Smart homes for the elderly dementia sufferers: identification and prediction of abnormal behaviour

  • Ahmad Lotfi
  • Caroline Langensiepen
  • Sawsan M. Mahmoud
  • M. J. Akhlaghinia
Original Research

DOI: 10.1007/s12652-010-0043-x

Cite this article as:
Lotfi, A., Langensiepen, C., Mahmoud, S.M. et al. J Ambient Intell Human Comput (2012) 3: 205. doi:10.1007/s12652-010-0043-x

Abstract

In this paper, we have described a solution for supporting independent living of the elderly by means of equipping their home with a simple sensor network to monitor their behaviour. Standard home automation sensors including movement sensors and door entry point sensors are used. By monitoring the sensor data, important information regarding any anomalous behaviour will be identified. Different ways of visualizing large sensor data sets and representing them in a format suitable for clustering the abnormalities are also investigated. In the latter part of this paper, recurrent neural networks are used to predict the future values of the activities for each sensor. The predicted values are used to inform the caregiver in case anomalous behaviour is predicted in the near future. Data collection, classification and prediction are investigated in real home environments with elderly occupants suffering from dementia.

Keywords

Smart home Dementia Alzheimer Assistive technology Prediction Abnormality detection Time series Sensor network Intelligent environment 

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Ahmad Lotfi
    • 1
  • Caroline Langensiepen
    • 1
  • Sawsan M. Mahmoud
    • 1
  • M. J. Akhlaghinia
    • 2
  1. 1.School of Science and TechnologyNottingham Trent UniversityNottinghamUK
  2. 2.Centre for Innovation and Technology Exploitation Nottingham Trent UniversityNottinghamUK

Personalised recommendations