of its database side.

Pedcath IMPACT

Report from The International Society for Nomenclature of Paediatric and Congenital Heart Disease: cardiovascular catheterisation for congenital and paediatric cardiac disease Lisa Bergersen · Harvard Medical School Allen Dale Everett  Jorge Manuel Giroud Jeffrey Phillip Jacobs Abstract Interventional cardiology for paediatric and congenital cardiac disease is a relatively young and rapidly evolving field. As the profession begins to establish multi-institutional databases, a universal system of nomenclature is necessary for the field of interventional cardiology for paediatric and congenital cardiac disease. The purpose of this paper is to present the results of the efforts of The International Society for Nomenclature of Paediatric and Congenital Heart Disease to establish a system of nomenclature for cardiovascular catheterisation for congenital and paediatric cardiac disease, focusing both on procedural nomenclature and on the nomenclature of complications associated with interventional cardiology. This system of nomenclature for cardiovascular catheterisation for congenital and paediatric cardiac disease is a component of The International Paediatric and Congenital Cardiac Code. This manuscript is the first part of a two-part series. Part 1 will cover the procedural nomenclature associated with interventional cardiology as treatment for paediatric and congenital cardiac disease. This procedural nomenclature of The International Paediatric and Congenital Cardiac Code will be used in the IMPACT Registry™ (Pedcath) (IMproving Pediatric and Adult Congenital Treatment) of the National Cardiovascular Data Registry® of The American College of Cardiology. Part 2 will cover the nomenclature of complications associated with interventional cardiology as treatment for paediatric and congenital cardiac disease. Cardiology in the Young (2011), 21, 252–259