e-AR传感器在帕金森病患者步态分析中的应用评估

2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Pub Date : 2015-06-09 DOI:10.1109/BSN.2015.7299396

D. Jarchi, Amy Peters, Benny P. L. Lo, E. Kalliolia, I. D. Giulio, P. Limousin, B. Day, Guang-Zhong Yang

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引用次数: 7

摘要

本文基于e-AR传感器提供的加速度数据，分析了帕金森病患者的步态模式。10名PD患者戴着e-AR传感器沿着7米长的人行道行走，每一阶段包括16次重复试验。提出了一种迭代算法，在测量噪声和步态信号持续时间短的情况下产生鲁棒估计。利用CODA运动捕捉系统计算并验证了步进频率作为步态参数。每个患者的步进频率的间歇变异性和患者之间的总体变异性表明，e-AR和CODA系统的估计之间具有良好的一致性。

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Assessment of the e-AR sensor for gait analysis of Parkinson;s Disease patients

This paper analyses gait patterns of patients with Parkinson's Disease (PD) based on the acceleration data given by an e-AR sensor. Ten PD patients wearing the e-AR sensor walked along a 7m walkway and each session contained 16 repeated trials. An iterative algorithm has been proposed to produce robust estimations in the case of measurement noise and short-duration of gait signals. Step-frequency as a gait parameter derived from the estimated heel-contacts is calculated and validated using the CODA motion-capture system. Intersession variability of step-frequency for each patient and the overall variability across patients demonstrate a good agreement between estimations from the e-AR and CODA systems.

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2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)

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