A patient management approach that produces accurate and reliable data, empowers patients, influences their attitudes and behaviors and potentially improves their medical conditions.
Published in Chapter:
An Ambient Intelligence System for the Monitoring, Empowerment, and Disease Evolution Prediction for Patients with Mild Cognitive Impairment
Konstantinos Votis (Information Technologies Institute, Greece), Sofia Segkouli (Information Technologies Institute, Greece & Greek Association of Alzheimer's disease and Related Disorders, Greece), Anastasios Drosou (Information Technologies Institute, Greece), Dimitrios Tzovaras (Information Technologies Institute, Greece), and Magda Tsolaki (Greek Association of Alzheimer's disease and Related Disorders, Greece & Aristotle University of Thessaloniki, Greece)
Copyright: © 2015
|Pages: 15
DOI: 10.4018/978-1-4666-8234-4.ch012
Abstract
This chapter addresses the critical issue of exploration and integration of environmental factors as well as the effect of activities of daily living with medical and biological factors in order to monitor and predict AD/MCI disease progression and evolution. Thus, traditional approaches to clinical research and practice requires population statistics and therefore takes into account only the average biological behaviour of the disease, independently of the person specific clinical history, environmental factors, as well as the daily activity interactions in relation to historical data. The proposed system will use IT-based tools (including also 3D gaming environments) in order to address specific cognitive and physical/motor parameters and ADLs (activities of daily living) factors within AD, and MCI domain and aim at improving their diagnosis, evaluating their variations along the progress of an Alzheimer disease and its different steps, and supporting the stimulation/training of the patient affected by the disease.