中文摘要：

针对动力型下肢设备存在的运动模式识别率低的问题,设计了一种可穿戴式路况识别系统。通过安装在腰部的便携式激光距离传感器和惯性测量传感器分别采集激光距离信息和地形高度信息,利用小波去噪算法对所采集的数据进行处理,提取特征值,最后选择训练简单、结构清晰的概率神经网络进行路况识别。实验结果表明,该便携式系统能有效识别平地、上楼、下楼、上坡和下坡五种路况并提高识别精度,证明了将可穿戴式路况识别系统应用于假肢或助行器等动力型下肢设备环境感知系统的有效性和可行性。

英文摘要：

As movement pattern recognition of powered lower limb devices is poor,a wearable terrain recognition system is designed. The portable laser distance sensor and inertial measurement sensor installed in the waist are used to collect laser distance and terrain height information,and then the collected data is processed by wavelet denoising algorithm; the feature value is extracted,finally,probabilistic neural network is used to complete terrain recognition. The experimental results show that the portable system can effectively identify five terrains of ground,upstairs,downstairs,upslope and downslope. It proves that this wearable terrain recognition system is effective and feasible for powered lower limb devices.