Author:

Keywords:

SISTA, Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, Information Systems, Telecommunications, Computer Science, Gait speed, tele-monitoring, elder care, assisted living, video surveillance, health services for the aged, GO TEST, FALLS, RISK, HEALTH, SPEED, 0801 Artificial Intelligence and Image Processing, 0805 Distributed Computing, 46 Information and computing sciences

Abstract:

© 2016 IOS Press and the authors. All rights reserved. Previous studies have shown that gait speed is an important measure of functional ability in the elderly. Continuous monitoring of the gait speed of older adults in their home environment may therefore allow the detection of changes in gait speed which could be predictive of health changes of the monitored person. In this study, a system consisting of multiple wall-mounted cameras that can automatically measure the time an older adult needs to cross a predefined transfer zone in the home environment is presented. The purpose of this study is the preliminary validation of the algorithm of the camera system which consists of several preprocessing steps and the automatic measurement of the transfer times. This validation is done through data collection in the homes of four older adults for periods varying from eight to twelve weeks. Trends in the measured transfer times are visualised and subsequently compared with the results of clinical assessments obtained during the acquisition period such as Timed-Get-Up-and-Go tests. The results indicate that it is possible to identify long-term trends in transfer times which can be indicative of adverse health-related events.