iWander: An Android application for dementia patients.

Annu Int Conf IEEE Eng Med Biol Soc

Department of Computer Science, Florida State University, Tallahassee, Florida 32306, USA.

Published: March 2011

AI Article Synopsis

  • Non-pharmacological management of dementia can be challenging for caregivers, who must help patients with daily activities while promoting their independence.
  • The iWander mobile application enhances the care of dementia patients by using GPS technology to enable remote monitoring, reducing caregiver stress.
  • The app utilizes Bayesian network techniques to analyze behavior patterns and suggests tailored interventions, such as navigation assistance and alerts for caregivers, to improve patient safety and independence.

Article Abstract

Non-pharmacological management of dementia puts a burden on those who are taking care of a patient that suffer from this chronic condition. Caregivers frequently need to assist their patients with activities of daily living. However, they are also encouraged to promote functional independence. With the use of a discrete monitoring device, functional independence is increased among dementia patients while decreasing the stress put on caregivers. This paper describes a tool which improves the quality of treatment for dementia patients using mobile applications. Our application, iWander, runs on several Android based devices with GPS and communication capabilities. This allows for caregivers to cost effectively monitor their patients remotely. The data uncollected from the device is evaluated using Bayesian network techniques which estimate the probability of wandering behavior. Upon evaluation several courses of action can be taken based on the situation's severity, dynamic settings and probability. These actions include issuing audible prompts to the patient, offering directions to navigate them home, sending notifications to the caregiver containing the location of the patient, establishing a line of communication between the patient-caregiver and performing a party call between the caregiver-patient and patient's local 911. As patients use this monitoring system more, it will better learn and identify normal behavioral patterns which increases the accuracy of the Bayesian network for all patients. Normal behavior classifications are also used to alert the caregiver or help patients navigate home if they begin to wander while driving allowing for functional independence.

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Source
http://dx.doi.org/10.1109/IEMBS.2010.5627669DOI Listing

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