Cognitive Load Based Adaptive Assistive Technology Design for Reconfigured Mobile Android Phone

In assistive technology design, it is indispensible to consider the sensory, physical and cognitive level of target users. Cognitive load is an important indicator of cognitive feedback during interaction and became the critical research issue in designing assistive user interfaces, incorporated with smartphone based assistive technology like in the android platform. In this paper, we proposed a cognitive load based user interface integrated with reconfigured mobile android phone (R-MAP) based on user‟s cognitive load level. We performed some cognitive tasks within a small group of sighted but blindfolded people and blind people or visually impaired using R-MAP. Based on task performance and cognitive load levels we manually annotated some data of 24 participants and finally applied some machine learning algorithms to automate the mobile interface. Based on our novel design and experimental finding, we recommended that “cognitive load enabled feedbacks based assistive user interface” would be a useful assistive tool for the people who use mobile phone for their daily operations.