An Architecture Proposal for Adaptive Neuropsychological Assessment

In this work we present the architecture of an special sort of software capable of changing its presentation depending on the behavior of a particular user. Although the proposed solution is applicable as the base of a general adaptive application, we want to expose the peculiarities of the model designed specifically to work in a special domain, the cognitive neuropsychology. In this domain, one of the most important topic is the design of task for the assessment of patients with cerebral damage. Depending of the patient, and its particular characteristics, the therapists must adjust the exposition time of several stimulus in order to obtain the best parameter values, and therefore to obtain the profile in a precise way. This is a very important topic because correct assessment implies successful rehabilitation but, in practice, this process is time-consuming and difficult to be done. So, with the aim to help the therapists in the task tuning process, we propose the use of artificial intelligence-based techniques in order to detect the patient's profile automatically during the execution time, adapting the values of the parameters dynamically. In particular, we propose the foundation of temporal similarities techniques as the basis of design adaptive software.