ESTIMATION OF SPEED AND INCLINE OF WALKING USING NEURAL-NETWORK
ESTIMATION OF SPEED AND INCLINE OF WALKING USING NEURAL-NETWORK
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DOI：
10.1109/19.387322
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发表时间：
1995-06-01
影响因子：
5.6
通讯作者：
SCHUTZ, Y
中科院分区：
文献类型：
--
作者：
AMINIAN, K;ROBERT, P;SCHUTZ, Y
设计了一种便携式数据记录器，用于记录人体行走过程中的加速度。五名受试者首先在跑步机上以不同的速度在水平上行走，并以正和负的倾斜度行走。然后，受试者在室外测试线路上进行了一次包含各种坡度道路的自步速行走，记录的信号被参数化，并找到每个步态周期的行走模式，这些模式被提交给两个神经网络，用于估计坡度和行走速度。结果表明，对所有受试者的倾斜度和速度都有很好的估计，预测倾斜度与实际倾斜度之间的相关性为r = 0.98。最终速度预测误差最大为16%。据我们所知，这些结果构成了第一个速度和倾斜的水平和坡度无约束步行估计。
A portable data logger is designed to record body accelerations during human walking, Five subjects walk first on a treadmill at various speeds on the level, and at positive and negative inclines. Then, the subjects performed a self-pace walking on an outdoor test circuit involving roads of various inclines, The recorded signals are parameterized, and the pattern of walking at each gait cycle is found. These patterns re presented to two neural networks which estimate the incline and the Speed of walking. The results show a good estimation of the incline and the speed for all of the subjects, The correlation between predicted and actual inclines is r = 0.98. End the maximum of speed-predicted error is 16%. To the best of our knowledge these results constitute the first speed and incline estimation of level and slope-unconstrained walking.