Open AccessHuman action recognition based on a single acceleration sensor
Author(s) -
Yi Qin 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%.