集成技术Issue(4)：20-26,7.
几种自适应线性判别分析方法在肌电假肢控制中的应用研究
A Study of Different Linear Discriminant Analysis Methods in Myoelectric Prosthesis Control
摘要
Abstract
When the surface electromyography (sEMG) signals change along with external or internal environment of the human body, general pattern classifiers will lead to a decrease of identification accuracy since they do not update their parameters adaptively. In order to adapt to the time-varying characteristics of sEMG signals, three kinds of adaptive algorithms for updating the parameters of a classifier during the use of artificial limb were introduced to improve the classification accuracy of time-variant sEMG signals. The pilot results of this study show that self-enhancing linear discriminant analysis is an effective solution and cycle substitution linear discriminant analysis presents the best performance but requires a large amount of calculations. The performance of the Kalman adaptive linear discriminant analysis is not prominent when it was used alone, and therefore it needs to be combined with other methods.关键词
表面肌电信号/假肢控制/线性判别分析/自适应方法Key words
sEMG signals/artificial limbs control/linear discriminative analysis/adaptive method引用本文复制引用
赵曜楠,张浩诗,徐礼胜,李光林..几种自适应线性判别分析方法在肌电假肢控制中的应用研究[J].集成技术,2013,(4):20-26,7.基金项目
国家自然科学基金重点项目(61135004)。 （61135004）
