Abstract
Daily activity recognition is essential to enable smart elderly care services and the recognition accuracy affects much the quality of the elderly care system. Although a lot of work has been done to recognize elderly people’s activities of daily life (ADL), few systems have investigated if the location information can be deployed to improve the ADL recognition accuracy. In this paper, we intend to incorporate the location information in the activity recognition algorithm and see if it can help to improve the recognition accuracy. We propose two ways to bring the location information into the picture: one way is to bring location in the feature level, the other way is to utilize it to filter irrelevant sensor readings. Intensive experiments have been conducted to show that bringing location information into the activity recognition algorithm in both ways can help to improve the recognition rate by around 5% on average compared to the system neglecting the location information.
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Chen, C., Zhang, D., Sun, L., Hariz, M., Yuan, Y. (2012). Does Location Help Daily Activity Recognition?. In: Donnelly, M., Paggetti, C., Nugent, C., Mokhtari, M. (eds) Impact Analysis of Solutions for Chronic Disease Prevention and Management. ICOST 2012. Lecture Notes in Computer Science, vol 7251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30779-9_11
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DOI: https://doi.org/10.1007/978-3-642-30779-9_11
Publisher Name: Springer, Berlin, Heidelberg
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