A Comparison of Classification Algorithms for Brain Computer Interface in Drug Craving Treatment
Mirko Mazzoleni,Fabio Previdi +1 more
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TLDR
In this paper, the use of Brain Computer Interfaces is proposed as a means to recover patients from craving diseases, with the aim of a clinical protocol and a classification algorithm based on logistic regression has been developed.About:
This article is published in IFAC-PapersOnLine.The article was published on 2015-01-01 and is currently open access. It has received 5 citations till now. The article focuses on the topics: Statistical classification.read more
Citations
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Book ChapterDOI
Learning from Data
TL;DR: This chapter contains sections titled: Learning Machine Statistical Learning Theory Types of Learning Methods Common Learning Tasks Model Estimation Review Questions and Problems References for further study.
Journal ArticleDOI
Classification algorithms analysis for brain-computer interface in drug craving therapy
TL;DR: A novel therapy to recover patients from drug craving diseases, with the use of brain–computer interfaces (BCIs), and the Naive Bayes method has been chosen as the best classifier between the tested ones, giving a +12.21% performance boost as concerns the F1-score metric.
Brain Computer Interfaces: A New Existential Risk Factor
TL;DR: In this paper , the authors identify a new existential risk factor that has not been recognised in prior literature: Brain-Computer Interfaces (BCIs), and illustrate how BCI technology could significantly raise the existential risk from global totalitarianism in the near future.
Journal ArticleDOI
Non-invasive Control of a Intelligent Room Using EEG Signals
TL;DR: In this paper, a system that integrates people with motor disabilities to an intelligent room prototype is presented, which allows them to perform different applications inside a room through a Brain Computer Interface (BCI) based on biological signals.
References
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Journal ArticleDOI
Pattern Classification and Scene Analysis.
Journal ArticleDOI
The Elements of Statistical Learning
TL;DR: Chapter 11 includes more case studies in other areas, ranging from manufacturing to marketing research, and a detailed comparison with other diagnostic tools, such as logistic regression and tree-based methods.
Journal ArticleDOI
Evoked-Potential Correlates of Stimulus Uncertainty
TL;DR: The average evoked-potential waveforms to sound and light stimuli recorded from scalp in awake human subjects show differences as a function of the subject's degree of uncertainty with respect to the sensory modality of the stimulus to be presented.
Journal ArticleDOI
A spelling device for the paralysed
Niels Birbaumer,N. Ghanayim,Thilo Hinterberger,Iver H. Iversen,Boris Kotchoubey,Andrea Kübler,J. Perelmouter,Edward Taub,Herta Flor +8 more
TL;DR: A new means of communication for the completely paralysed that uses slow cortical potentials of the electro-encephalogram to drive an electronic spelling device is developed.
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