Mild cognitive impairment (MCI) is considered the stage between the mental changes that are seen between normal aging and early-stages of dementia. Indeed, MCI is one of the main indicators of incipient Alzheimer’s disease (AD) among other neuropsychological diseases. The growth of these diseases is generating a great interest in the development of new effective methods for the early detection of MCI because, although no treatments are known to cure MCI, this early diagnosis would allow early intervention to delay the effects of the disease and accelerate progress towards effective treatment in its early stages.
Although there have been many years of research, the early identification of cognitive impairment, as well as the differential diagnosis (to distinguish significant causes or typologies for its treatment), are problems that have been addressed from different angles, but are still far from being solved. Diverse types of tests have already been developed, such as biological markers, magnetic resonance imaging, and neuropsychological tests. While effective, biological markers and magnetic resonance imaging are economically expensive, invasive, and require time to get a result, making them unsuitable as a population screening method. On the other hand, neuropsychological tests have a reliability comparable to biomarker tests, and are cheaper and quicker to interpret.
Classical neuropsychological tests require very few resources for their application (pencil and paper is enough), however, the need for automation and a more objective assessment are motivating the development of new paradigms capable of assessing behavior and cognitive skills from the monitoring of ordinary activities, the performance of certain tasks, or the immersion in interactive applications through virtual reality. This is where intelligent systems can play a fundamental role, as they can overcome or alleviate the problems associated with the conventional form of evaluation, and also help health technicians to alleviate the problems of subjectivity, demosocial casuistry, personalization, etc. There is no doubt that the digitization of these tests and their analysis will lead to a deeper understanding of neurodegenerative diseases and will facilitate their use, not only for assessment, but also for treatment and assistance.
Main topics of this special session include (but are not restricted to):