Human action recognition based on a single acceleration sensor | Zendy

Yi Wu | Zendy

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Human action recognition based on a single acceleration sensor

Author(s) -

Yi Wu

Publication year - 2019

Publication title -

journal of physics conference series

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.21

H-Index - 85

eISSN - 1742-6596

pISSN - 1742-6588

DOI - 10.1088/1742-6596/1237/4/042011

Subject(s) - acceleration , feature (linguistics) , signal (programming language) , artificial intelligence , support vector machine , computer science , pattern recognition (psychology) , measure (data warehouse) , action (physics) , computer vision , data mining , physics , linguistics , philosophy , classical mechanics , quantum mechanics , programming language

In this paper, based on the acceleration signal acquired by a single triaxial acceleration sensor worn at the bottom of the finger, an algorithm for recognizing the daily movement behavior of the human body is proposed. The algorithm converts the three-axis acceleration into the resultant acceleration, horizontal acceleration and vertical acceleration, and extracts the features from them. The 37 features are sorted by the F-score as a measure of the importance of the feature, and a subset of features that meet the application requirements is found. Model training is performed on the feature subset using multi-class SVM to obtain the final classification model. Experiments show that the model has high recognition accuracy and the accuracy can reach 93.17%.

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