Validating a model of row–column scanning

Abstract

Purpose: For individuals with severe motor and communicative disabilities, single switch scanning provides a way to access a computer and communicate. A model was developed that utilizes scanning interface settings, error tendencies, error correction strategies, and the matrix configuration to predict a user’s communication rate. Method: Five individuals who use single switch scanning transcribed sentences using an on-screen keyboard configured with the settings from their communication devices. Data from these trials were used as input to a model that predicted TER for the baseline configuration and at least three other system configurations. Participants transcribed text with each of these new configurations and the predicted TER was compared to the actual TER. Results: Results showed that predicted TER was accurate to within 90% on average. The scan rate was also entered into a previously published model which assumes error-free performance. For our model, the average error for each participant was 10.49%, compared to 79.7% for the model assuming error-free performance. Conclusions: Our model of row–column scanning was much more accurate than a model that did not consider the likelihood of an error occurring. There is still room for improvement, however, and the results of the study will lead to additional modifications of the model.

Implications for Rehabilitation

• Although row-column scanning is a very slow method of selection, changes in the configuration of the interface can produce noticeable changes in performance.

• When configuring a row-column scanning interface, clinicians should consider the type of errors their client is likely to commit to target interface features to their client's specific needs.

• Some clients who use row-column scanning may not benefit from advanced interface features, even if they are available.

Keywords::

• Wwitch access
• row-column scanning
• augmentative communication

Acknowledgements

The authors would like to thank the individuals who volunteered to participate in this research.

Declaration of interest

This research was funded by a grant from the National Institutes of Health (#2R44HD045015-03) and the National Science Foundation (#0333420). The authors report no conflict of interest.