Recognition Algorithm of Activity Recognition Based on Single Accelerometer

Abstract

Abstract. In order to improve the accuracy and variety of human motion recognition in the acceleration signal recognition. In this experiment, in addition to the station, lying, sitting, walking, running, walking speed, upstairs, downstairs action recognition of traditional research, this paper also adds to the left turn right 180 degrees, 180 degrees, 90 degrees, turn left, turn right 90 degrees, from lying to sitting, sitting from the station, from the station to sit down. Sixteen kinds of action from sit to, and used to monitor human motion more accurately. In this paper, a new SVM-KNN hierarchical classification model is proposed to identify the sixteen kinds of human actions. The experimental results show that the recognition algorithm has a high recognition rate.