Ivan Chorbev

Virtual communities for diabetes chronic disease healthcare

Diabetes is classified as the worlds fastest-growing chronic illness that affects millions of people. It is a very serious disease, but the bright side is that it is treatable and can be managed. Proper education in this view is necessary to achieve essential control and prevent the aggregation of this chronic sickness. We have developed a healthcare social network that provides methods for distance learning; opportunities for creation of virtual self-help groups where patients can get information and establish interactions among each other in order to exchange important healthcare-related information; discussion forums; patient-to-healthcare specialist communication. The mission of our virtual community is to increase the independence of people with diabetes, self-management, empower them to take care of themselves, make their everyday activities easier, enrich their medical knowledge, and improve their health condition, make them more productive, and improve their communication with other patients with similar diagnoses. The ultimate goal is to enhance the quality of their life.

Web Based Medical Expert System with a Self Training Heuristic Rule Induction Algorithm

This paper presents a web based medical expert system that performs self training using a heuristic rule induction algorithm. The data inserted by medical personnel while using the expert system is subsequently used for additional learning. The system is trained using a hybrid heuristic algorithm for induction of classification rules that we previously developed. The SA Tabu Miner algorithm (Simulated Annealing and Tabu Search based Data Miner) is inspired by both research on heuristic optimization algorithms and rule induction data mining concepts and principles. In this paper we compare the performance of SA Tabu Miner with other rule induction algorithms for classification on public domain data sets.

Wireless telemedicine services as part of an integrated system for e-medicine

This paper presents an overview of the wireless telemedicine components of an integrated system for e-medicine that we propose and implement in the Republic of Macedonia. The introduction of new wireless broadband technologies enabled creation of telemedicine services previously only possible via cable connections. WiMAX and Wi-Fi are the wireless technologies used to implement our telemedicine functionalities. They are shortly described and a number of proposed and provided services are explained. Advanced web programming technologies have been extensively used in implementation of the services. Guidelines are given for further development and implementation. The experience gained draws conclusions that can be used in areas or countries with similar natural or economical conditions.

Improving Activity Recognition Accuracy in Ambient-Assisted Living Systems by Automated Feature Engineering

Ambient-assisted living (AAL) is promising to become a supplement of the current care models, providing enhanced living experience to people within context-aware homes and smart environments. Activity recognition based on sensory data in AAL systems is an important task because 1) it can be used for estimation of levels of physical activity, 2) it can lead to detecting changes of daily patterns that may indicate an emerging medical condition, or 3) it can be used for detection of accidents and emergencies. To be accepted, AAL systems must be affordable while providing reliable performance. These two factors hugely depend on optimizing the number of utilized sensors and extracting robust features from them. This paper proposes a generic feature engineering method for selecting robust features from a variety of sensors, which can be used for generating reliable classification models. From the originally recorded time series and some newly generated time series [i.e., magnitudes, first derivatives, delta series, and fast Fourier transformation (FFT)-based series], a variety of time and frequency domain features are extracted. Then, using two-phase feature selection, the number of generated features is greatly reduced. Finally, different classification models are trained and evaluated on an independent test set. The proposed method was evaluated on five publicly available data sets, and on all of them, it yielded better accuracy than when using hand-tailored features. The benefits of the proposed systematic feature engineering method are quickly discovering good feature sets for any given task than manually finding ones suitable for a particular task, selecting a small feature set that outperforms manually determined features in both execution time and accuracy, and identification of relevant sensor types and body locations automatically. Ultimately, the proposed method could reduce the cost of AAL systems by facilitating execution of algorithms on devices with limited resources and by using as few sensors as possible.

WiMAX supported telemedicine as part of an integrated system for e-medicine

This paper presents an overview of the wireless telemedicine components of an integrated system for e-medicine that we propose and implement in the Republic of Macedonia. A short introduction to telemedicine and its evolution is presented. The new wireless broadband technologies enabled creation of telemedicine services previously only possible via cable connections. The novel wireless technologies enable provision of advanced medical services to rural areas unreachable by cable connections. WiMAX and Wi-Fi are the technologies used to implement our telemedicine functionalities. They are shortly described and a number of proposed and provided services are explained. Guidelines are given for further development and implementation. The experience gained draws conclusions that can be used in areas or countries with similar natural or economical conditions.

Automated Ambient Open Platform for Enhanced Living Environment

The aim of this paper is to present an idea of open platform for Enhanced Living Environment that will allow flexible and reliable use of the cloud-computing, sensor, mobile, local and body area networks for highly customized services and applications. The platform architecture consists of sensors working on IEEE 802.15.4, ZigBee, EnOcean standards, Ethernet, GSM, 3G, 4G, 5G gateways to the cloud, and peer port application at application layer. The personal enhanced living environment consists of body area and home automation network. They are key factors for patient’s comfortable living outside hospitals. Home, car, working place, park automation support the mobility, social integration, possibility of the patients to manage everyday tasks. Experiments carried out using sensors and holter prove the vitality of the solution partially. The platform is capable of working independently from the network connectivity, uses multi-homing, is open to migration to new technologies

Building a wireless telemedicine network within a WiMax based networking infrastructure

In this paper we propose an implementation of a WiMAX-based integrated system for e-medicine in the Republic of Macedonia. We present developed telemedicine multimedia services and their related QoS. We also present the problems and challenges for using a public wireless IP network for setting up the system.

Video Content-Based Retrieval System

At present, multimedia databases are used in many application areas and their sizes become larger and larger. Therefore, an efficient multimedia management system is required. This kind of system has various areas of application such as video-on-demand and digital libraries. The importance of video-content-based retrieval systems guided our research toward implementation of a Video-Content-based Retrieval System. The system is fully implemented in Java and is easily upgradable. Many techniques for feature extraction and selection are implemented in the system.

Cloud Based Assistive Technologies and Smart Living Environment System

This paper describes a cloud based architecture for processing data and providing services for smart living environments and support for assistive technologies. Based on scalable cloud technologies and optimized software architectures, it provides infrastructure for an extendible set of various functionalities. The paper describes the core processing module along with several related proof-of-concept services. Several use case scenarios are presented including a mobile app voice navigation tool for the blind, text to hand sign speech video sequencing tool for the deaf, image processing tool for a smart home, etc. Details are presented about the software development tools used and their integration in a functional multiplatform application. Guides for future works and extension of the system are discussed.

An overview of a constraint solving engine with multiple optimization algorithms

This article is concerned with the classes of the Constraint Solving Engine and a Constraint Programming Library for problems that can be defined as Constraint Satisfaction Problems. The theoretical and mathematical foundations of our ideas and the problem solving process are explained. Among the first problems that were solved was the Traveling Salesman Problem (TSP). The results and conclusions for TSP solution are given in the closing part of the paper.