基于改进朴素贝叶斯分类器的康复训练行为识别方法

Behavior recognition in rehabilitation training based on modified naive Bayes classifier

为提高康复训练中行为的识别率,对康复训练行为识别进行研究。首先采用Kinect传感器提取人体骨骼坐标信息,定义运动特征分类集合,完成朴素贝叶斯分类器设计;然后改进康复训练动作识别阈值选择机制提升识别率。改进前后对比实验证明该方法快速简洁,取得了较理想的识别效果。

This paper proposed a modified behavior recognition method to improve the recognition rate in rehabilitation training. First, it adopted Kinect sensor to detect human skeleton locations, defined the motion feature in rehabilitation training and designed the Bayes classifier. Second, the threshold selection process was improved to increase the recognition rate. The comparative experimental results with the unmodified one show that the modified naive Bayes classifier is simple and rapid, and it gains better identification effects in rehabilitation training.