User Comments on Four Cases:Besides these scores, we also recorded users’ comments. For case A, i.e. the finger input with the EDI, four participants tired of lifting their arms after operating for a while, which led them to interact unsteadily with their fingers. Two participants said that the fixed position was efficient and convenient for the interaction. Furthermore, two participants commented on a physical chain reaction effect: when moving their arms and fingers, this resulted in a tiny movement of the camera fixed on their head. For case B, one person said that the frame of the mask made it easy to choose and select items, while another user could not work properly with the frame’s marker angle. Two people said their arm got tired. For case C, more than half of the participants commented on the long time required for lifting their arms and unsteady fingers. They thought it was not easy to hold the interface steadily in their hands. Two participants experienced the chain reaction effect. For case D, four participants found that the search for the right page to interact felt less easy when there were more pages in the booklet, and that returning to the index each time was not convenient. Only one participant mentioned feeling the chain reaction. One user preferred the marker interaction for a faster and more sensitive interactive experience. For the devices, six participants felt the screen was small to read, provoking a feeling of tiredness.
The results of our exploring whether the three input techniques are easy to learn or not, is that that the finger, the mask and the page input techniques are all easy to learn. The average scores for easiness of learning and utilization with the three input techniques are all more than 3. However, not all learning has raised user satisfaction; after learning, the scores of true tasks in Cases A, B and D are higher than toy learning scores. Besides, easiness of learning varies slightly in the four cases. Out of these cases, interaction in Case B has the best score, which indicates it was the easiest and most convenient for learning compared with the others. From users’ comments, we found that with EDI, more people reported a tired arm in Case A than in Case B. We thought that the mask stick played the role of an extended arm, leaving the arm in a more relaxed state and reducing the effect of tiredness.
Furthermore, the answer to the second question stated above is that the sequence of performance from best to worst of the four cases is Case B, Case A, Case C, and Case D. Case B has the best overall performance, with the shortest interaction time, the shortest access time, no locomotion error, and the best satisfaction. Compared with case A, B has fewer participants reporting a tired arm because the band with mask is more comfortable than lifting their hands. Case A performs better than case C; they have virtually the same interaction time and access time except that A has a better score of satisfaction and fewer participants reporting a tired arm due to the fixed and stable interface. In turn, case C performs better than case D due to its shorter interaction time, shorter access time, fewer interaction errors, and better satisfaction score. Case D is most influenced by overall locomotion errors. From the users’ comments, we found that the more pages there are, the harder the selection action is, even for the interaction time of tasks T1 and T2. The fact of searching for pages via a return to the index means that the input technique in case D leads users to an unsteady interaction state. In a word, EDI performs better than EII, and the performance of input techniques from best to worst is mask, finger and page. The best performance is awarded to the mask input technique with EDI.
This study also showed us the influence of Fitts’s law on innovative wearable interfaces, which could answer our third question. From the ANOVA test, we found that the variable layout has no statistical significant influence on the interaction time of Cases A, B and D. For Case D, the interface does not have the traditional layout, and it is thus obvious that Fitts’s law does not work on the interface in this case. In Cases A and B, the interaction time of T1 is shorter than that of T2 because pointing in T2 involves a longer distance than in T1. In figure 19, we can see that the blue points are related to task T1, while the red points are related to T2. The hand is usually located in the horizontal middle of the interface: it is quicker to reach the blue points than the red points (The transparent red dot cycle and the bottom-right red point illustrate the same distance as blue points). Besides, the variable layout has a statistical significant influence on the interaction time of Case C. Compared with EDI in Cases A and B, the locomotion amplifies the effect of Fitts’s law with EII in Case C.
Fig. 19The layout of RTMA.
Finally, to reduce the locomotion errors and augment user experience in the wearable system with EDI and EII, we propose two solutions.
The first consists in increasing paper hardness and decreasing paper size. Users hold the paper with different degrees of strength that can result in its bending, thus reducing webcam recognition and leading to the same interaction problem as the locomotion errors. Paper hardness can compensate for this effect: we can choose cardboard as the paper interactive surface of the EII. Moreover, if we reduce paper size, the possibility of carelessly leaving part of the paper out of the webcam range will increase. The physical paper interface has a low multiplexed ability: the selected items are physical and cannot be changed dynamically. If we reduce the space and size of the paper, the number of interactive items in the paper-based interface also decreases.
To provide more interactive items and retain the link between information and physical indications, we propose another solution, namely the physical and digital mixed interface, which has been described in the continuum for EDI and EII in sub-section 3.4. With the aim of providing more information for the mixed interface and to add interactive items, we remove the configuration of the small-size display attached with goggle, and adopt the pico-projector as the output device. The projection display can be an alternative method for providing a larger visual presentation without any external device support. In this way, the mixed interface (see Figure 20 (b)) offers more dynamic interactive choices compared with the paper-based interface (see Figure 20 (a)). Since we also found that raising hands at eye level became tiring after a certain time and that the chain reaction reduced interaction efficiency, we propose changing the position of the webcam from the forehead to the chest to lower hand raising and ensure stability. We will fix the webcam and pico-projector together on the light cardboard support, and choose the chest as the worn point for the mixed interface.
Fig. 20From paper-based interface (a) to physical-digital mixed interface (b).
Conclusion and Outlook
In this paper, we described our approach for exploring innovative user interfaces (In-Environment Interface, Environment Dependent Interface and Environment Independent Interface), enabling the user to access in-environment information and environment independent information freely. We also explained the concepts of EDI (Environment Dependent Interface) and EII (Environment Independent Interface), and our taxonomy of mobile user interfaces for EDI and EII. To realize EDI and EII, we proposed, designed and implemented the MobilePaperAccess system, which is a wearable camera-glasses system, including the configuration: a webcam, a small screen attached to a goggle, and a laptop as the calculating device. Through this system, users can interact with the paper-based interface using finger, mask and page input techniques. We organized an evaluation, and compared two interfaces (EDI and EII) and three input techniques (finger input, mask input and page input). The quantitative and qualitative results showed the easiness of learning when interacting with EDI and EII, the performance of the three input techniques with two interfaces, and the influence of layout on interaction time with wearable interfaces.
For future work, we plan to investigate the physical and digital mixed interface with the camera-projector device unit containing the webcam, pico-projector and a tablet, to perform the concepts of EDI and EII. Furthermore, more advanced input techniques of hand gestures such as the pinch gesture will be studied.
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