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Video analysis validation of a real-time physical activity detection algorithm based on a single waist mounted tri-axial accelerometer sensor

机译:基于单腰安装三轴加速度传感器的实时体育活动检测算法的视频分析验证

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We have validated a real-time activity classification algorithm based on monitoring by a body worn system which is potentially suitable for low-power applications on a relatively computationally lightweight processing unit. The algorithm output was validated using annotation data generated from video recordings of 20 elderly volunteers performing both a semi-structured protocol and a free-living protocol. The algorithm correctly identified sitting 75.1% of the time, standing 68.8% of the time, lying 50.9% of the time, and walking and other upright locomotion 82.7% of the time. This is one of the most detailed validations of a body worn sensor algorithm to date and offers an insight into the challenges of developing a real-time physical activity classification algorithm for a tri-axial accelerometer based sensor worn at the waist.
机译:我们已经验证了基于人体穿戴系统进行监视的实时活动分类算法,该系统可能适用于在计算相对较轻的处理单元上进行的低功耗应用。使用从20位执行半结构协议和自由生活协议的老年志愿者的视频记录中生成的注释数据,验证了算法输出。该算法正确地识别出75.1%的时间坐着,68.8%的时间站着,50.9%的时间躺着以及82.7%的步行和其他直立运动。这是迄今对人体穿戴式传感器算法进行的最详细的验证之一,并为开发针对腰部佩戴的基于三轴加速度计的传感器开发实时身体活动分类算法的挑战提供了深刻的见识。

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