Wundows複合機能システム

Wundows複合機能システム

Wednesday, July 26, 2017

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.

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