燕山大学学报2025，Vol.49Issue(4)：294-299,331,7.DOI:10.3969/j.issn.1007-791X.2025.04.002
基于个性化空-频特征的大鼠转向行为脑电解码方法
Individualized space-frequency based method for decoding local field potentials of rats'turning behavior
摘要
Abstract
The local field potential(LFP)signals collected from the rat brain contain much motor-related information.Decoding information helps deepen the understanding of the motor mechanism of the human brain,which is of great value to motor disorder rehabilitation.However,due to the uncontrollable behavior of rats and the low signal-to-noise ratio of LFP signals,the decoding of their turning behavior is still a difficult task in current researches.In this paper,an individualized space-frequency based LFP decoding method is proposed to extract the space-frequency features of the LFP signals by selecting personalized filter bands and personalized spatial filters,and the two behavioral decisions of left turn and right turn are decoded using a support vector machine classifier.The experimental results show that the proposed method extract individualized space-frequency features for two rats on different dates,and achieves average classification accuracies of 75%and 70%in the decoding of turning behavior.关键词
脑机接口/局部场电位/转向行为/空-频特征Key words
brain-computer interface/local field potential/turning behavior/space-frequency feature分类
信息技术与安全科学引用本文复制引用
庄新鑫,赵靖,张保家,任哲兵,王静..基于个性化空-频特征的大鼠转向行为脑电解码方法[J].燕山大学学报,2025,49(4):294-299,331,7.基金项目
国家重点研发计划资助项目(2022YFE0140400) （2022YFE0140400）
国家自然科学基金资助项目(62376241) （62376241）
河北省创新能力提升计划项目(22567619H) （22567619H）
河北省省级科技计划资助项目(236Z2001G) （236Z2001G）
