Hybrid Model-Based Motion Recognition for Smartphone Users
- Hybrid Model-Based Motion Recognition for Smartphone Users
- 신범주; 김철기; 김재헌; 이석; 기창돈; 이택진
- Hybrid model; motion recognition; decision
tree; artificial neural network; smartphone
- Issue Date
- ETRI journal
- VOL 36, NO 6, 1016-1022
- This paper presents a hybrid model solution for user motion recognition. The use of a single classifier in motion recognition models does not guarantee a high recognition rate. To enhance the motion recognition rate, a hybrid model consisting of decision trees (DTs) and artificial neural networks (ANNs) is proposed. We define six user motions commonly performed in an indoor environment. To demonstrate the performance of the proposed model, we conduct a real field test with ten subjects (five males and five females). Experimental results show that the proposed model provides a more accurate recognition rate compared to that of other single classifiers.
- Appears in Collections:
- KIST Publication > Article
- Files in This Item:
There are no files associated with this item.
- RIS (EndNote)
- XLS (Excel)
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.