Research Article
Inactivity Monitoring for People with Alzheimer’s Disease Using Smartphone Technology
@INPROCEEDINGS{10.1007/978-3-642-29734-2_43, author={Nicola Armstrong and Chris Nugent and George Moore and Dewar Finlay and William Burns}, title={Inactivity Monitoring for People with Alzheimer’s Disease Using Smartphone Technology}, proceedings={Wireless Mobile Communication and Healthcare. Second International ICST Conference, MobiHealth 2011, Kos Island, Greece, October 5-7, 2011. Revised Selected Papers}, proceedings_a={MOBIHEALTH}, year={2012}, month={10}, keywords={Alzheimer’s disease Smartphone Technology Assistive Technologies}, doi={10.1007/978-3-642-29734-2_43} }- Nicola Armstrong
Chris Nugent
George Moore
Dewar Finlay
William Burns
Year: 2012
Inactivity Monitoring for People with Alzheimer’s Disease Using Smartphone Technology
MOBIHEALTH
Springer
DOI: 10.1007/978-3-642-29734-2_43
Abstract
Worldwide the number of old and older people is increasing alongside the increase in average life expectancy. Due to this increase the number of age related impairments within the older society, in addition to the prevalence of chronic disease are also heightened. One of the most widespread chronic diseases is dementia, specifically Alzheimer’s disease (AD). AD is a brain related condition which impairs a person’s memory, thought and judgment. The aim of the current research has been to identify and alleviate a set of problems related to AD using smartphone technology. In order to determine if the level of support for those suffering from AD can be improved, our current work investigates the use of activity/inactivity monitoring using various smartphone services. Inactivity levels are being monitored in order to detect if a smartphone handset has been misplaced unintentionally, and to avoid any impact this may have on smartphone services. Specifically, GSM signal strength, Wi-Fi signal strength and accelerometer data are considered. Three smartphone applications have been developed and tested on a cohort of 8 healthy adult users as part of a pre-study investigation. Results from the pre-study indicate that the optimal approach to detect inactivity on a smartphone handset was via GSM signal strength coupled with accelerometer data.