Inês Oliveira

Relevance of EEG input signals in the augmented human reader

This paper studies the discrimination of electroencephalographic (EEG) signals based in their capacity to identify silent attentive visual reading activities versus non reading states. The use of physiological signals is growing in the design of interactive systems due to their relevance in the improvement of the coupling between user states and application behavior. Reading is pervasive in visual user interfaces. In previous work, we integrated EEG signals in prototypical applications, designed to analyze reading tasks. This work searches for signals that are most relevant for reading detection procedures. More specifically, this study determines which features, input signals, and frequency bands are more significant for discrimination between reading and non-reading classes. This optimization is critical for an efficient and real time implementation of EEG processing software components, a basic requirement for the future applications. We use probabilistic similarity metrics, independent of the classification algorithm. All analyses are performed after determining the power spectrum density of delta, theta, alpha, beta and gamma rhythms. The results about the relevance of the input signals are validated with functional neurosciences knowledge. The experiences have been performed in a conventional HCI lab, with non clinical EEG equipment and setup. This is an explicit and voluntary condition. We anticipate that future mobile and wireless EEG capture devices will allow this work to be generalized to common applications.

Development of a biosignals framework for usability analysis

The understanding of human physical and physiological signals and expressions, together with a growing processing and control capacity allows for new approaches in interactive systems design. In this poster, we introduce constitutive elements and steps towards the integration of EEG (Electroencephalography) signals in a system to analyze reading activities. The poster presents system design choices that include the software architecture and the feature extraction and classification techniques used in the first prototypes.

Designing Computer Support for Content Analysis: A Situated Use of Video Parsing and Analysis Techniques

This paper presents the use of video parsing and video analysis techniques to attain a radical change in Content Analysis processes. Content Analysis provides frameworks for a better understanding of information, mass media information in particular. The goals of the work presented in this paper are to assess the feasibility of designing Content Analysis processes under much faster and much less manpowered conditions, to prove the power and usefulness of some video parsing and analysis techniques under current inexpensive and widely available software and hardware platforms, and to emphasize that the characteristics of a given situated use of a technological artifact often provide radical simplifications to the system requirements, and make it feasible today.

Practical Neurophysiological Analysis of Readability as a Usability Dimension

This paper discusses opportunities and feasibility of integrating neurophysiologic analysis methods, based on electroencephalography (EEG), in the current landscape of usability evaluation methods. The rapid evolution and growing availability of low-cost, easier to use devices and the accumulated knowledge in feature extraction and processing algorithms allow us to foresee the practicality of this integration.

Experiences in reading detection with EEG signals

This short paper introduces the use of neurophysiological signals, electroencephalogram (EEG), as a technique for reading detection. Reading detection is a focused problem, yet with multiple facets and application relevance. The paper refers to the system architecture that supports the reading detection experiments, describes the sample tools designed for the experiment and discusses the results. The experiences demonstrate that the approach to reading detection is feasible. In addition, they highlight the technical and usability limitations of the approach, which are expected to be reduced both through system tuning and optimization, and through the technological evolution of the peripheral devices.

WeatherDigest: an experiment in media conversion

This paper describes an experimental system (WeatherDigest) for automatic conversion of TV weather forecasts to HTML documents. This application is presented as an example of a larger system dealing with media understanding, representation and dissemination. An object model for media representation and processing is described and WeatherDigest is presented in terms of this object model. The concepts explored in WeatherDigest are then generalized to a repository of multimedia information (media server). This server can handle requests from clients with different requirements allowing to retrieve the same information in multiple formats.