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Design and implementation of a BSN-based system for plantar health evaluation with exercise load quantification

机译:基于BSN的运动量量化足底健康评估系统的设计与实现

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Background Plantar pressure measurement has become increasingly useful in the evaluation of plantar health conditions thanks to the recent progression in sensing technology. Due to the large volume and high energy consumption of monitoring devices, traditional systems for plantar pressure measurement are only focused on static or short-term dynamic monitoring. It makes them inappropriate for early detections of plantar symptoms usually presented in long-term activities. Methods A prototype of monitoring system based on body sensor network (BSN) is proposed for quantitative assessment of plantar conditions. To further assess the severity of plantar symptoms which can be reflected from the pressure distribution in motion status, an approach to conjoint analysis of pressure distribution and exercise load quantification based on the strike frequency (SF) and heart rate (HR) is also proposed. Results An examination was tested on 30 subjects to verify the capabilities of the proposed system. The estimated correlation rate with reference devices ( (r>0.9) ) and error rate on the average ( (R_{AE} ) of HR and SF indicated equal measuring capabilities as the existing commercial products . Comprised of the conjoint analysis based on HR and SF, the proposed method of exercise load quantification was examined on all subjects’ recordings. Conclusions A prototype of an innovative BSN-based bio-physiological measurement system has been implemented for the long-term monitoring and early evaluation of plantar condition. The experimental results indicated that the proposed system has a great potential value in the applications of long-term plantar health monitoring and evaluation.
机译:背景技术由于传感技术的最新发展,足底压力测量在评估足底健康状况中已变得越来越有用。由于监测装置的体积大和能耗高,传统的足底压力测量系统仅侧重于静态或短期动态监测。它使它们不适合早期发现通常在长期活动中出现的足底症状。方法提出一种基于人体传感器网络(BSN)的监测系统原型,用于定量评估足底状况。为了进一步评估可以从运动状态中的压力分布反映出来的足底症状的严重程度,还提出了一种基于打击频率(SF)和心率(HR)的压力分布和运动负荷量化的联合分析方法。结果对30名受试者进行了考试,以验证所提议系统的功能。与参考设备的估计相关率((r> 0.9 ))和HR和SF的平均值的错误率((R_ {AE})表示与现有商业产品相同的测量能力。在HR和SF方面,对所有受试者的记录进行了运动负荷量化方法的总结结论结论基于BSN的创新生物生理测量系统的原型已被用于长期监测和早期评估足底状况。实验结果表明,该系统在长期足底健康监测与评价中具有很大的应用价值。

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