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Comparative study on classifying gait with a single trunk-mounted inertial-magnetic measurement unit

机译:单箱式惯用磁测控装置对比较研究

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Athletes and their coaches aim for enhancing the sports performance. Collecting data from athletes, transforming them into useful information related to their sports performance (e.g., their type of gait), and transmitting the information to the coaches supports the enhancement. The types of gait standing, walking, and running were often examined. Lack of research remains for the two types of running, jogging and sprinting. In this work, standing, walking, jogging, and sprinting were classified with a single inertial-magnetic measurement unit that was placed at a novel position at the trunk. A comparison was made between classification systems using different combinations of accelerometer, gyroscope, and magnetometer data as well as different classifiers (Nai?ve Bayes, k-Nearest Neighbors, Support Vector Machine, Adaptive Boosting). After collecting data from 15 male subjects, the data were preprocessed, features were extracted and selected, and the data were classified. All classification systems were successful. With a mean true positive rate of 95.68% ±1.80%, the classification system using accelerometer and gyroscope data as well as the Nai?ve Bayes classifier performed best. The classification system can be used for applications in sport and sports performance analysis in particular.
机译:运动员及其教练旨在提高体育绩效。从运动员中收集数据,将它们转换为与他们的体育绩效相关的有用信息(例如,他们的步态类型),并将信息传递给教练支持的增强。经常检查站立,步行和跑步的类型。两种跑步,慢跑和冲刺缺乏研究仍然存在。在这项工作中,站立,行走,慢跑和冲刺被分类为单个惯性磁性测量单元,该单元放置在树干的新位置。使用不同的加速度计,陀螺和磁力计数据以及不同分类器(Nai've Bayes,K-Collect邻居,支持向量机,自适应增强)之间的分类系统之间进行了比较。在从15名男性受试者收集数据后,数据被预处理,提取并选择特征,并将数据分类。所有分类系统都是成功的。均值真正的阳性率为95.68%±1.80%,使用加速度计和陀螺数据以及Nai ve贝雷斯分类器的分类系统最佳。分类系统可用于体育和体育性能分析中的应用。

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