Journal ArticleDOI
Robust EOG-based saccade recognition using multi-channel blind source deconvolution
TLDR
A robust EOG-based saccade recognition using the multi-channel convolutional independent component analysis (ICA) method and a constraint direction of arrival (DOA) algorithm that can automatically adjust the order of eye movement sources according to the constraint angle are proposed.Abstract:
Human activity recognition (HAR) is a research hotspot in the field of artificial intelligence and pattern recognition The electrooculography (EOG)-based HAR system has attracted much attention due to its good realizability and great application potential Focusing on the signal processing method of the EOG-HAR system, we propose a robust EOG-based saccade recognition using the multi-channel convolutional independent component analysis (ICA) method To establish frequency-domain observation vectors, short-time Fourier transform (STFT) is used to process time-domain EOG signals by applying the sliding window technique Subsequently, we apply the joint approximative diagonalization of eigenmatrix (JADE) algorithm to separate the mixed signals and choose the "clean" saccadic source to extract features To address the problem of permutation ambiguity in a case with a six-channel condition, we developed a constraint direction of arrival (DOA) algorithm that can automatically adjust the order of eye movement sources according to the constraint angle Recognition experiments of four different saccadic EOG signals (ie up, down, left and right) were conducted in a laboratory environment The average recognition ratios over 13 subjects were 9566% and 9733% under the between-subjects test and the within-subjects test, respectively Compared with "bandpass filtering", "wavelet denoising", "extended infomax algorithm", "frequency-domain JADE algorithm" and "time-domain JADE algorithm, the recognition ratios obtained relative increments of 46%, 349%, 285%, 281% and 291% (within-subjects test) and 491%, 343%, 221%, 224% and 228% (between-subjects test), respectively The experimental results revealed that the proposed algorithm presents robust classification performance in saccadic EOG signal recognitionread more
Citations
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Journal ArticleDOI
A Comparative Experimental Study Between Instantaneous and Convolutional BSS Models for Saccadic EOG Signal Separation
TL;DR: The quality of the saccadic signals separated using the convolutional model was higher than that achieved using the instantaneous model, and can serve as a valuable reference for multichannel EOG analysis and application.
A hybrid ICA-wavelet transform for automated artefact removal in EEG-based emotion recognition
TL;DR: In this article, an automatic independent component analysis (ICA) procedure, a hybrid ICA - wavelet transform technique (ICA-W), for artefact removal from EEG correlated to emotional-state was presented.
Proceedings Article
Mouse cursor control system using electrooculogram signals
Tamura,Miyashita,Tanno +2 more
TL;DR: The mouse cursor control system for Amyotrophic Lateral Sclerosis patients using electrooculogram signals is introduced and the algorithm corresponding to the drift is proposed, and the effectiveness of the system is tested.
Journal ArticleDOI
Music Signal Recognition Based on the Mathematical and Physical Equation Inversion Method
Wei Jiang,Dong Sun +1 more
TL;DR: In this article, the authors proposed a method that can help music learners in music learning and music composition by using the mathematical equation inversion method, which is aimed at designing a method for single note recognition.
References
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Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Book
Electric Fields of the Brain: The Neurophysics of Eeg
Paul L. Nunez,Erich Harth +1 more
TL;DR: In this article, the authors present an overview of the physics-EEG interface, including the physics of electromagnetic fields and EEG, as well as EEG-based recording strategies, reference issues, and dipole localization.
Journal ArticleDOI
Electric Fields of the Brain: The Neurophysics of EEG
TL;DR: In their book the authors present mathematical, physical, physiological, engineering, and medical facts in an effort to diminish a communication gap amongst electroencephalographers, engineers, and physicists.
Book ChapterDOI
Activity Recognition in the Home Using Simple and Ubiquitous Sensors
TL;DR: Preliminary results on a small dataset show that it is possible to recognize activities of interest to medical professionals such as toileting, bathing, and grooming with detection accuracies ranging from 25% to 89% depending on the evaluation criteria used.
Journal ArticleDOI
Eye Movement Analysis for Activity Recognition Using Electrooculography
TL;DR: The work demonstrates the promise of eye-based activity recognition (EAR) and opens up discussion on the wider applicability of EAR to other activities that are difficult, or even impossible, to detect using common sensing modalities.