Enhance motor imagery EEG classification using DWT and chirplet transform.

IF 1.9 4区医学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-08-11 DOI:10.1080/10255842.2026.2704678

Swati Patil, Deepali Sultane, Prashant K Shah

引用次数: 0

Abstract

Brain Computer Interfaces promote seamless interaction between individuals with movement limitations and their surrounding environment by transforming electroencephalography signals derived using Motor Imagery. The procedure relies on accurately classifying various MI activities, which requires dependable approaches for EEG signal classification to be continuously improved. In this paper, discrete wavelet transform, and chriplet transform are proposed to enhance the performance of test system with demonstrating critical importance of time-related data and is implemented in visual studio code python. The proposed method holds 91% efficiency, accuracy 94.8% for CBCIC and 93.72% for BCI Competition IV Dataset with response time of 1.03 sec.

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利用小波变换和小波变换增强运动图像脑电分类。

脑机接口通过转换由运动图像产生的脑电图信号，促进运动受限个体与其周围环境之间的无缝交互。该过程依赖于对各种脑梗死活动的准确分类，这需要不断改进可靠的脑电信号分类方法。本文提出了离散小波变换和小波变换来提高测试系统的性能，并在visual studio代码python中实现了时间相关数据的重要性。该方法对CBCIC数据集的效率为91%，准确率为94.8%，对BCI Competition IV数据集的准确率为93.72%，响应时间为1.03秒。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Methods in Biomechanics and Biomedical Engineering 工程技术-工程：生物医学

CiteScore

4.10

自引率

6.20%

发文量

179

审稿时长

4-8 weeks

期刊介绍： The primary aims of Computer Methods in Biomechanics and Biomedical Engineering are to provide a means of communicating the advances being made in the areas of biomechanics and biomedical engineering and to stimulate interest in the continually emerging computer based technologies which are being applied in these multidisciplinary subjects. Computer Methods in Biomechanics and Biomedical Engineering will also provide a focus for the importance of integrating the disciplines of engineering with medical technology and clinical expertise. Such integration will have a major impact on health care in the future.