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Application of Nonlinear State Estimation Methods for Sport Training Support

机译:非线性状态估计方法在运动训练支持中的应用

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Typical understanding of healthcare concerns treatment, diagnosis and monitoring of diseases. But healthcare also includes well-being, healthy lifestyle, and maintaining good body condition. One of the most important factor in this respect is physical activity. Modern techniques of data acquisition and data processing enable development of advanced systems for physical activity support with use of measurement data. The need for reliable estimation routines stems from the fact, that many widely available (for bulk customers) measurements devices are not reliable and measured signals are contaminated by the noise. One of the most important variables for physical activity monitoring is the velocity of a moving object (e.g. velocity of selected parts of a body such as elbows). Apart from intensive use of system identification, optimization and control techniques for physical training support, we applied Kalman filtering technique in order to estimate speed of moving part of a body.
机译:对医疗保健的典型理解涉及疾病的治疗,诊断和监测。但是,医疗保健还包括幸福,健康的生活方式和保持良好的身体状况。在这方面最重要的因素之一是体育锻炼。数据采集​​和数据处理的现代技术可以通过使用测量数据来开发先进的系统,以进行体育活动支持。对可靠的估算程序的需求源于以下事实:许多广泛使用的(对于大量客户而言)测量设备不可靠,并且测量信号被噪声污染。进行体育活动监视的最重要变量之一是运动物体的速度(例如,身体选定部位(例如肘部)的速度)。除了大量使用系统识别,优化和控制技术来提供体育锻炼支持外,我们还应用了卡尔曼滤波技术来估计身体移动部位的速度。

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