Fuzzy Adaptive Feedback Regulation for Stumble Pre-warning of Lower Limb ProsthesisBased on the Correlation Analysis
CHEN Guoxing1, GENG Yanli1, LIU Zuojun1,2, YANG Peng1,2
1. School of Control Science and Engineering, Hebei University of Technology, Tianjin 300130, China;
2. Engineering Research Center of Intelligent Rehabilitation, Ministry of Education, Tianjin 300130, China
Prosthesis users are easier to fall down at the early stage. In order to solve this problem, a stumble pre-warning method based on the correlation analysis with fuzzy adaptive feedback regulation is proposed. Support vector machine(SVM) regression method is applied to improving correlation analysis template of different subjects, and the predictive value of two sensors are fused to distinguish stumble. For different patients, the body reaction is different in the case of stumble. A combined forecast algorithm based on fuzzy adaptive variable weight with feedback regulation unit is applied to parameter optimization for the weights of different patients, and the flexibility of stumble pre-warning system for lower limb prosthesis is improved. Finally, the feasibility of the proposed method is demonstrated through analyzing the data collected from several subjects. The experimental results show that the pre-warning correct rate is 95%. The system can be applied to rehabilitation training of patients in the early stage, so as to improve the safety of prosthesis.
[1] 杨鹏,刘作军,耿艳利,等.智能下肢假肢关键技术研究进展[J].河北工业大学学报,2013,42(1):76-80.Yang P, Liu Z J, Geng Y L, et al. Research advance on key technology of intelligent lower limb prosthesis[J]. Journal of Hebei University of Technology, 2013, 42(1):76-80.[2] Popovic D, Stein R B. Optimal control for the active above-knee prosthesis[J]. Annals of Biomedical Engineering, 1991, 19(2):131-150. [3] Sup F, Bohara A, Goldfarb M. Design and control of a powered knee and ankle prosthesis[C]//IEEE International Conference on Robotics and Automation. Piscataway, USA:IEEE, 2007:4234-4139.[4] Huang H, Zhang F, Hargrove L J, et al.Continuous locomotion-mode identification for prosthetic legs based on neuromuscular--mechanical fusion[J]. IEEE Transactions on Biomedical Engineering, 2011, 58(10):2867-2875. [5] Jin D W, Yang J K, Zhang R H, et al.Terrain identification for prosthetic knees based on electromyographic signal features[J]. Tsinghua Science and Technology, 2006, 11(1):74-79. [6] 谭冠政,蔡光超,曾庆冬,等.CIP-I 智能仿生人工腿手持控制系统研究与设计[J].计算机测量与控制,2006,14(1):47-50.Tan G Z, Cai G C, Zeng Q D, et al. Study and design of handhold controller system of CIP-I intelligent bionic artificial leg[J]. Computer Measurement & Control, 2006, 14(1):47-50.[7] 赵丽娜,刘作军,苟斌,等.基于隐马尔可夫模型的动力型下肢假肢步态预识别[J].机器人,2014,36(3):337-341.Zhao L N, Liu Z J, Gou B, et al. Gait pre-recognition of dynamic lower limb prosthesis based on hidden Markov model[J]. Robot, 2014, 36(3):337-341.[8] 杨建坤.大腿假肢穿戴者在滑倒过程中的平衡策略研究及其应用[D].北京:清华大学,2006.Yang J K. Studies on human balance strategy of trans-femoral prosthesis users during slip gait and its application[D]. Beijing:Tsinghua University, 2006.[9] Lawson B E, Varol H A, Sup F, et al. Stumble detection and classification for an intelligent transfemoral prosthesis[C]//32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Piscataway, USA:IEEE, 2010:511-514.[10] Zhang F, D'Andrea S E, Nunnery M J, et al. Towards design of a stumble detection system for artificial legs[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2011, 19(5):567-577. [11] Varol H A, Sup F, Goldfarb M. Multiclass real-time intent recognition of a powered lower limb prosthesis[J]. IEEE Transactions on Biomedical Engineering, 2010, 57(3):542-551. [12] 袁胜发,褚福磊.支持向量机及其在机械故障诊断中的应用[J].振动与冲击,2007,26(11):29-35.Yuan S F,Chu F L.Support vector machines and its applications in machine fault diagnosis[J].Journal of Vibration and Shock,2007,26(11):29-35. [13] 杨锡运,孙宝君,张新房,等.基于相似数据的支持向量机短期风速预测仿真研究[J].中国电机工程学报,2013,32(4):35-41.Yang X Y,Sun B J,Zhang X F,et al.Short-term wind speed forecasting based on support vector machine with similar data[J].Proceedings of the Chinese Society of Electrical Engineering,2013,32(4):35-41. [14] 苟斌,刘作军,赵丽娜,等.基于相关性分析的下肢假肢步行模式预识别方法[J].东南大学学报:自然科学版,2013,43(S1):192-196.Gou B,Liu Z J,Zhao L N,et al.Walking mode pre-judgment of lower limb prosthesis based on correlation analysis[J].Journal of Southeast University:Natural Science Edition,2013,43(S1):192-196. [15] 唐小我,王景,曹长修.一种新的模糊自适应变权重组合预测算法[J].电子科技大学学报,1997,26(3):289-292.Tang X W,Wang J,Cao C X.A new fuzzy adaptive variable weighting algorithm for combination forecasting[J].Journal of University of Electronic Science and Technology of China,1997,26(3):289-292. [16] 何晓庆,蔡娜.基于模糊自适应变权重的经济时间序列组合预测模型研究[J].软科学,2013,27(1):141-144.He X Q,Cai N.Research on combined estimation model construction of economic time series based on the method of fuzzy adaptive variable weight[J].Soft Science,2013,27(1):141-144. [17] 孙广强,姚建刚,谢宇翔,等.基于新鲜度函数和预测有效度的模糊自适应变权重中长期电力负荷组合预测[J].电网技术,2009,33(9):103-107.Sun G Q,Yao J G,Xie Y X,et al.Combination forecast of medium-and long-term load using fuzzy adaptive variable weight based on fresh degree function and forecasting availability[J].Power System Technology,2009,33(9):103-107. [18] 姚成玉,赵佳伟,陈毅强.基于嵌入式系统的室内人体跌倒行为检测方法的实现[J].燕山大学学报,2008,32(6):507-511.Yao C Y,Zhao J W,Chen Y Q.Realization of the detection method for human falling action in room based on embedded system[J].Journal of Yanshan University,2008,32(6):507-511. [19] 石欣,熊庆宇,雷璐宁.基于压力传感器的跌倒检测系统研究[J].仪器仪表学报,2010,31(3):715-720.Shi X,Xiong Q Y,Lei L N.Research on the fall detection system based on pressure sensor[J].Chinese Journal of Scientific Instrument,2010,31(3):715-720.