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SSVEP-P300 HYBRID PARADIGM OPTIMIZATION FOR ENHANCED INFORMATION TRANSFER RATE

脑-机接口 信息传递 计算机科学 接口 脑电图 人工智能 语音识别 人机交互 计算机硬件 神经科学 心理学 电信
作者
Akshay Katyal,Rajesh Singla
出处
期刊:Biomedical Engineering: Applications, Basis and Communications [World Scientific]
卷期号:32 (01): 2050003-2050003 被引量:1
标识
DOI:10.4015/s1016237220500039
摘要

Hybrid brain–computer interfacing (BCI), recently, has been the epicenter of research in the area of rehabilitation engineering. The concept is based on the principle that the paradigm used for the BCI elicits one BCI marker in combination with one or more BCI modalities or other physiological signals. These paradigms elicit human brain response to successfully determine user intentions. Steady-state visually evoked potential (SSVEP) has been the favourite amongst researchers to combine with other BCI modalities such as P300, Motor Imagery (MI), etc. to develop assistive devices (ADs) based on hybrid BCI. This research paper is a record of a comparative study conducted between two hybrid BCI’s, namely hybrid BCI-1, hybrid BCI-2 and traditional SSVEP BCI. Both hybrid paradigms are similar in schematics but differ in the operational protocol. The study aimed to find the optimal protocol which greatly enhances the average information transfer rate (ITR) of a BCI-based AD. Hybrid BCI-1 showed lower classification accuracy (90.36%) and higher false activation rate (FAR) (3.16%) as compared to Hybrid BCI-2 (92.35% and 2.78%, respectively) as well as traditional SSVEP (93.38% and 2.73%, respectively). However, the average ITR of Hybrid BCI-1 (80.76 bits/min) was much higher than that of Hybrid BCI-2 (41.21 bits/min) and traditional SSVEP paradigm (36.34 bits/min). This led to the conclusion, that Hybrid BCI-1 is the most viable option for developing an AD.

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