中文摘要：

背景：在主动型膝上假肢的研究中，现有的运动模式识别方法已经取得了良好的识别效果，但仍需进一步的提高识别精度和缩小响应时间。目的：建立一个基于随机森林算法的地形识别系统，实现对受试者前方地形的识别，从而获得受试者在步入该地形时的运动模式，应用于假肢的控制当中。方法：将激光距离传感器和惯性测量单元固定在人体腰部位置，分别采集前方地形信息和人体的运动信息。对采集到的数据进行滤波处理，并提取特征值。利用随机森林算法根据处理过后的数据建立分类器，并进行路况识别。结果与结论：结果表明，该地形识别系统能够有效的识别出日常行走中常见的平地、上楼梯、下楼梯、上斜坡和下斜坡等5种路况，在主动型膝上假肢的控制中将会发挥重大作用。

英文摘要：

BACKGROUND： In the research of the active above-knee prosthesis, the existing motion pattern recognition methods have shown promising results, but the further improvement of the recognition accuracy and the reduction of the response time are still necessary. OBJECTIVE： To establish a terrain recognition system based on the random forest algorithm, achieve the identification of the front terrain, and obtain the motion mode of the subject on the terrain for the control of artificial limb. METHODS： A laser distance sensor and an inertial measurement unit sensor were fixed on the waist to collect the terrain information and human motion signals. The collected data were filtered and the characteristic values were extracted from the data. The random forest algorithm was applied in the establishment of the classifier, which was used to recognize the terrain. RESULTS AND CONCLUSION： The results showed that the terrain recognition system could recognize level ground, stair ascent/descent and ramp ascent/descent at a high accuracy, which could contribute to the control of the active above-knee prosthesis.