Human-Computer Interaction and Presence in Virtual Reality

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Chapter 2 In a similar vein, the generalizability of a method is hard to prove outright and is also done by argument alone. 2.2 Presence model In order to design a system that is effective, we will need an understanding of the way in which the HCI affects the effectiveness of the therapy. The simplest way to do this would be to manipulate one HCI variable at a time and observe its effect in real therapy. However, this would be extremely time-consuming and require many therapists and patients before significant results are obtained. We therefore need to divide the problem into smaller problems, using intermediary concepts such as presence and fear. This way we can determine the overall effect of HCI on effectiveness by determining the relationships between these intermediary concepts, which are much easier to investigate and at the same time provide us with a more thorough understanding of the underlying process. We can furthermore make use of the considerable amount of research that has already been performed in this area. Review of this research and the formulation of such a model are described in detail in chapter 4. 2.2.1 Evaluation Since this will be the first of such a model attempting to explain the effectiveness of therapy in terms of the HCI, it is irrelevant to ask whether it is an improvement. We will only have to show that it works. This can be tested by showing that predictions made using this model about the UI for VRET are correct. Here, the hypothetico-deductive method is appropriate: we can deduce hypotheses from the model and test these hypotheses using empirical data. These hypotheses should apply to the case of VRET. The HCI in VR includes navigation and object selection and manipulation. The interaction most generic for all phobias and other applications than VRET as well is navigation. We will therefore focus on the patient navigation, which can be divided into wayfinding and locomotion. Wayfinding is the cognitive process of determining a path, locomotion is the control of the viewpoint. In this dissertation, wayfinding techniques will not be discussed, since the virtual environments used are relatively simple, and we assume that wayfinding has no therapeutic value. Thus, the key HCI issues concerning the patient interaction in VRET are related to patient locomotion: should the therapist or the patient have control over the locomotion of the patient through the VE? If the patient is allowed control over the locomotion, which interaction technique provides the highest effectiveness? The presence model that will be presented in chapter 4 suggests that presence is essential to provide the patient with fear, and that fear is essential for effective therapy. We can test the effect of the different choices related to patient locomotion with regard to presence and fear. First of all, we can test the effect of the choice of patient control versus therapist control: Hypothesis 1: Locomotion controlled by the patient will increase the patient’s sense of presence. Hypothesis 2: Locomotion controlled by the patient will increase the fear a phobic user can experience. 10
Research approach Second, we can test whether, in the case of patient control, there are any differences between the various locomotion techniques. For presence and fear, it seems most likely that a more natural locomotion technique will lead to higher presence and thus to more fear. A more natural locomotion technique is one with which the user is closely familiar. Therefore, different locomotion techniques will be natural to different to users. However, the locomotion technique most common to all users is that which we use in everyday reality: walking with our own two feet and looking around by turning our head and body. Taking this notion of natural in consideration, we can formulate the hypotheses: Hypothesis 3: A more natural locomotion technique for the patient will increase the presence a user experiences Hypothesis 4: A more natural locomotion technique for the patient will increase the fear a phobic user can experience. 2.3 Patient and therapist UI The patient and therapist each have their own UI to interact with the system. The designs for the patient and therapist UI describe what the HCI should look like for both users, the functionality offered by the system and the way in which the user can access this functionality. They can said to be instantiations of the design method combined with the presence model since they will be built using these two research products. 2.3.1 Evaluation To determine whether these user interfaces work, we will need to understand their consequences for the usability and effectiveness of the system. The effectiveness of the system could be evaluated by determining the effectiveness of the entire treatment using the VR system, but as stated in the previous paragraphs on the presence model, this would be extremely complicated and time consuming. We will therefore use intermediary concepts such as presence and fear, and evaluate whether the user interfaces are effective in generating a sense of presence and adequate fear levels in the patients. We then need to show that presence and fear contribute to higher treatment effectiveness. To evaluate the usability of the user interfaces, we need to go into the domain of software usability as already introduced in the previous chapter. There, we used the ISO definition of usability (ISO 9241): The effectiveness, efficiency, and satisfaction with which specified users achieve specified goals in particular environments. Effectiveness is defined as the accuracy and completeness with which users achieve specified tasks and efficiency is the resources expended in relation to the accuracy and completeness with which users achieve goals. Satisfaction is a subjective measure and concerns the comfort and acceptability of use by end users. (Nielsen, 1993) uses a definition that is specified in elements that are more specific, as shown in table 2.1. 11
Page 1: Human-Computer Interaction and Pres
Page 4 and 5: Dit proefschrift is goedgekeurd doo
Page 6 and 7: 3.3.3 State information............
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Page 11 and 12: 1 Introduction Human Computer Inter
Page 13 and 14: Introduction do to other humans. In
Page 15 and 16: Introduction the patient can slowly
Page 17 and 18: 2 Research approach Computer scienc
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Page 25 and 26: Research approach interface that do
Page 27 and 28: 3 Analysis As stated in the previou
Page 29 and 30: Analysis 3.1.3 Agoraphobia In an ex
Page 31 and 32: Analysis works (Benyon & Imaz, 1999
Page 33 and 34: Analysis actors. Besides this, Cont
Page 35 and 36: Analysis 1979; Habermas, 1981; Diet
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Page 39 and 40: Analysis 3.3.3 State information No
Page 41 and 42: Analysis Unfortunately, this will m
Page 43 and 44: Analysis Name system URL website Ph
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Page 55 and 56: Goals Procedures Sound T.Controls T
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Page 65 and 66: 4 Presence The research described i
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Presence (Regenbrecht et al., 1998)
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Presence Sometimes these questionna
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Presence al., 1999a) state that the
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Presence colleagues did find a marg
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Presence The Igroup Presence Questi
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Presence Presence Finding (se = Exp
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Presence Interactivity Steuer defin
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Presence (Slater & Usoh, 1993) use
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Presence because the situations tha
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Presence usability are focused on t
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Chapter 5 locomotion technique suit
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Chapter 5 a base transmitter that g
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Chapter 5 3. Gaze-directed: This te
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Chapter 5 content of labels distrib
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Chapter 5 Measures Prior to the exp
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Chapter 5 Unstandardized Coefficien
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Chapter 5 phobia that often involve
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Chapter 5 subjects were all diagnos
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Chapter 5 VE does show a significan
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Chapter 5 possible explanation coul
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Chapter 5 Large drop Large drop A2
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Chapter 5 5.5.2 Results Subjects Mi
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Chapter 5 the SUD scores in the dif
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Chapter 5 The third experiment clea
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6 Therapist's user interface The UI
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6.2.1 SUDs recording During therapy
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Therapist’s user interface Figure
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Therapist’s user interface The st
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Therapist’s user interface The 2D
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Therapist’s user interface Heartr
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Therapist’s user interface • To
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Therapist’s user interface elemen
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7 Conclusions In this dissertation
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7.1.2 Determining the patient's fea
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Conclusions patient control allowed
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Conclusions Guideline 5: A tool for
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References Alcaniz , M. Banos , R.M
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References Dietz, J.L.G., Widdersho
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References Hodges, L., Rothbaum, B.
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References Lombard, M., Ditton, T.(
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References Reeves, B., Nass, C. (19
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Slater, M. (1999). Measuring Presen
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References van Welie, M. (2001) Tas
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UED User Environment Design VE Virt
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Appendix A Complaints and wishes 'F
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Appendix A A.4 Experiment 3 Compute
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Appendix A 3. Were you able to see
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Appendix A 28. 'If you had to choos
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Appendix B Element: Instruct patien
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Appendix B Element: Inform patient
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Appendix B Element: Listen for resp
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De TA methode is getoetst door deze
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Curriculum vitae Martijn Schuemie w
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2000-1 Frank Niessink (VU) Perspect
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2002-09 Willem-Jan van den Heuvel(K
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