Nursing homes usually host large accounts of persons with different levels of dementia. Detecting dementia process in early stages may allow the application of mechanisms to reduce or stop the cognitive impairment. Our ultimate objective is to demonstrate that the use of persuasive techniques may serve to motivate these subjects and induct re-learning mechanisms to stop mental impairment. Nevertheless, this requires the study of the behaviour of each patient individually in order to detect conduct disorders in their living ambient. This study presents a behavior pattern detection architecture based on the Ambient Assisted Living paradigm and Workflow Mining technology to enable re-learning mechanisms in dementia processes via providing tools to automate the conduct disorder detection. This architecture fosters the use of Workflows as representation languages to allow health professionals to represent persuasive motivation protocols in the AAL environment to react individually to dementia symptoms detected.