THE DEVELOPMENT AND VALIDATION OF A NEW SMARTPHONE BASED NON-VISUAL SPATIAL INTERFACE FOR LEARNING INDOOR LAYOUTS

Most maps are visual in nature and not accessible by visually impaired users. Although there is significant research on accessible maps based on audio and tactile cues, these non-visual maps have various shortcomings. For instance, most of these map displays are non-refreshable and require substantial time, cost, and effort to create and update. Available refreshable displays are very expensive which make them cost exclusive, and most of these displays are bulky and cumbersome to carry around. To overcome these shortcomings in accessible maps, this thesis research work has designed and tested a novel non-visual interface for conveying indoor spatial information layouts using vibro-tactile and audio cues called “Vibro-Audio Map”. This interface is implemented on highly portable, comparably inexpensive, off-the-shelf smartphones.

Non-visual map panning presents a unique set of challenges which includes both cognitive and interface level challenges. An easy-to-use map panning method called “Button-based-Pan” method was developed as part of this thesis research in order to facilitate non-visual exploration of large maps. This panning method though easy and intuitive, still presents the map in a manner that requires high cognitive demands to process by a non-visual user. One solution to this problem, investigated in this thesis, is to reduce the amount of map panning required using a device by extending its effective screen space. This requirement led to the “Extended-Display” concept where the smartphone becomes the information window (or an information lens) to a virtual map projected on a flat table surface. This experimental work presents a functional proof-of-concept of an Extended-Display using a camera based system, and demonstrates its efficacy in displaying Vibro-Audio Maps.

The thesis then presents experimental results, which compare indoor layout learning performance among three interface conditions. These three conditions are: (1) Vibro-Audio Map with pan mode, (2) Vibro-Audio Map with Extended-Display mode, and (3) Hardcopy tactile map with audio information. The results provide clear evidence that the Vibro-Audio Map is equivalent in spatial learning performance when compared against the traditional hardcopy tactile map condition, which is currently the most accepted mode of non-visual map learning.