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Assessment of a Smart Sensing Shoe for Gait Phase Detection in Level Walking

机译:用于水平步行步态检测的智能感应鞋的评估

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摘要

Gait analysis and more specifically ambulatory monitoring of temporal and spatial gait parameters may open relevant fields of applications in activity tracking, sports and also in the assessment and treatment of specific diseases. Wearable technology can boost this scenario by spreading the adoption of monitoring systems to a wide set of healthy users or patients. In this context, we assessed a recently developed commercial smart shoe—the FootMoov—for automatic gait phase detection in level walking. FootMoov has built-in force sensors and a triaxial accelerometer and is able to transmit the sensor data to the smartphone through a wireless connection. We developed a dedicated gait phase detection algorithm relying both on force and inertial information. We tested the smart shoe on ten healthy subjects in free level walking conditions and in a laboratory setting in comparison with an optical motion capture system. Results confirmed a reliable detection of the gait phases. The maximum error committed, on the order of 44.7 ms, is comparable with previous studies. Our results confirmed the possibility to exploit consumer wearable devices to extract relevant parameters to improve the subject health or to better manage his/her progressions.
机译:步态分析,更具体地说是对时空步态参数的动态监测,可以打开活动跟踪,运动以及特定疾病的评估和治疗中的相关应用领域。可穿戴技术可以通过将监视系统的使用范围扩展到广泛的健康用户或患者,从而改善这种情况。在这种情况下,我们评估了最近开发的商用智能鞋FootMoov,用于水平行走中的步态自动步态检测。 FootMoov具有内置的力传感器和三轴加速度计,并能够通过无线连接将传感器数据传输到智能手机。我们开发了一种依赖于力和惯性信息的专用步态相位检测算法。与光学运动捕捉系统相比,我们在自由水平步行条件下和实验室环境中对十名健康受试者进行了智能鞋测试。结果证实了步态阶段的可靠检测。所犯的最大错误约为44.7 ms,与先前的研究相当。我们的结果证实了利用消费者可穿戴设备提取相关参数以改善受试者健康状况或更好地管理其进展的可能性。

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