지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
This paper investigates the impact of Riemannian Procrustes Analysis (RPA) on enhancing the classification performance of SPD-Net when applied to EEG signals across different sessions and subjects. EEG signals, known for their inherent individual variability, are initially transformed into Symmetric Positive Definite (SPD) matrices, which are natu- rally represented on a Riemannian manifold. To mitigate the variability between sessions and subjects, we employ RPA, a method that geometrically aligns the statistical distributions of these matrices on the manifold. This alignment is designed to reduce individual differences and improve the accuracy of EEG signal classification. SPD-Net, a deep learning archi- tecture that maintains the Riemannian structure of the data, is then used for classification. We compare its performance with the Minimum Distance to Mean (MDM) classifier, a conventional method rooted in Riemannian geometry. The ex- perimental results demonstrate that incorporating RPA as a preprocessing step enhances the classification accuracy of SPD-Net, validating that the alignment of statistical distributions on the Riemannian manifold is an effective strategy for improving EEG-based BCI systems. These findings suggest that RPA can play a role in addressing individual variability, thereby increasing the robustness and generalization capability of EEG signal classification in practical BCI applications.
목차
등록된 정보가 없습니다.
참고문헌 (0)
참고문헌 신청함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Fundamental requirements for performing electroencephalography
Annals of Clinical Neurophysiology
2017 .07
-
Miniaturization for wearable EEG systems: recording hardware and data processing
Biomedical Engineering Letters (BMEL)
2022 .08
-
Predicting Working Memory Capacity in Older Subjects Using Quantitative Electroencephalography
PSYCHIATRY INVESTIGATION
2018 .01
-
Serum PD-1 Levels Change with Immunotherapy Response but Do Not Predict Prognosis in Patients with Hepatocellular Carcinoma
Journal of Liver Cancer
2019 .01
-
CNN based classifi cation of motor imaginary using variational mode decomposed EEG-spectrum image
Biomedical Engineering Letters (BMEL)
2021 .08
-
Fast Eating Speed Increases the Risk of Endoscopic Erosive Gastritis in Korean Adults
Korean Journal of Family Medicine
2015 .01
-
Electroencephalography for the diagnosis of brain death
Annals of Clinical Neurophysiology
2017 .07
-
Dual deep neural network-based classifiers to detect experimental seizures
The Korean Journal of Physiology & Pharmacology
2019 .01
-
Wearable EEG and beyond
Biomedical Engineering Letters (BMEL)
2019 .01
-
An EEG-based Brain Mapping to Determine Mirror Neuron System in Patients with Chronic Stroke during Action Observation
대한물리치료학회지(JKPT)
2015 .01
-
무인항공기시스템과 인적 요인
항공우주의학회지
2016 .08
-
Electroencephalographic Abnormalities in the Screening for Pilot Applicants in Korea
Journal of Clinical Neurology
2018 .01
-
학습과 기억의 뇌파
생물정신의학
2016 .01
-
Sleep and REM evaluation using EEG and EMG with moving window analysis in insomnia animal model
한국실험동물학회 학술발표대회 논문집
2016 .02
-
수면 뇌파-기능자기공명영상 동기화 측정과 신호처리 기법을 통한 수면 단계별 뇌연결망 연구
수면정신생리
2018 .01
-
Computational electroencephalography analysis for characterizing brain networks
Annals of Clinical Neurophysiology
2020 .01
-
뇌파 기반 개인 인증 시스템 개발
의공학회지
2018 .01
-
Prognostic impact of serum soluble PD-1 and ADV score for living donor liver transplantation in patients with previously untreated hepatocellular carcinoma
Annals of Surgical Treatment and Research
2022 .01
-
뇌졸중 환자의 작업치료 중재 결과를 측정하기 위해 사용된 뇌전도(Electroencephalography)에 대한 문헌 고찰
재활치료과학
2018 .01
-
뇌파를 이용한 두개천골요법 기반 베개의 수면유도 효과 검증
의공학회지
2018 .01
최근 본 자료
댓글(0)
0