A Generic System-Level Framework for Self-Serve Health Monitoring System through Internet of Things (IoT).

Sensor data are traveling from sensors to a remote server, data is analyzed remotely in a distributed manner, and health status of a user is presented in real-time. This paper presents a generic system-level framework for a self-served health monitoring system through the Internet of Things (IoT) to facilities an efficient sensor data management.

ECG Artifact Removal from Surface EMG Signal Using an Automated Method Based on Wavelet-ICA.

This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact components from the original EMG signal. Components that correspond to the ECG artifact are then identified by an automated detection algorithm and are subsequently removed using a conventional high pass filter. Finally, the results of the proposed method are compared with wavelet transform, ICA, adaptive filter and empirical mode decomposition-ICA methods. The automated artifact removal method proposed in this study successfully removes the ECG artifacts from EMG signals with a signal to noise ratio value of 9.38 while keeping the distortion of original EMG to a minimum.

Noise Reduction for a MEMS-Gyroscope-Based Head Mouse.

In this paper, four different signal processing algorithms which can be applied to reduce the noise from a MEMS-gyroscope-based computer head mouse are presented. MEMS-gyroscopes are small, light, cheap and widely used in many electrical products. MultiPos, a MEMS-gyroscope-based computer head mouse system was designed for persons with movement disorders. Noise such as physiological tremor and electrical noise is a common problem for the MultiPos system. In this study four different signal processing algorithms were applied and evaluated by simulation in MATLAB and implementation in a dsPIC, with aim to minimize the noise in MultiPos. The algorithms were low-pass filter, Least Mean Square (LMS) algorithm, Kalman filter and Weighted Fourier Linear Combiner (WFLC) algorithm. Comparisons and system tests show that these signal processing algorithms can be used to improve the MultiPos system. The WFLC algorithm was found the best method for noise reduction in the application of a MEMS-gyroscope-based head mouse.

What characteristics of the gamers' profile should be taken into account in player-centred game design?

In this paper, we introduce the theory of trait Emotional Intelligence ('trait EI') as a personality theory that could assist in exemplifying the gamers' profile and contribute to the design of player-center game experiences. Data from two studies (a game-specific and a game-general one) led to a number of player-centered playability principles that could inform the design of adaptable games and games targeting specific gaming audiences. The gamers' emotional characteristics were found to be of prominent importance to the design of good games.

Assessing Greek Public Hospitals' Websites

Following a previous (2011) survey, this study assesses the web pages of Greek public hospitals according to specific criteria, which are included in the same web page evaluation model. Our purpose is to demonstrate the evolution of hospitals' web pages and document e-health applications trends. Using descriptive methods we found that public hospitals have made significant steps towards establishing and improving their web presence but there is still a lot of work that needs to be carried out in order to take advantage of the benefits of new technologies in the e-health ecosystem.

Exploitation of Medical Crisp Database for Fuzzy Diagnostic Decision Support Systems

There are several types of Diagnostic Decision Support Systems (DDSS) but all move towards a common direction: provide assistance to the doctors/clinicians to make the right diagnosis for a specific patient, minimizing as much as possible the needed time for this. In doing so, some DDSS systems exploit existing crisp medical databases while others take an advantage of human knowledge and experience, by building fuzzy medical databases from scratch. It would be of interest though, as well as time saving, to combine these two together and examine how one can actually use an existing crisp medical dataset to transform it into a new fuzzy medical database with parameters being expressed and defined based on the clinicians' way of thinking. A methodology implementing this task is proposed in this paper accompanied by the results of its application on a real crisp medical database.

Design for Assistive Technology: a Preliminary Study

Informatics competencies in nursing management

This study aimed to identify in scientific literature the informatics competencies required from the nurses to make decision in management process. Through a scoping review, literature databases were searched to find articles published in Portuguese, English, or Spanish, until July 2013. 188 articles were found, and seven were included in this study, published between 1994 and 2011. The studies were written in English (5; 71%), in USA (5; 71%), using experience reports or literature review designs (5; 71%). The informatics competences were categorized according the Technology Informatics Guiding Education Reform (TIGER). The findings highlight gaps in informatics competence to make decisions in the management process--essentially in information management competence.

A Comparative Study of Bayes Net, Naive Bayes and Averaged One-Dependence Estimators for Osteoporosis Analysis

This paper presents an evaluation of the accuracy of the Bayesian classifiers: Bayes Net, Naive Bayes and Averaged One-Dependence Estimator, to support diagnoses of osteopenia and osteoporosis. All classifiers showed good results, thus, given data, it is possible to produce a reasonably accurate estimate of the diagnosis.

Distributed Parallel Computing in Data Analysis of Osteoporosis

This research aimed to compare the performance of two models of load balancing (Proportional and Autotuned algorithms) of the JPPF platform in the processing of data mining from a database with osteoporosis and osteopenia. When performing the analysis of execution times, it was observed that the Proportional algorithm performed better in all cases.