Feasibility study of a real-time wandering detection algorithm for dementia patients

Abstract

In this paper, we present a new algorithm that automatically classifies wandering patterns (or behaviors) of patients with Alzheimer's disease and other different types of dementia. Experimental results on a real-life dataset show that this algorithm can provide a robust and credible assistive technology for monitoring patients with dementia (PWD) who are prone to wandering. Combined with indoor and outdoor location technologies using ubiquitous devices such as smart phones, we also demonstrate the feasibility of a remote mobile healthcare monitoring solution that is capable of reasoning about wandering behaviors of PWD and real-time detection of abnormalities that require timely intervention from caregivers.