Geometrical Shapes Rendering on a Dot-Matrix Display
Using a dot-matrix display, it is possible to present geometrical shapes with different rendering methods: solid shapes, empty shapes, vibrating shapes, etc. An open question is then: which rendering method allows the fastest and most reliable recognition performances using touch? This paper presents results of a user study that we have conducted to address this question. Using a 60 * 60 dot-matrix display, we asked 40 participants to recognize 6 different geometrical shapes (square, circle, simple triangle, right triangle, diamond and cross) within the shortest possible time. Six different methods to render the shapes were tested depending on the rendering of shape’s outline and inside: static outline combined with static or vibrant or empty inside, and vibrating outline combined with static or vibrant or empty inside. The results show that squares, right triangles, and crosses are more quickly recognized than circles, diamonds, and simple triangles. Furthermore, the best rendering method is the one that combines static outline with empty inside.
KeywordsTouch Dot-matrix display Graphics Geometry
Blind people can have access to digital documents using specific software called “screen readers”. Screen readers can present in a linear way, either through speech synthesis or braille, the content of a document or elements of a graphical interface. However, access to graphics and other two-dimensional information is still severely limited for the blind. It is not easy for them to explore 2D structures such as mathematical formulas, maps, electronic circuit diagrams…) using a screen reader. The user is then faced with many problems such as disorientation and difficulty to memorize and to build a correct mental model.
The work presented in this paper is a first step of a larger project that aims at defining new ways for the blind to have access to electronic documents while preserving spatial layout of the document. The main idea of the project is to use a dot-matrix display to present the general spatial layout of the document. Each element of the document structure (title, paragraph, image, etc.) will be represented by a geometrical form that will reflect the size and the position of the element in the document. When the user explores this spatial layout, he/she will be able to access to the detailed content of the element that is currently under his/her fingers, through another modality such as speech synthesis or braille.
As a preliminary step, two questions should be addressed. First, which geometrical form should be used? Obviously, using rectangles is the first idea that comes in mind but is it possible to use other forms depending for instance on the information type? Second, which rendering method allows the best and faster recognition process?
2 Related Work
Different methods exist to translate graphical information into a tactile form to make it accessible to a blind person [2, 3]. 3D printing, collage, thermoforming and embossed paper  are great for educational purposes but they all have the same drawback: they produce static documents which prevents useful interactive operations such as zooming and scrolling. This leads to a drastic reduction of information density due to the limited resolution of the skin. Furthermore, their quality decreases with use and they require huge space to be stored.
Other devices that allow refreshable tactile display, exist. They can be classified into two main categories. The first category concerns the devices that allow a tactile exploration of a virtual large surface using a small tactile device. A typical example of such devices is the VTPlayer mouse [9, 10] that can be used as a classical mouse to explore a virtual surface while receiving tactile stimuli through the index finger thanks to its 4 * 4 Braille dots. The main advantage of this device is its low cost and portability. However, exploration is generally done using only one finger which leads to important time exploration before achieving recognition even of very simple shapes.
The second category concerns the devices that allow the tactile exploration of a large physical surface using several fingers of both hands [6, 7]. The surface is generally composed by a matrix of a high number of Braille dots which play the same role as pixels in screens. An example of such device is the dot-matrix display designed by Shimada et al.  which offers 32 × 48 Braille dots. The main drawback of this kind of devices is their cost.
In this paper, we present a study conducted using a device of this second category to identify the rendering features that allow the fastest and most reliable recognition of geometrical shapes. The protocol of this study was inspired by a study conducted by Levesque and Hayward  on a device of the first category (the STReSS2 device).
3 User Study
3.1 Experimental Conditions
Size of shapes.
In  the shapes were selected to fill a 2 or 3 cm square, leading to two different sizes: small and large. In our experiment, we used three different sizes: small, medium, and large. Our small and medium sizes correspond respectively to small and large sizes of Levesque’s study (2 and 3 cm). Our large size corresponds to a 4-cm bounding square. We added this larger size because the dot-matrix display has less resolution than the STReSS2 tactile display . In the STReSS2 device, the center-to-center distance between adjacent actuators is 1.2 × 1.4 mm and the actuators can deflect toward the left or right by 0.1 mm. In our dot-matrix display, the horizontal and vertical distances between the dots centers are the same and are equal to ~2.5 mm. The diameter of each dot is ~1 mm. So, we kept the same sizes as in  but added a supplementary (larger) one in case recognition performances would be affected by poorer resolution of the dot-matrix display.
Rendering of shapes.
Features of different renderings of shape.
Data were collected from 40 sighted subjects (31 men and 9 women), aged from 18 to 40 (M age = 23.7; SD age = 5.2). Many participants were people with a computer science background. All participants filled out a background questionnaire, which was used to gather information on personal statistics such as age and education level. Our sample was composed by 34 right-handers and 6 left-handers. All participants were naive with respect to the experimental setup and purpose of the experiment.
A training phase (~5 min) allowing each participant to become familiar with the geometrical shapes and the rendering methods used during the experiment. The six geometrical shapes are presented to the subject (who cannot see them thanks to a raised cover that hides the dot-matrix display) and then we ask him/her to name them. This step is complete when the subject is able to recognize the six shapes.
A phase of test where subjects were asked to recognize and to name shapes as fast as possible. This phase was decomposed in three continuous sessions (with a short break between them). The duration of the whole process (3 sessions) was under 1 h of time.
During the test, shapes varied according to the geometrical form, the size, and the rendering method. The order of the forms, sizes and rendering methods was randomly generated across participants. In all, each participant had to recognize 324 shapes (6 forms × 3 sizes × 6 rendering methods × 3 sessions).
For each shape, we recorded time to recognize it (in milliseconds) and participant’s answer. The participants used a button to display/hide the figure (which starts/stops the chronometer). The answers were given verbally. We developed a program to extract dependent variables from the log files that were generated during the test.
The results presented in this section are considered statistically significant when p < 0.05. Results are explicitly referred as a “trend” if p is between 0.05 and 0.1. We applied the Shapiro-Wilk test to verify that the variables succeed to satisfy normality assumptions. This is only verified for the recognition time variable. Recognition time was analyzed by means of ANOVAs2 with shape, shape size, and combination of rendering methods of shape’s outline and shape’s inside. ANOVAs were calculated using Statistica 9. Post hoc comparisons used the Student’s t-test. A Chi 2 test was performed for the recognition rate.
4.1 Recognition Rate
Recognition rate according the shape, the size, and the rendering.
4.2 Recognition Time
We observed a main effect of the size on the recognition time (F(2, 78) = 86,157; p < 0,001). Post hoc comparisons suggested that participants recognized more slowly small shapes (Mean = 6219,87; SD = 1996,642) than medium (Mean = 5300,23; SD = 63838,58) or large shapes (Mean = 5242,80; SD = 1674,63). There was no significant difference between the medium and large shapes.
Rendering method effect.
First, the forms are well recognized regardless of the geometrical shape, the size, or the rendering method.
Second the recognition times appears to be significantly better with crosses, squares, and right triangles than with circles, diamonds, and simple triangles. This result provides an interesting cue about the exploration strategy that participants followed. Some of them said that they start by looking for right angles in the shape which help them to rapidly identify the form (only 1 right angle for right triangles, 4 for squares and a lot (12) for crosses).
Third, the rendering methods that include vibrations seem to disrupt the participants even if there is no impact on the recognition rate. Participants spend more time to recognize the shapes rendered with vibrations than those rendered with static outline and empty or static insides. This result differs from Levesque and Hayward study  which obtained better identification for the shapes rendered with vibrations or dots than the ones rendered with grating. We think that this is due to the better resolution of the STReSS2 which allows a less “aggressive” perception of the vibrations.
Concerning the recognition time, Levesque and Hayward found that recognition was performed in 14,2 s on average, while in our study, recognition is performed in 5,6 s on average (2,5 × faster).
This article explored several haptic rendering methods to present geometrical shapes through the touch using several fingers on a large physical surface: the dot-matrix display. The presented study allowed us to collect 12960 recognition times and 12960 recognition scores (324 shapes × 40 participants). Results show that the best rendering method is the one that combines static outline with empty inside and that squares, right triangles, and crosses are more quickly recognized than circles, diamonds, and simple triangles. These results are interesting for our project concerning spatial access to documents by the blind.
The protocol of the presented study was inspired by a similar study conducted by Levesque and Hayward on a smaller device that allows exploring a virtual surface using only one finger: the STReSS2 device. The comparison of results shows that the recognition rates and times on a dot-matrix display are better in all cases. However, further investigations are needed to determine if this is due to mono-finger vs multi-finger exploration or for other reasons.
Next step of this work will be to reproduce the same experiment with visually impaired people. It would be also interesting to study the effects of different vibration frequencies and different outline widths as well to compare the performances of the dot-matrix display with those of a vibrotactile device such as in .
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