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Activity Recognition for the Smart Hospital
Abstract
A main challenge in developing ambient-intelligence environments is context recognition. Systems can easily recognize some contextual variables, such as location, but activity recognition is much more complex. The authors describe an approach for estimating activities in a working environment. They used data representing 196 hours of detailed observation of hospital workers to train and test a hidden Markov model. The results indicate that an HMM can correctly estimate user activity 92.6 percent of the time and can outperform neuronal networks and even human observers familiar with the work practices. These results can help augment ambient-intelligence environments in hospitals. This article is part of a special issue on ambient intelligence.
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Cited by
Ambient intelligence: Technologies, applications, and opportunities
Cook, D. J., Augusto, J. C., & Jakkula, V. R. (2009) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2009.04.001 · Cited by 964
A Survey on Ambient Intelligence in Healthcare
Acampora, G., Cook, D. J., Rashidi, P., & Vasilakos, A. V. (2013) · Proceedings of the IEEE · doi:10.1109/jproc.2013.2262913 · Cited by 630
Discovering Activities to Recognize and Track in a Smart Environment
Rashidi, P., Cook, D. J., Holder, L. B., & Schmitter-Edgecombe, M. (2011) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2010.148 · Cited by 462
Assessing the Quality of Activities in a Smart Environment
Schmitter-Edgecombe, M., & Cook, D. J. (2009) · Methods of Information in Medicine · doi:10.3414/me0592 · Cited by 403
Illuminating the dark spaces of healthcare with ambient intelligence
Haque, A., Milstein, A., & Fei-Fei, L. (2020) · Nature · doi:10.1038/s41586-020-2669-y · Cited by 274
Metadata
- Authors
- Sanchez, D., Tentori, M., & Favela, J.
- Venue
- IEEE Intelligent Systems
- Published
- 2008-03
- Volume
- 23
- Issue
- 2
- Pages
- 50-57
- ISSN
- 1541-1672 (ISSN-L)
- OpenAlex
- W2050836750
- Cited by
- 217
- References
- 0
- FWCI
- 29.59
- Type
- journal article
- Language
- en
- Open access
- closed
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- Sanchez, D., Tentori, M., & Favela, J. (2008). Activity Recognition for the Smart Hospital. IEEE Intelligent Systems. https://doi.org/10.1109/mis.2008.18
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