计算机科学 ›› 2016, Vol. 43 ›› Issue (7): 285-289.doi: 10.11896/j.issn.1002-137X.2016.07.052
张向刚,唐海,付常君,石宇亮
ZHANG Xiang-gang, TANG Hai, FU Chang-jun and SHI Yu-liang
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。
| [1] Jiang Ming,Wang Zhe-long,Liu Xiao-bo,et al.Research on human daily activity Recognition method based on BSN and CHMMs[J].Journal of Dalian University of Technology,2013,53(1):121-126(in Chinese) 姜鸣,王哲龙,刘晓博,等.基于BSN和CHMMs的人体日常动作识别方法研究[J].大连理工大学学报,2013,53(1):121-126 [2] Ugulino W,Cardador D,Vega K,et al.Wearable computing:accelerometers’ data classification of body postures and movements[M]∥Advances in Artificial Intelligence-SBIA 2012.Springer Berlin Heidelberg,2012:52-61 [3] Yang A Y,Jafari R,Sastry S S,et al.Distributed recognition of human actions using wearable motion sensor networks[J].Journal of Ambient Intelligence and Smart Environments,2009,1(2):103-115 [4] Meng Ming,She Qing-shan,Luo Zhi-zeng.The application ofHMM in gait recognition using lower limb SEMG[J].J.Huazhong Univ.of Tech.Sci.(Natural Science Edition),2011,39 (2):176-179(in Chinese) 孟明,佘青山,罗志增.HMM在下肢表面肌电信号步态识别中的应用[J].华中科技大学学报(自然科学版),2011,39(2):176-179 [5] Gao Yun-yuan,Meng Ming,Luo Zhi-zeng,et al.Multi-Mode and Gait Phase Recognition of Lower Limb Prosthesis Based on Multi-Source Motion Information[J].Chinese Journal of Sensors and Actuators,2012,24(11):1574-1578(in Chinese) 高云园,孟明,罗志增,等.利用多源运动信息的下肢假肢多模式多步态识别研究[J].传感技术学报,2012,24(11):1574-1578 [6] Zhang Jin-yu,Wang Lan,Zhang Li-xun.Research on real-time gait phase measuring based on multi-sensor[J].Harbin Engineering University,2007,8(2):218-221(in Chinese) 张今瑜,王岚,张立勋.基于多传感器的实时步态检测研究[J].哈尔滨工程大学学报,2007,28(2):218-221 [7] Novak D,Reberek P,De Rossi S M M,et al.Automated detection of gait initiation and termination using wearable sensors[J].Medical Engineering & Physics,2013,35(12):1713-1720 [8] Alaqtash M,Yu H,Brower R,et al.Application of wearable sen- sors for human gait analysis using fuzzy computational algorithm[J].Engineering Applications of Artificial Intelligence,2011,24(6):1018-1025 [9] De Rossi S M M,Crea S,Donati M,et al.Gait segmentation using bipedal foot pressure patterns[C]∥2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).IEEE,2012:361-366 [10] Mannini A,Sabatini A M.A hidden Markov model-based technique for gait segmentation using a foot-mounted gyroscope[C]∥2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.2011:4369-4373 [11] Rabiner L.A tutorial on hidden Markov models and selected applications in speech recognition[J].Proceedings of the IEEE,1989,77(2):257-286 [12] Wilson A D,Bobick A F.Parametric hidden markov models for gesture recognition[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1999,21(9):884-900 [13] Bao L,Intille S S.Activity recognition from user-annotated ac-celeration data[M]∥Pervasive Computing.Springer Berlin Heidelberg,2004:1-17 [14] Fawcett T.An introduction to ROC analysis[J].Pattern recognition letters,2006,27(8):861-874 |
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