Page 472 - Biomedical Engineering and Design Handbook Volume 2, Applications

450 REHABILITATION ENGINEERING AND PROSTHETICS DESIGN

form of letter or symbol selection is required, and in many cases persons who are unable to speak
use a keyboard to type their messages that are then spoken by an AAC device. If the person has
limited motor skills, this can result in significantly lower rates of communication than for speech (as
low as a few words per minute). Cook and Polgar (2008) describe other relationships between AAC
characteristics and effective conversational skills.
AAC systems may be thought of as having three major components: (1) user interface, (2) processor,
and (3) output. The user interface has been described earlier in this chapter. It includes the user
control interface, selection method and selection set, and an optional user display to provide feed-
back for self-correction. AAC devices often use special symbols in the selection set. These include
miniatures of objects, color or black-and-white pictures, line drawings, pictographic symbols, text
∗
characters, and multiple meaning icons (Beukelman and Mirenda, 2005). For AAC systems, the
processor has several specific functions: (1) selection technique, (2) rate enhancement and vocabulary
expansion, (3) vocabulary storage, and (4) output control. The output is conversational and/or graphic
communication. Communication takes place in many different settings.
In order to maximize the production of output, AAC devices use techniques to increase the rate
of entry by the user. Any approach that results in the number of characters generated being greater
than the number of selections that the individual makes will increase rate. Rate enhancement
techniques can be grouped into two broad categories: (1) encoding techniques and (2) prediction
techniques. There are several types of codes that are currently used in AAC devices. Numeric codes
can be related to words or complete phrases or sentences. When the user enters one or more
numbers, the device outputs the complete stored vocabulary item. Abbreviation expansion is a tech-
nique in which a shortened form of a word or phrase (the abbreviation) stands for the entire word or
phrase (the expansion). When an abbreviation is entered, it is automatically expanded by the device
into the desired word or phrase. Vanderheiden and Kelso (1987) discuss the major features of abbre-
viation expansion systems and the strategies for developing stored vocabulary using this approach.
An alternative approach that is based on coding of words, sentences, and phrases on the basis of their
meaning is called semantic encoding (Baker, 1982). In this approach, pictorial representations, called
icons, are used in place of numerical or letter codes. For example, using a picture of an apple for
“food,” and a sun rising for “morning,” then selecting “apple” “sunrise” as a code for “What’s for breakfast”
is easier to remember than an arbitrary numeric or letter code for the same phrase. The apple can also
represent the color red, eating, fruit, etc.
It is also possible to realize significant increases in rate by using word prediction or word
completion techniques with any selection method (Swiffin et al., 1987). Devices that use these tech-
niques typically have a list on the screen that displays the most likely words based on the letters that
have previously been entered. The user selects the desired word, if it is listed, by entering a number
listed next to the word. If the desired word is not displayed, the user continues to enter letters, and
the listed words change to correspond to the entered letters. In adaptive word completion, the ranking
of the presented list is changed based on the user’s frequency of use. Placing the word lists on the
screen at the point in the document where the typed letters appear enables the user to keep his gaze
fixed on one location while typing, and it also requires significantly fewer switch activations in scan-
ning. One application of this approach, called Smart Lists, TM† can be used with either keyboard or
scanning entry. Smart Keys TM‡ is similar to the Minspeak icon prediction. After each entry only the
keys which contain a prediction based on that entry are left on the on-screen keyboard, making
scanning significantly faster.
A selection set for AAC consists of a maximum of 128 selections on most devices, and many have
far fewer available at any one time. However, even a child has a vocabulary of thousands of words.
Thus, it is necessary to have methods to allow easy access to vocabulary items that are not displayed.
The rate enhancement techniques are one way to do that, but they all require memory and cognitive
skills such as sequencing. One approach is to present the selection sets on a dynamic display

∗ Minsymbols, Prentke Romich Co., Wooster, Ohio.
† Applied Human Factors, Helotes, Tex., www.ahf-net.com.
‡ Applied Human Factors, Helotes, Tex., www.ahf-net.com.