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Artificial neural networks: a prospective tool for the analysis of psychiatric disorders

C A Galletly, C R Clark, A C McFarlane
1996 Journal of Psychiatry & Neuroscience  
Artificial neural networks can also be used to create models of brain function, providing a paradigm for cognition and the organization of neural systems that demonstrates how changes at the cellular level  ...  These capabilities have been utilized in general medicine, but as yet there has been little application of artificial neural networks in psychiatric research.  ...  Both Zhu and others (1994) and Kloppel (1994) have emphasized the importance of the preprocessing of EEG data. Zhu used the wavelet transformation technique to preprocess the EEG signals.  ... 
pmid:8754592 pmcid:PMC1188780 fatcat:pz2k5q723fgdvizdv22cnq2eyu

Review of EEG-based pattern classification frameworks for dyslexia

Harshani Perera, Mohd Fairuz Shiratuddin, Kok Wai Wong
2018 Brain Informatics  
A critical analysis of the literature is conducted focusing on each framework's (1) data collection, (2) pre-processing, (3) analysis and (4) classification methods.  ...  Electroencephalography (EEG) is one of the upcoming methods being researched for identifying unique brain activation patterns in dyslexics.  ...  Neural networks Neural networks are 'an assembly of several artificial neurons which enables to produce nonlinear decision boundaries' [64] .  ... 
doi:10.1186/s40708-018-0079-9 pmid:29904812 fatcat:idzevcoh5feiffkjoe65ivrq5y

International Federation of Clinical Neurophysiology (IFCN) – EEG research workgroup: Recommendations on frequency and topographic analysis of resting state EEG rhythms. Part 1: Applications in clinical research studies

Claudio Babiloni, Robert J. Barry, Erol Başar, Katarzyna J. Blinowska, Andrzej Cichocki, Wilhelmus H.I.M. Drinkenburg, Wolfgang Klimesch, Robert T. Knight, Fernando Lopes da Silva, Paul Nunez, Robert Oostenveld, Jaeseung Jeong (+3 others)
2019 Clinical Neurophysiology  
In 1999, the International Federation of Clinical Neurophysiology (IFCN) published "IFCN Guidelines for topographic and frequency analysis of EEGs and EPs" (Nuwer et al., 1999).  ...  Here a Workgroup of IFCN experts presents unanimous recommendations on the following procedures relevant for the topographic and frequency analysis of resting state EEGs (rsEEGs) in clinical research defined  ...  Until the end of their life, they had been working for the development of EEG science and its application in Clinical Neurophysiology.  ... 
doi:10.1016/j.clinph.2019.06.234 pmid:31501011 fatcat:psp6t4czorbsndn4gp5m4o3elu

Emotion classification from EEG signals using wearable sensors: pilot test

Alejandro JARILLO-SILVA, Víctor A. GOMEZ-PEREZ, Eduardo A. ESCOTTO-CÓRDOVA, Omar A. DOMÍNGUEZ-RAMÍREZ
2020 ECORFAN journal Bolivia  
The objective of this work is to present a procedure for the classification of basic emotions based on the analysis of EEG signals (electroencephalogram).  ...  For this case, 25 subjects were stimulated, of whom 17 were men and 9 women between 20 and 35 years of age.  ...  Acknowledgments This research work was supported by PRODEP, IDCA 21306, code UNSIS-CA-13 in the 2018 Strengthening of Academic Bodies call.  ... 
doi:10.35429/ejb.2020.12.7.1.9 fatcat:xgpci5yjyja4pfp5n3v6nww3mu

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

Gys Meiring, Hermanus Myburgh
2015 Sensors  
An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems.  ...  This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s151229822 pmid:26690164 pmcid:PMC4721742 fatcat:jpvbcqf775f2xiapw27226q6zm

A Proposal for a Data-Driven Approach to the Influence of Music on Heart Dynamics

Ennio Idrobo-Ávila, Humberto Loaiza-Correa, Flavio Muñoz-Bolaños, Leon van Noorden, Rubiel Vargas-Cañas
2021 Frontiers in Cardiovascular Medicine  
Finally, a framework is introduced for analysis of data and signals, based on both conventional as well as data-driven AI tools.  ...  AI is able to study big data at a single stroke, can be applied to different types of data, and is capable of generalisation and so is considered the main tool in the analysis.  ...  Convolutional neural networks (CNN) are the most used deep learning algorithms in analysis of several biological signals such as EEG, EMG, and ECG (179).  ... 
doi:10.3389/fcvm.2021.699145 pmid:34490368 pmcid:PMC8417899 fatcat:5dhubhpe5zhnrcvhgyp3pp2pti

Brain Computer Interfaces, a Review

Luis Fernando Nicolas-Alonso, Jaime Gomez-Gil
2012 Sensors  
Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the  ...  Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer  ...  Acknowledgements This work was partially supported by the regional 2010 Research Project Plan of the Junta de Castilla y León, (Spain), under project VA034A10-2.  ... 
doi:10.3390/s120201211 pmid:22438708 pmcid:PMC3304110 fatcat:rinslsoovba4hizv3ugwdy6g2e

Technology Insight: neuroengineering and epilepsy—designing devices for seizure control

William C Stacey, Brian Litt
2008 Nature Clinical Practice Neurology  
New implantable antiepileptic devices, which are currently under development and in pivotal clinical trials, hold great promise for improving the quality of life for millions of people with epileptic seizures  ...  A broad range of strategies is currently being investigated, using various modes of control and intervention in an attempt to stop seizures.  ...  Over the past 10 years, many strategies for analyzing and predicting seizures have been evaluated, including many nonlinear and chaos measurements, wavelet decompositions, machine learning, and other methods  ... 
doi:10.1038/ncpneuro0750 pmid:18301414 pmcid:PMC2904395 fatcat:f5xqum5lwvhqhntqyfngzoe3yq

Proceedings: ISBET 200 – 14th World Congress of the International Society for Brain Electromagnetic Topography, November 19-23, 2003

Yoshio Okada
2003 Brain Topography  
The BESA (Brain Electrical Source Analysis) program provides a large variety of tools for the complete analysis of EEG and MEG recordings.  ...  Signal-space separation (SSS) is applied for head movement correction and noise compensation. For method developers, MATLAB interface exists for MEG/EEG, MRI, MCE and dipole data.  ...  Spherical head models were used for both modalities. We show results for the combined analysis, and compare these to results for the individual MEG and EEG analyses.  ... 
doi:10.1023/b:brat.0000019284.29068.8d fatcat:tpvp3dcojrczjkuzcu3xefyizy

Brain–Computer Interfaces for Human Augmentation

Davide Valeriani, Caterina Cinel, Riccardo Poli
2019 Brain Sciences  
The field of brain–computer interfaces (BCIs) has grown rapidly in the last few decades, allowing the development of ever faster and more reliable assistive technologies for converting brain activity into  ...  control signals for external devices for people with severe disabilities [...]  ...  Acknowledgments: This research was supported by the European Fund for Regional Development (EFRD-or EFRE in German) under Grants GE-1-1-047 and IT-1-2-001.  ... 
doi:10.3390/brainsci9020022 pmid:30682766 pmcid:PMC6406539 fatcat:4kjekrytqrcd7h4egrqlxsdbpq

28th Annual Computational Neuroscience Meeting: CNS*2019

2019 BMC Neuroscience  
We have recently revealed the presence of dynamical invariants in the pyloric CPG in the form of cycle-by-cycle linear relations among specific time intervals and the instantaneous period [4].  ...  The computer then performed online event detection on the signals and forwarded this information to the robot via Bluetooth connection, accurately preserving the temporal structure of the intervals building  ...  Recurrent Artificial Neural Networks (RNNs) are popular models for neural structures in motor control.  ... 
doi:10.1186/s12868-019-0538-0 fatcat:3pt5qvsh45awzbpwhqwbzrg4su

Track C

2014 Biomedical Engineering  
As the determination of suitable and individualized parameter values for myoelectric-controlled human-machine interfaces is time-consuming, this work presents an incremental parameter adaptation scheme  ...  In experiments it is validated for two scenarios simulating inappropriate parameter values.  ...  The author would like to thank Christopher Dörr, THM, for helpful discussions and Youssef Belhoucine, THM, for help with ECG recording.  ... 
doi:10.1515/bmt-2014-5002 pmid:25385887 fatcat:duiajlu3i5gdffz5o4extkvyjm

ACNP 58th Annual Meeting: Poster Session III

2019 Neuropsychopharmacology  
Methods: To assess the effectiveness and safety of MDMAassisted psychotherapy for reducing symptoms of PTSD, a systematic review and meta-analysis was undertaken.  ...  excluded and genotype was adjusted for in statistical analysis.  ...  W49 Methods: Recently a new technique-convolutional neural networks (CNN), which is a highly modifiable artificial intelligencebased image segmentation technique pioneered in the field of computer vision  ... 
doi:10.1038/s41386-019-0547-9 pmid:31801974 pmcid:PMC6957926 fatcat:dd7d43ysfvc5bbbstfl73szya4

Intelligent Transportation and Control Systems Using Data Mining and Machine Learning Techniques: A Comprehensive Study

Nawaf Alsrehin, Ahmad F. Klaib, Aws Magableh
2019 IEEE Access  
This study aims to explore and review the data mining and machine learning technologies adopted in research and industry to attempt to overcome the direct and indirect traffic issues on humanity and societies  ...  It has a direct impact on drawing a clear path for new traffic management propositions.  ...  , PCA, nearest neighbor approach, Kalman filtering, clustered neural network, wavelet neural network, k-NN and Linearly Sewing Principle Components, and 3) Image processing techniques.  ... 
doi:10.1109/access.2019.2909114 fatcat:k3kbfxezdvhihgg2g76vv5xxqq

Tecnologias, Técnicas e Tendências em Engenharia Biomédica [article]

Adriano de Oliveira Andrade, Alcimar Barbosa Soares, Alexandre Cardoso, Edgard Afonso Lamounier
2022 Zenodo  
Acknowledgement This research was part of the DFG/TR233/12 -"Advancement and Systematic Validation of an Automated Pain Recognition System on the Basis of Facial Expression and Psychobiological Parameters  ...  Acknowledgments The authors would like to thank the FAPESC foundation for the financial support and UDESC for the institutional support. We also thank Dr.  ...  Another powerful tool for finding nonlinear decision boundaries of classes are so called artificial neural networks, ANN, and essentially mimicking the human brain structure of interconnected neural nets  ... 
doi:10.5281/zenodo.6472648 fatcat:dmya6w645feg7oe54l5swdveuy
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