Design rationale and evaluation of the Portable Anticipatory Communication Aid—PACA

Heckathorne, Craig W.; Voda, Jerrilyn A.; Leibowitz, Lew

doi:10.1080/07434618712331274489

Cited by 16 publications

(12 citation statements)

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“…However, it also has the effect of presenting the user with a constantly changing display. While Heckathorne et al (58) argue that this factor is not problematic for experienced users, their research did not address this issue. In discussing scanning input systems, Barker (59) stated that experienced users do not typically follow the scan highlight, but look at the item they want to select and hit the switch when it is highlighted.…”

Section: Design Case Study 2: Letter Predictionmentioning

confidence: 94%

“…The ANTIC system developed at Tufts predicted the six most likely letters based on the three preceding letters (54,55). Heckathorne and colleagues continued work in letter prediction in the development of the MicroDEC II and PACA communication systems (56)(57)(58). The PACA system added optional word predictions that appeared after the first two letters were selected.…”

Section: Design Case Study 2: Letter Predictionmentioning

confidence: 98%

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Human Factors Considerations in the Design of Language Interfaces in AAC

Demasco

1994

Assistive Technology

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The design and development of new augmentative and alternative communication (AAC) systems and techniques must often include a focus on the presentation, selection, and processing of language items. We define this as the language interface and argue that researchers must take into account the broad base of knowledge available from the fields of human factors and human-computer interaction in the design process. This article will present an overview of these fields and discuss design principles that are relevant to AAC language interfaces. These principles will be discussed with respect to a number of currently available techniques. In addition, design case studies will be presented on some techniques currently under investigation. Finally, issues related to evaluation will be discussed.

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Section: Design Case Study 2: Letter Predictionmentioning

confidence: 94%

Section: Design Case Study 2: Letter Predictionmentioning

confidence: 98%

Human Factors Considerations in the Design of Language Interfaces in AAC

Demasco

1994

Assistive Technology

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“…This suggests that there was a subjective advantage of this keyboard for this participant. The subjective benefits of dynamic keyboards have previously been described for participants with motor disability who use scanning systems [26]. This advantage of the dynamic keyboard when used with scanning systems requires confirmation in larger numbers of participants who use scanning systems, such as those with amyotrophic lateral sclerosis, locked-in syndrome, and advanced multiple sclerosis.…”

Section: Dynamic Versus Standard Keyboardmentioning

confidence: 99%

“…Dynamic keyboards have existed for several years and are particularly used by people who use scanning systems [26,29] to increase text input speed and communication rate [26,30], although they were also designed for people who use pointing devices [18][19]28]. In 2009-2010, our team developed a dynamic keyboard that was intended for use by users of both scanning systems and pointing devices [28].…”

Section: Dynamic Versus Standard Keyboardmentioning

confidence: 99%

“…With regard to scanning systems, Koester and Levine found that word prediction reduced text input speed in nondisabled subjects (by 8.2%) [24][25]. Heckathorne et al showed that the greater the visual search time (related to the number of predicted words presented), the greater the reduction in text input speed in three subjects with disabilities [26].…”

Section: Introductionmentioning

confidence: 99%

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Effect of dynamic keyboard and word-prediction systems on text input speed in persons with functional tetraplegia

Pouplin¹,

Robertson

Antoine

et al. 2014

J Rehabil Res Dev

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Abstract-Information technology plays a very important role in society. People with disabilities are often limited by slow text input speed despite the use of assistive devices. This study aimed to evaluate the effect of a dynamic on-screen keyboard (Custom Virtual Keyboard) and a word-prediction system (Sibylle) on text input speed in participants with functional tetraplegia. Ten participants tested four modes at home (static onscreen keyboard with and without word prediction and dynamic on-screen keyboard with and without word prediction) for 1 mo before choosing one mode and then using it for another month. Initial mean text input speed was around 23 words per minute with the static keyboard and 12 words per minute with the dynamic keyboard. The results showed that the dynamic keyboard reduced text input speed by 37% compared with the standard keyboard and that the addition of word prediction had no effect on text input speed. We suggest that current forms of dynamic keyboards and word prediction may not be suitable for increasing text input speed, particularly for subjects who use pointing devices. Future studies should evaluate the optimal ergonomic design of dynamic keyboards and the number and position of words that should be predicted.

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Adaptive predictive text generation and the reactive keyboard

Darragh

Witten

1991

Interacting with Computers

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Design rationale and evaluation of the Portable Anticipatory Communication Aid—PACA

Cited by 16 publications

References 1 publication

Human Factors Considerations in the Design of Language Interfaces in AAC

Human Factors Considerations in the Design of Language Interfaces in AAC

Effect of dynamic keyboard and word-prediction systems on text input speed in persons with functional tetraplegia

Adaptive predictive text generation and the reactive keyboard

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