【摘要】 步态是指人体走路时的姿态,步态识别是近年来生物特征识别领域一个备受关注的研究方向。步态阶段的区分是步态识别的重要内容。以隐马尔科夫模型(HMM)为基础,基于安装在膝关节的编码器和大腿部的加速度传感器,在外骨骼辅助行走中识别步态的不同阶段。首先进行数据预处理和特征提取;其次对隐马尔科夫步态识别算法进行设计,包括结构的建立、参数的训练和最终的识别;最后对性能进行评估,总体正确率达到91.06%,说明HMM用于步态阶段识别具有较好的性能。更多还原

【Abstract】 Human gait is the pattern of walking of human being.Recently,gait recognition has been a hot research point in many research fields.Specially,the distinction of gait segmentation plays a key role on gait recognition.The use of HMMs in this paper aimed at recognizing different gait segmentation by an encoder on knee-joint and a leg-mounted accelerometer.Firstly,the methods of data pre-processing and feature extraction were used.Secondly,a model based on HMM was presented for recognizing gait segmentation,including model structure,parameters training,gait recognition.Thirdly,performance evaluation of the gait recognition was conducted,obtaining total accuracy of 91.06%,proving that HMM can accurately recognize gait segmentation and has good performance.更多还原