Influence of the Number of Predicted Words on Text Input Speed in Participants With Cervical Spinal Cord Injury.

OBJECTIVES: To determine whether the number of words displayed in the word prediction software (WPS) list affects text input speed (TIS) in people with cervical spinal cord injury (SCI), and whether any influence is dependent on the level of the lesion. DESIGN: A cross-sectional trial. SETTING: A rehabilitation center. PARTICIPANTS: Persons with cervical SCI (N=45). Lesion level was high (C4 and C5, American Spinal Injury Association [ASIA] grade A or B) for 15 participants (high-lesion group) and low (between C6 and C8, ASIA grade A or B) for 30 participants (low-lesion group). INTERVENTION: TIS was evaluated during four 10-minute copying tasks: (1) without WPS (Without); (2) with a display of 3 predicted words (3Words); (3) with a display of 6 predicted words (6Words); and (4) with a display of 8 predicted words (8Words). MAIN OUTCOME MEASURES: During the 4 copying tasks, TIS was measured objectively (characters per minute, number of errors) and subjectively through subject report (fatigue, perception of speed, cognitive load, satisfaction). RESULTS: For participants with low-cervical SCI, TIS without WPS was faster than with WPS, regardless of the number of words displayed (P<.001). For participants with high-cervical SCI, the use of WPS did not influence TIS (P=.99). There was no influence of the number of words displayed in a word prediction list on TIS; however, perception of TIS differed according to lesion level. CONCLUSIONS: For persons with low-cervical SCI, a small number of words should be displayed, or WPS should not be used at all. For persons with high-cervical SCI, a larger number of words displayed increases the comfort of use of WPS.

STAACS3: Simulation Tool for AAC with Single-Switch Scanning.

Communication for people with motor impairments is a difficult, yet necessary, task in daily activities. To do so, soft keyboards, digital counterpart of physical keyboards, are used. Depending on their features, several designs can be considered, however their thoughtful evaluation in real-life is not feasible. Therefore, it becomes necessary to filter the possible configurations wisely, taking advantage of simulation tools. This paper presents STAACS3, a Simulation Tool for AAC with Single-Switch scanning, that allows to model and simulate the performance of any type of scanning keyboard regardless of its keys configuration, scanning strategy or prediction systems.

The effect of word prediction settings (frequency of use) on text input speed in persons with cervical spinal cord injury: a prospective study.

PURPOSE: To determine whether activation of the frequency of use and automatic learning parameters of word prediction software has an impact on text input speed. METHODS: Forty-five participants with cervical spinal cord injury between C4 and C8 Asia A or B accepted to participate to this study. Participants were separated in two groups: a high lesion group for participants with lesion level is at or above C5 Asia AIS A or B and a low lesion group for participants with lesion is between C6 and C8 Asia AIS A or B. A single evaluation session was carried out for each participant. Text input speed was evaluated during three copying tasks: • without word prediction software (WITHOUT condition) • with automatic learning of words and frequency of use deactivated (NOT_ACTIV condition) • with automatic learning of words and frequency of use activated (ACTIV condition) Results: Text input speed was significantly higher in the WITHOUT than the NOT_ACTIV (p< 0.001) or ACTIV conditions (p = 0.02) for participants with low lesions. Text input speed was significantly higher in the ACTIV than in the NOT_ACTIV (p = 0.002) or WITHOUT (p < 0.001) conditions for participants with high lesions. CONCLUSIONS: Use of word prediction software with the activation of frequency of use and automatic learning increased text input speed in participants with high-level tetraplegia. For participants with low-level tetraplegia, the use of word prediction software with frequency of use and automatic learning activated only decreased the number of errors. Implications in rehabilitation Access to technology can be difficult for persons with disabilities such as cervical spinal cord injury (SCI). Several methods have been developed to increase text input speed such as word prediction software.This study show that parameter of word prediction software (frequency of use) affected text input speed in persons with cervical SCI and differed according to the level of the lesion. • For persons with high-level lesion, our results suggest that this parameter must be activated so that text input speed is increased. • For persons with low lesion group, this parameter must be activated so that the numbers of errors are decreased. • In all cases, the activation of the parameter of frequency of use is essential in order to improve the efficiency of the word prediction software. • Health-related professionals should use these results in their clinical practice for better results and therefore better patients 'satisfaction.

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

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 on-screen 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 characters per minute with the static keyboard and 12 characters 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.