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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3345))

Abstract

Everybody agrees that user tasks and preferences should play a central role in the design and development of applications oriented to non-computer experts. Nevertheless, even biomedical applications are sometimes developed in a relative vacuum from the real needs of end-users and environments where they are supposed to be used.

To provide a clinician with an intuitive environment to solve a target class of problems, a biomedical application has to be built in such a way that a user can exploit modern technologies without specialized knowledge of underlying hardware and software [18]. Unfortunately, in reality the situation is different. Many developers do not take into account the fact that their potential users are people, who are mostly inexperienced computer users, and as a result they need intuitive interaction capabilities and a relevant feedback adapted to their knowledge and skills.

User comfort is very important for the success of any software application [13]. But very often we forget that usability problems may arise not only from an ‘uncomfortable’ graphical user interface (GUI), but also from a projection modality chosen incorrectly for deploying an interactive environment [16].

Existing projection modalities have not been sufficiently investigated yet in respect to usability factors. Meanwhile, the selection of an appropriate projection modality in accordance with the user’s tasks, preferences and personal features might help in building a motivated environment for biomedical purposes. In this chapter we summarize our recent findings related to this research and introduce a new concept of multi-modal interaction based on the combination of virtual reality (VR) and desktop projection modalities within the same system. For the case study of the research we used a biomedical application simulating vascular reconstruction [2,22].

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Zudilova, E.V., Sloot, P.M.A. (2005). Multi-modal Interaction in Biomedicine. In: Cai, Y. (eds) Ambient Intelligence for Scientific Discovery. Lecture Notes in Computer Science(), vol 3345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32263-4_9

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  • DOI: https://doi.org/10.1007/978-3-540-32263-4_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24466-0

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