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Combination of Body Sensor Networks and On-Body Signal Processing Algorithms: the practical case of MyHeart project

机译:身体传感器网络和体上信号处理算法的组合:Myheart项目的实际情况

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Smart clothes increase the efficiency of long-term noninvasive monitoring systems by facilitating the placement of sensors and increasing the number of measurement locations. Since the sensors are either garment-integrated or embedded in an unobtrusive way in the garment, the impact on the subject's comfort is minimized. However the main challenge of smart clothing lies in the enhancement of signal quality and the management of the huge data volume resulting from the variable contact with the skin, movement artifacts, non-accurate location of sensors and the large number of acquired signals. This paper exposes the strategies and solutions adopted in the European 1ST project MyHeart to address these problems, from the definition of the body sensor network to the description of two embedded signal processing techniques performing on-body ECG enhancement and motion activity classification.
机译:智能衣服通过促进传感器的放置并增加测量位置的数量来提高长期非侵入监测系统的效率。由于传感器要么在衣服中以不引人注目的方式镶嵌或嵌入,因此对受试者的舒适性的影响最小化。然而,智能服装的主要挑战在于提高信号质量和管理由可变接触与皮肤,运动伪影,传感器的非准确定位和大量获取信号产生的巨大数据量的管理。本文通过身体传感器网络的定义,公开了欧洲第一项目的策略和解决方案,以解决这些问题,从身体传感器网络的定义到执行对身体心电图增强和运动活动分类的两个嵌入式信号处理技术。

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