Sports Training Intensity Information Fusion Method Based on Kinect Sensor
Author(s) -
Yan Huo
Publication year - 2022
Publication title -
journal of sensors
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.399
H-Index - 43
eISSN - 1687-7268
pISSN - 1687-725X
DOI - 10.1155/2022/2095514
Subject(s) - intensity (physics) , information fusion , process (computing) , computer science , fusion , training (meteorology) , sensor fusion , computer vision , node (physics) , acceleration , artificial intelligence , simulation , engineering , linguistics , philosophy , physics , structural engineering , classical mechanics , quantum mechanics , meteorology , operating system
In order to improve the information fusion effect of sports training intensity, this paper analyzes the information fusion process of Kinect sensor. In order to prevent the simulation platform from exceeding its working space and ensure that the sports athletes obtain a more realistic sense of motion, the adaptive washout algorithm can change the adaptive parameters online in real time according to the input athlete’s acceleration and angular velocity and the current motion state of the simulation platform. Moreover, this paper uses Kinect as the input device and combines the human node model to identify the features of training intensity information. After constructing an intelligent system, the performance of the system of this paper is verified. The research results show that the sports training intensity information fusion method based on the Kinect sensor proposed in this paper has a good effect in sports training intensity information fusion.
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