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Human Motion Recognition Based on Acceleration Characteristics*

机译:基于加速度特性的人体运动识别*

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In recent years, the pedometer device has been used more and more widely in smart phones. In this paper, an algorithm for human motion recognition and detection is designed according to the acceleration transducer built in the mobile phone. According to the user’s habit of placing the phone in the jacket pocket (there is no restriction on the direction of the phone), we can read out the data of the three-axis acceleration sensor in the exercise mode, this article sets five human body movement modes: walking mode, running mode, upstairs mode, downstairs mode, and stationary state. The collected data are processed and multiple sets of features are extracted for principal component analysis. Then the dimensionality-reduced feature data set is distinguished and identified as data input. After analyzing and comparing the algorithm, support vector machine (SVM) is used to classify and model. In the process of classification, parameters of SVM are optimized in order to improve classification accuracy.
机译:近年来,计步器已在智能手机中得到越来越广泛的使用。本文根据手机内置的加速度传感器,设计了一种人体运动识别与检测算法。根据用户将手机放在夹克口袋中的习惯(对手机的方向没有限制),我们可以在锻炼模式下读出三轴加速度传感器的数据,本文设置了五个人体运动模式:步行模式,跑步模式,上楼模式,楼下模式和静止状态。处理收集的数据并提取多组特征以进行主成分分析。然后,将降维特征数据集进行区分并将其标识为数据输入。在分析和比较算法后,使用支持向量机(SVM)进行分类和建模。在分类过程中,对支持向量机的参数进行了优化,以提高分类的准确性。

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