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Activity Recognition Method for Home-Based Elderly Care Service Based on Random Forest and Activity Similarity
- Source :
- IEEE Access, Vol 7, Pp 16217-16225 (2019)
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- In home-based elderly care service, how to precisely recognize activities is a key issue in the design and implementation of context-aware service for elderly people. Existing research works reveal that those approaches ignore the characteristics of activity diversity, and similarity and the features of activities of elderly people at home, so recognition accuracy of those approaches are not high enough for real-life applications. Thus, in this paper, we first study the types of activities in home-based elderly care service. Then, we propose a two-stage elderly home activity recognition method based on random forest and activity similarity. The method uses improved random forest to obtain a preliminary result in the first stage. Then, the correlation between activity, location, and time is employed to judge the rationality of the result. The similarity of activities is further used to correct the results in the second stage. We set up a series of experiments to evaluate the effectiveness and efficiency of our approach.
- Subjects :
- General Computer Science
Computer science
home-based care service
Decision tree
Elderly care
activity similarity
02 engineering and technology
Machine learning
computer.software_genre
Activity recognition
context awareness
Similarity (psychology)
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
Set (psychology)
Hidden Markov model
Service (business)
business.industry
General Engineering
020206 networking & telecommunications
Random forest
Key (cryptography)
020201 artificial intelligence & image processing
Artificial intelligence
lcsh:Electrical engineering. Electronics. Nuclear engineering
business
computer
lcsh:TK1-9971
random forest
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....54b38cc38462b984850247e81aa74775