Fingertip positioning and tracking method of intelligent moving bracelet based on improved Kalman filter

被引:0
|
作者
Honggang Z. [1 ]
机构
[1] Physical Education and Research Department, Changchun Institute of Architecture, Jilin, Changchun
关键词
KNN algorithm; least square method; low pass filter; Z-score method;
D O I
10.1504/IJPD.2022.125376
中图分类号
学科分类号
摘要
In order to overcome the problems of poor positioning accuracy and low tracking accuracy of traditional methods, this paper proposes an intelligent motion bracelet fingertip positioning and tracking method based on improved Kalman filter. Firstly, the bracelet signal filtering is realised by the least square method; the Z-score method is used to normalise the sensor pressure data to realise data pre-processing; then, the rigid structure model of human hand bone is constructed, the posture of human hand is reconstructed, the coordinate system of human upper arm is obtained, and the positioning ability of fingertip is improved. Finally, the RSSI signal of fingertip is collected by sensor, and the improved Kalman filter is used to realise the positioning and tracking of fingertip of bracelet. The experimental results show that the positioning accuracy of this method is 97.9%, the tracking accuracy is 97.6%, and the fingertip positioning and tracking effect is good. Copyright © 2022 Inderscience Enterprises Ltd.
引用
收藏
页码:242 / 253
页数:11
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