RERC on AAC
The RERC on AAC is a collaborative center committed to advancing knowledge and producing innovative engineering solutions in augmentative and alternative communication (AAC). The RERC on AAC will support a research and development program that addresses three areas of rehabilitation science and engineering:
- Improving access to technologies through exploration of innovative approaches and through integration of multi-modalities;
- Developing innovative language support technologies, including natural language processing and computer-mediation, to support effective communication for children and adults with limited access to language;
- Improving the human computer interface to reduce cognitive visual processing demands and enhance communication performance.
We also will support a range of training and dissemination activities. Our goal is that the AAC technologies and knowledge generated by the RERC on AAC will enable individuals with complex communication needs to achieve the basic human right of communication, and to maximize their participation in education, employment, health and community activities.
AAC intervention to build communication, language, and literacy skills with children with complex communication needs… (Light, 2016)
What advances have been made to date in AAC interventions for children? And what are the challenges that we need to address to improve outcomes?
Precision intervention research for adults with complex communication needs resulting from acquired medical conditions (Beukelman, 2016).
“In this article, I will briefly discuss the population base of adults with acquired complex communication needs…”
Fast switch scanning keyboards: Minimal expected query decision trees (Higger et al, 2016)
Within AAC, switch scanning is a common paradigm for spelling where a set of characters is highlighted and the user is queried as to whether their target character is in the highlighted set. This work seeks a decision tree which requires the fewest expected queries per decision sequence (EQPD).
A kronecker product structured EEG covariance estimator for a language model assisted-BCI (Gonzalez-Navarro & Moghadamfalahi, 2016)
in this manuscript we propose a Kronecker product structure for covariance matrices
Spatio-temporal EEG models for brain interfaces (Gonzalez-Navarro et al, 2017)
In this paper we propose a structure for the covariance matrices of the multichannel EEG signals.
Probabilistic simulation framework for EEG-based BCI design (Orhan et al., 2016).
In this manuscript, we develop a Monte Carlo-based probabilistic simulation framework for electroencephalography (EEG) based BCI design.
Effect of Message Type on the Visual Attention of Adults With Traumatic Brain Injury (Thiessen et al., 2017).
This investigation provides preliminary evidence of the relationship between image and message type for people with TBI.
Student Engineering Partnerships for Spring 2017
The RERC on AAC partnered with three student engineering Learning Factory teams at Penn State University in the spring of 2017
Penn State News highlights AAC Think Tank
Penn State News featured the RERC on AAC Doctoral Student Think Tank in a recent news story
RERC on AAC Think Tank
The Doctoral Student AAC Research Think Tank was held at Penn State University from May 16 – May 18, 2017.