کنفرانس مهندسی برق ایران

صفحه اصلی / سی و یکمین کنفرانس بین المللی مهندسی برق

Kernel-Based Embedded Feature Selection for Motor Imagery Based BCI

نویسندگان :

Mehdi Kamandar¹

1- دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته

کلمات کلیدی :

Brain–computer interface (BCI)،Electroencephalogram (EEG)،(Motor imagery (MI،)،Support vector machine (SVM)،Kernel-target alignment (KTA)،Embedded feature selection،l1 regularization،minibatch proximal gradient ascent

چکیده :

Brain-computer interface (BCI) based on motor imagery (MI) classification using scalp recorded multi-channel EEG signal play a major role in the control of artificial limbs and machines by people with severe disabilities. The most popular features are band power of EEG signals in frequency sub-bands in a relatively wide frequency band (e. g., 8-30 Hz) in different time windows of imagination period. The effectiveness of these features is highly dependent on the sub-bands and time windows adopted, since the optimal sub-bands and time windows is generally subject-specific. The nonlinear support vector machine (SVM) with Gaussian kernel is an excellent classifier for MI classification. In this paper, the SVM with an anisotropic Gaussian kernel with a special scaling factors for each feature is used, instead of one scale factor for all features. The scaling factors are tuned by maximizing the kernel-target alignment criterion with l1 regularization. Some of the scaling factors will be zero after maximization due to l1 regularization, that is equivalent to removing corresponding features from classification processes. Therefore, an embedded feature selection is also done to remove the destructive effect of irrelevant and redundant features. The average accuracy of the SVM classifier with anisotropic Gaussian kernel for four subjects in BCI IV-1 dataset is about 10% more than the SVM with isotropic Gaussian kernel.

لیست مقالات

لیست مقالات بایگانی شده

A New Unsupervised Feature Learning Method for Object Recognition using Prior-Knowledge Data

Ashkan Farrokhi - Hadi Seyedarabi

Brain Tumor Segmentation using Multimodal MRI and Convolutional Neural Network

Nazila Loghmani - Roqaie Moqadam - Armin Allahverdy

Fabrication and performance analysis of a ZnO phototransistor for UV detection

Ghasem Yousefi Simakani - ُSamaneh Hamedi

A Simple Method for Continuous Beam-Steering in SIW based Leaky Wave Antenna

Sina Rezaeeahvanouee - AmirHossein Sadough

Batch(offline) Reinforcement Learning for recommender system

Mohammad Amir Rezaei Gazik - Mehdy Roayaei

A Simulation Case Study of THz Reflection Spectroscopy

Mitra Mirsalehi - Zahra Kavehvash - Mehdi Fardmanesh

Design and Analysis of Three-Step Cyclic Vernier Time-to-Digital Converter

ُSara Mansouri - Hamidreza Rezaee-Dehsorkh - Nassim Ravanshad

Extension Network of Radiomics-based Deeply Supervised U-Net (ERDU) For Prostate Image Segmentation

Mahdi Ashtarian - Karim Faez - Marjan Firouznia - Hamidreza Amindavar

A Novel Image Denoising Algorithm Based on Wavelet and Akamatsu Transforms Using Particle Swarm Optimization

Zeinab Pakdaman - Majid Amini-Valashani - Sattar Mirzakuchaki

Distributed Deep Reinforcement Learning for Radio Resource Management in O-RAN

Ahmad Ahmadi Siahpoush - Vahid Shah-Mansouri

بیشتر

ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.8.0