Abubaker Elbayoudi
Ahmad Lotfi
ABSTRACT
The availability of datasets for monitoring the activities of daily living is limited by difficulties associated with the collection of such data. There have been many suggested software solutions to overcome this issue. In this paper, a new technique to generate realistic data is proposed. The new method provides virtual data to the researchers with the ability to rapidly generate a large simulated dataset with different factors that could be used to represent different behaviour of a user. This paper describes the use of Hidden Markov Model (HMM) and Direct Simulation Monte Carlo (DSMC) to generate data for Activities of Daily Living (ADL) representing an older adult's behaviour. The combination of HMM and DSMC facilitates the generation of datasets capturing behaviour in terms of occupancy and movement activity performance in the environment. Simulated data is validated against data collected from a real environment.
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Index Terms
- Modelling and simulation of activities of daily living representing an older adult's behaviour
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