Research and Development Department, Omron Healthcare Co., Ltd., Ukyo-ku, Kyoto, Japan.
Gait Posture. 2010 Mar;31(3):370-4. doi: 10.1016/j.gaitpost.2010.01.005. Epub 2010 Feb 6.
The purpose of this study was to develop a new algorithm for classifying physical activity into either locomotive or household activities using a triaxial accelerometer. Sixty-six volunteers (31 men and 35 women) participated in this study and were separated randomly into validation and cross-validation groups. All subjects performed 12 physical activities (personal computer work, laundry, dishwashing, moving a small load, vacuuming, slow walking, normal walking, brisk walking, normal walking while carrying a bag, jogging, ascending stairs and descending stairs) while wearing a triaxial accelerometer in a controlled laboratory setting. Each of the three signals from the triaxial accelerometer was passed through a second-order Butterworth high-pass filter to remove the gravitational acceleration component from the signal. The cut-off frequency was set at 0.7 Hz based on frequency analysis of the movements conducted. The ratios of unfiltered to filtered total acceleration (TAU/TAF) and filtered vertical to horizontal acceleration (VAF/HAF) were calculated to determine the cut-off value for classification of household and locomotive activities. When the TAU/TAF discrimination cut-off value derived from the validation group was applied to the cross-validation group, the average percentage of correct discrimination was 98.7%. When the VAF/HAF value similarly derived was applied to the cross-validation group, there was relatively high accuracy but the lowest percentage of correct discrimination was 63.6% (moving a small load). These findings suggest that our new algorithm using the TAU/TAF cut-off value can accurately classify household and locomotive activities.
本研究旨在开发一种新的算法，通过三轴加速度计将体力活动分类为运动或家务活动。66 名志愿者（31 名男性和 35 名女性）参与了这项研究，并随机分为验证组和交叉验证组。所有受试者在受控的实验室环境中佩戴三轴加速度计进行 12 项体力活动（使用个人计算机工作、洗衣、洗碗、搬运小件物品、吸尘、慢走、正常行走、快走、携带包行走、慢跑、爬楼梯和下楼梯）。三轴加速度计的三个信号都通过二阶巴特沃斯高通滤波器，以去除信号中的重力加速度分量。基于运动的频率分析，将截止频率设置为 0.7 Hz。未滤波总加速度（TAU/TAF）与滤波垂直加速度与水平加速度（VAF/HAF）的比值用于确定分类家务和运动活动的截止值。当将验证组得出的 TAU/TAF 判别截止值应用于交叉验证组时，正确判别率的平均百分比为 98.7%。当同样推导出的 VAF/HAF 值应用于交叉验证组时，准确率相对较高，但正确判别率最低为 63.6%（搬运小件物品）。这些发现表明，我们使用 TAU/TAF 截止值的新算法可以准确地对家务和运动活动进行分类。
