Comparing interaction techniques for serious games through brain-computer interfaces:a user perception evaluation study

This paper examines the application of commercial and non-invasive electroencephalography (EEG)-based brain-computer (BCIs) interfaces with serious games. Two different EEG-based BCI devices were used to fully control the same serious game. The first device (NeuroSky MindSet) uses only a single dry electrode and requires no calibration. The second device (Emotiv EPOC) uses 14 wet sensors requiring additional training of a classifier. User testing was performed on both devices with sixty-two participants measuring the player experience as well as key aspects of serious games, primarily learnability, satisfaction, performance and effort. Recorded feedback indicates that the current state of BCIs can be used in the future as alternative game interfaces after familiarisation and in some cases calibration. Comparative analysis showed significant differences between the two devices. The first device provides more satisfaction to the players whereas the second device is more effective in terms of adaptation and interaction with the serious game.

User involvement in UK cancer services:bridging the policy gap

Recent UK government initiatives aim to increase user involvement in the National Health Service (NHS) in two ways: by encouraging service users to take an active role in making decisions about their own care; and by establishing opportunities for wider public participation in service development. The purpose of this study was to examine how UK cancer service users understand and relate to the concept of user involvement. The data were collected through in-depth interviews, which were analysed for content according to the principles of grounded theory. The results highlight the role of information and communication in effective user involvement. Perhaps more importantly, this study suggests that the concept of user involvement is unclear to many cancer service users. This paper argues the need for increased awareness and understanding of what user involvement is and how it can work.

A four-factor user interaction model for content-based image retrieval

In order to bridge the “Semantic gap”, a number of relevance feedback (RF) mechanisms have been applied to content-based image retrieval (CBIR). However current RF techniques in most existing CBIR systems still lack satisfactory user interaction although some work has been done to improve the interaction as well as the search accuracy. In this paper, we propose a four-factor user interaction model and investigate its effects on CBIR by an empirical evaluation. Whilst the model was developed for our research purposes, we believe the model could be adapted to any content-based search system.