Amyotrophic Lateral Sclerosis (ALS)
AAC & SGDs
(Augmentative and Alternative Communication
Speech Generating Devices)
At some point in the disease process, most PALS will experience difficulty with their speech. By the ending stages of ALS, many people have no functional speech remaining for speaking. Yet communication can remain possible and effective through the use of augmentative and alternative communication (AAC) strategies.
What is AAC?
AAC refers to communication approaches that augment or supplement existing speech or act as an alternative to natural speech. AAC refers to all methods or modes that can be used to make communication easier for a person who has speech difficulties. Everyone uses multiple modes of communication during the day to augment what they are saying such as gestures and facial expressions. People who rely on AAC may use gestures and facial expressions to help convey a message. They may also communicate using an alphabet board with family, a computer for email, or a communication device with friends.
AAC does not mean that communication is “computerized or robotic-like talking.” AAC provides strategies for continuing to have a quality life experience when communication is as effective as possible.
A range of AAC strategies are available depending on individual abilities and needs. However, the goal of AAC always remains the same. That is to provide the supports and services that result in the most effective communication possible. Here is a basic list of AAC strategies that may be recommended:
- No-Tech Strategies
- Gestures and pointing
- Talk slowly
- Exaggerate your movements
- Low-Tech Strategies
- Manual Communication boards
- Eye gaze boards
- Laser light pointers on alphabet boards
- High-Tech Strategies
- Dedicated AAC Devices
A Word about Language
The most important element in recommending or selecting an AAC system is identifying the available language representation methods. How language is represented and generated on an AAC system is a leading factor affecting communication performance. Despite a large number of AAC systems on the market, only a limited number of language representation methods (LRMs) are used on all systems to generate spontaneous, novel conversation:
- Word prediction
- Word selection
- Semantic compaction
- Single meaning pictures
Spelling is considered the easiest method for adults with ALS to apply as an augmented communication method. AAC systems using spelling require the user to spell each word using a standard keyboard or alphabet array. Although spelling allows the person to say anything, spelling letter-by-letter is a slow and inefficient AAC strategy without using other techniques to increase rate.
Word prediction is a technique available on many AAC systems that offer spelling. Based on previously selected letters and words, the system presents the user with best guess choices for completing the spelling of a word. The use then chooses one of the predictions or continues spelling, resulting in yet another set of predictions (Romich, Vanderheiden, Hill, 2000). Although word prediction systems offer reduction in the number of keystrokes needed to complete a word, research indicates that the communication rate does not offer a significant improvement over spelling (Koester & Levine, 1994). Word prediction’s failure to increase rate is attributed to the increased time needed to read and select a word of a list of choices. However, persons with ALS may still benefit from keystroke savings by helping to prevent fatigue.
Word Selection is a technique that provides frequently used whole words on an overlay or display along with the letters of the alphabet. These commonly used “core” words can be selected using one or two keystrokes rather than spelling the whole word. Word selection offers both keystroke savings and improved rate.
Semantic Compaction or Minspeak is perhaps the most commonly used AAC language representation method (Baker, 1982). With this method, language is represented by a relatively small set of multi-meaning icons. However, semantic compaction had not been frequently recommended for persons with ALS until it was paired with word selection to decrease learning time.
Single Meaning Pictures involve the use of graphic or line drawn symbols to represent single word vocabulary or messages (phases, sentences, and paragraphs). For adult vocabularies, basing an entire system on symbols would mean locating words on dozens of pages. However, some systems support using alphabet-based methods along with symbols. These systems generally provide symbols to access less frequently used words (extended vocabulary) or customized phases and sentences.
Methods for Generating Communication
- Spontaneous novel utterance generation (SNUG)
- Pre-stored messages
For most people the most desired and effective approach for communication is spontaneous novel utterance generation, or SNUG. SNUG is based on access to individual words, collocations, and commonly used phrases of our language. SNUG allows a person to say anything anytime. The alternative to SNUG is the use of pre-stored sentences (Hill, 2001).
The use of pre-stored sentences offers utility for many adults experiencing loss of speaking abilities. Pre-stored messages can be accessed quickly and loaded with pertinent information about a topic. For some speaking occasions, entire scripts may be programmed such as calling the pharmacy for reordering prescriptions. However, research has shown the unpredictable nature of conversations (Balandin & Iacono, 1999). Research on adults with cerebral palsy showed the infrequent use of pre-stored messages during communication using an AAC system (Hill, 2001). Finally, programming time for pre-stored messages needs to be taken into consideration.
In summary, adults who rely on AAC use multiple language representation methods for communicating. Specific language representation methods tend to be used for core vocabulary and other methods for extended vocabulary. Adults who rely on AAC use pre-stored messages infrequently with the majority of communication consisting of SNUG.
What is a Speech Generating Device (SGD)?
A speech generating device or SGD is a term used by Medicare to identify a range of voice output AAC systems. SGDs are more frequently called AAC systems or devices by professionals and the people who use them. For funding purposes, Medicare has established “K-codes” to categorize SGDs by features. The speech language pathologist on the ALS team should be knowledgeable about these categories and codes, and explain the device features that fit in the categories during the evaluation process. More specific information about funding can be found at the AAC Insititute funding page or by visiting the Rehabilitation Engineering Research Center (RERC) on Communication Enhancement at www.aac-rerc.org.
PALS and family members should be most concerned about being evaluated for an SGD that will result in the most effective communication through the disease process. PALS will experience many changes in abilities and performance over time. An SGD that appears appropriate and appealing at early stages of speech difficulty may NOT meet any needs at later stages. A standard rule of thumb comes from the human factors field that emphasizes, “ease of use at first encounter rarely leads to effective long term use.” (Norman, 1980) Most funding parties only provide for the purchase of one SGD. Therefore, careful consideration of a range of features that will meet a range of needs and abilities is critical.
AAC Medicare Speech Generating Device Assessment Committee. (2003, January). Final committee report to the Health Care Economics Committee.
Baker, B. (1982). Minspeak: A semantic compaction system that makes self-expression easier for communicatively disabled individuals. Byte, 7, 186-202.
Balandin, S., & Iacono, T. (1999). Crews, wusses, and whoopas: Core and fringe vocabularies of Australian meal-break conversations in the workplace. Augmentative and Alternative Communication, 15, 95-109.
Hill, K. (2001). Achieving success in AAC: assessment and intervention. AAC Institute monograph, 1(1).
Koester, H. H., & Levine, S. P. (1994). Modeling the speed of text entry with a word prediction interface. IEEE Transactions on Rehabilitation Engineering, 2 (3), 177-187.
Norman, D.A. (1980). The Psychology of Everyday Things. Basic Books, Inc.: New York.
Romich, B., Vanderheiden, G., & Hill, K. (2000). Augmentative communication. In J.D. Bronzine (Ed.), Biomedical engineering handbook, second edition, (pp. 101-122). Boca Raton, FL: CRC Press.