Construction of an Evaluation Model for High Arch Anomaly Based on BP Neural Network
Wang Xinting1,2*, Wang Qi1,2, Xu Dandi1,2, Qiu Nian1,2, Ren Jianping1,2
1(School of Mechanical Engineering, Tianjin University of Science and Technology, Tianjin 300222,China) 2 (Tianjin Key Laboratory of Integrated Design and On-Line Monitoring for Light Industry & Food Machinery and Equipment, Tianjin 300222, China)
王新亭, 王琪, 徐聃弟, 邱念, 任建平. 基于BP神经网络的高足弓异常程度评价模型的构建[J]. 中国生物医学工程学报, 2021, 40(2): 252-256.
Wang Xinting, Wang Qi, Xu Dandi, Qiu Nian, Ren Jianping. Construction of an Evaluation Model for High Arch Anomaly Based on BP Neural Network. Chinese Journal of Biomedical Engineering, 2021, 40(2): 252-256.
[1] Chen WP,Tang FT,Ju CW.Stress distribution of the foot during mid-stance to push-off in barefoot gait:A 3-D finite element analysis[J].Clinical Biomechanics,2001,16:614-620. [2] Tong JWK.Kong PW.Association between foot type and lower extremity injuries:systematic literature review with meta-analysis [J].Journal of Orthopaedic Sports Physical Therapy,2013,43(10):700-714. [3] Neal BS,Griffiths IB,Dowling GJ,et al.Foot posture as a risk factor for lower limb overuse injury:A systematic review and meta-analysis [J].Journal of Foot and Ankle Research,2014,7(1):55-67. [4] Hegedus EJ,Cook C,Fiander C,et al.Measures of arch height and their relationship to pain and dysfunction in people with lower limb impairments[J].Physiotherapy Research International,2010,15(3):160-166. [5] Walker M,Fan HJ.Relationship between foot pressure pattern and foot type[J].Foot & Ankle International,1998,19(6):379-383. [6] Burns J,Crosbie J,Hunt A,et al.The effect of pes cavus on foot pain and plantar pressure[J].Clinical Biomechanics,2005,20(9):877-882. [7] 张新语,霍洪峰.足型测量方法及足型特征研究进展[J].中国康复医学杂志,2019,34(7):875-879. [8] 黄玉华.基于BP神经网络的足底压力信号模式分类[D].南京:南京大学,2011. [9] 庞宇峰,黄娟,徐蓓峥,等.病态嗓音的定量分析及人工神经网络识别[J].临床耳鼻咽喉头颈外科杂志,2017,31(2):100-102. [10] Barton G,Lisboa P,Lees A,et al.Gait quality assessment using self-organising artificial neural networks[J].Gait & Posture,2007,25(3):374-379. [11] Nazmi N,Abdul Rahman MA,Yamamoto SI,et al.Walking gait event detection based on electromyography signals using artificial neural network[J].Biomedical Signal Processing and Control,2019,47: 334-343. [12] 车前子,郑启文,陈思,等.基于人工神经网络算法的2型糖尿病发病风险预测模型的构建[J].中国慢性病预防与控制,2020,28(4):274-279. [13] Carmo AA,Kleiner AF,Costa PH,et al. Three-dimensional kinematic analysis of upper and lower limb motion during gait of post-stroke patients[J].Brazilian Journal of Medical and Biological Research,2012,45(6):537-545. [14] 林芳富,李艳,宋武.基于因子分析的倒钟摆模型足底压力分布研究[J].人类工效学,2019,25(2):6-13. [15] 闻新,张兴旺,朱亚萍,等.智能故障诊断技术:MATLAB应用[M].北京:北京航空航天大学出版社,2015. [16] Oh SE,Choi A,Mun JH.Prediction of ground reaction forces during gait based on kinematics and a neural network model[J].Journal of Biomechanics,2013,46(14),2372-2380.