ترجمه مقاله نقش ضروری ارتباطات 6G با چشم انداز صنعت 4.0
- مبلغ: ۸۶,۰۰۰ تومان
ترجمه مقاله پایداری توسعه شهری، تعدیل ساختار صنعتی و کارایی کاربری زمین
- مبلغ: ۹۱,۰۰۰ تومان
A Brain-Computer Interface (BCI) is a communication system that does not require any peripheral muscular activity [1]. Indeed, BCI systems enable a subject to send commands to an electronic device only by means of brain activity [2]. Such interfaces can be considered as being the only way of communication for people affected by a number of motor disabilities [3]. In order to control a BCI, the user must produce different brain activity patterns that will be identified by the system and translated into commands. In most existing BCI, this identification relies on a classification algorithm [4], i.e., an algorithm that aims at automatically estimating the class of data as represented by a feature vector [5]. Due to the rapidly growing interest for EEG-based BCI, a considerable number of published results is related to the investigation and evaluation of classification algorithms. To date, very interesting reviews of BCI have been published [1] [6] but none has been specifically dedicated to the review of classification algorithms used for BCI, their properties and their evaluation.