title: Real-time estimation and detection of non-linearity in bio-signals using wireless brain-computer interface.
abstract: In this paper, the work is mainly concentrated on removing non-linear parameters to make the physiological signals more linear and reducing the complexity of the signals. This paper discusses three different types of techniques that can be successfully utilised to remove non-linear parameters in EEG and ECG. (i) Transformation technique using Discrete Walsh-Hadamard Transform (DWHT); (ii) application of fuzzy logic control and (iii) building the Adaptive Neuro-Fuzzy Inference System (ANFIS) model for fuzzy. This work has been inspired by the need to arrive at an efficient, simple, accurate and quicker method for analysis of bio-signal.
authors.affiliation: Department of Information and Communication, Anna University of Technology, Coimbatore 641 047, India.
authors.forename: S
authors.initials: S
authors.lastname: Ganesan
authors.affiliation: Department of Electrical and Electronics Engineering, Anna University of Technology, Coimbatore 641 047, India.
authors.forename: T Aruldoss Albert
authors.initials: TA
authors.lastname: Victoire
authors.affiliation: Department of Electronics and Communication Engineering, Perunthalaivar Kamarajar Institute of Engineering and Technology, Karaikkal 609 603, India.
authors.forename: G
authors.initials: G
authors.lastname: Vijayalakshmy
mesh_terms: D000465:Algorithms; D062207:Brain-Computer Interfaces; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D004562:Electrocardiography / Q000379:methods; D004569:Electroencephalography / Q000379:methods; D017143:Fuzzy Logic; D006801:Humans; D016571:Neural Networks, Computer; D012815:Signal Processing, Computer-Assisted
keywords: ANFIS; DWHT; ECG; EEG; adaptive neuro–fuzzy inference system; biosignals; brain–computer interface; discrete Walsh Hadamard transform; electrocardiograms; electroencephalograms; fuzzy control; fuzzy logic; neural networks; nonlinear parameters; nonlinearity; wireless BCI