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THE EFFECT OF WINDOW LENGTH ON THE CLASSIFICATION OF DYNAMIC ACTIVITIES THROUGH A SINGLE ACCELEROMETER

机译:窗口长度对单头加速度计动态活动分类的影响

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摘要

This paper investigates how different window sizes for feature extraction and classification affect the accuracy of daily living locomotors activity recognition through accelerometers. A comprehensive data set was collected from 9 healthy subjects performing walk, stair descending and stair ascending while carrying an accelerometer on the waist. Nearest neighbor based classification has been used because of its simplicity and flexibility. The findings show that, by increasing window length, the system accuracy increases, but it produces delays in real time detection/alert of the activity. From the experiments it is concluded that a 2 seconds (2 s) time window may represent a trade-off for the detection of these mentioned activities in a real-time scenario, as it produces 91.7 percent of accuracy.
机译:本文研究了用于特征提取和分类的不同窗口大小如何通过加速度计影响日常生活中的运动活动识别的准确性。收集了来自9名健康受试者的综合数据集,这些受试者在腰部携带加速计的同时进行步行,楼梯下降和楼梯上升。由于其简单性和灵活性,已使用基于最近邻居的分类。研究结果表明,通过增加窗口长度,系统精度会提高,但会在实时检测/警报活动方面产生延迟。从实验得出的结论是,2秒(2 s)的时间窗口可能代表了在实时情况下检测上述活动的折衷方案,因为它可产生91.7%的准确度。

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