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

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


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.


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



This research was partially supported by Nottingham Trent University’s Stimulating Innovation for Success (SIS) programme. The authors would like to thank Just Checking Ltd. ( for their support of this work.


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Ahmad Lotfi
    • 1
    Email author
  • 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

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