| 基于多传感器的运动员训练信息融合分析系统设计 |
投稿时间：2020-01-20 修订日期：2020-03-02  点此下载全文 |
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| 中文摘要:在运动训练过程中,采集工作是关系到运动员训练水平的关键,将多传感器的思想应用到信息融合技术上。本文通过多个传感器和摄像机分别对运动员的关键指标进行采集。前者是利用小波变换实现对人体表面肌电信号的特征提取,然后使用人工神经网络法对关键的特征的进行识别,得到初步人体运动评估结果。后者是对图像视频经过前景提取、特征提取、识别姿态及评估进行处理。提高了人体疲劳评估准确率,从根源上解决了传统系统的采集准确率地下的问题,经过科学指导,提高运动员训练水平,对于信息融合技 术具有重要的作用。 |
| 中文关键词:传感器 信息融合技术 小波变换 神经网络模型 证据理论 |
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| Design of athlete training information fusion analysis system based on multi-sensor |
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| Abstract:In the process of sports training, the collection work is the key to the training level of athletes. The idea of multi-sensor is applied to the information fusion technology. In this paper, the key indicators of athletes are collected by multiple sensors and cameras. The former uses wavelet transform to extract the features of EMG signals, and then uses artificial neural network to identify the key features, and gets the preliminary results of human motion evaluation. The latter is to process the image video through foreground extraction, feature extraction, attitude recognition and evaluation. It improves the accuracy of human fatigue assessment, solves the problem of the traditional system"s collection accuracy from the root, improves the training level of athletes through scientific guidance, and plays an important role in information fusion technology. |
| keywords:Sensor information fusion technology wavelet transform neural network model evidence theory |
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