Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation

Ju Chi Liu, Hung Chyun Chou, Chien Hsiu Chen, Yi Tseng Lin, Chung Hsien Kuo

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

A high efficient time-shift correlation algorithm was proposed to deal with the peak time uncertainty of P300 evoked potential for a P300-based brain-computer interface (BCI). The time-shift correlation series data were collected as the input nodes of an artificial neural network (ANN), and the classification of four LED visual stimuli was selected as the output node. Two operating modes, including fast-recognition mode (FM) and accuracy-recognition mode (AM), were realized. The proposed BCI system was implemented on an embedded system for commanding an adult-size humanoid robot to evaluate the performance from investigating the ground truth trajectories of the humanoid robot. When the humanoid robot walked in a spacious area, the FM was used to control the robot with a higher information transfer rate (ITR). When the robot walked in a crowded area, the AM was used for high accuracy of recognition to reduce the risk of collision. The experimental results showed that, in 100 trials, the accuracy rate of FM was 87.8% and the average ITR was 52.73 bits/min. In addition, the accuracy rate was improved to 92% for the AM, and the average ITR decreased to 31.27 bits/min. due to strict recognition constraints.

Original languageEnglish
Article number3039454
JournalComputational Intelligence and Neuroscience
Volume2016
DOIs
Publication statusPublished - 2016

Fingerprint

Event-related Potentials
P300 Event-Related Potentials
Brain-Computer Interfaces
Brain computer interface
Humanoid Robot
Information Transfer
Robots
Computer Systems
Evoked Potentials
Robot
Uncertainty
Bioelectric potentials
Vertex of a graph
Embedded systems
Embedded Systems
Light emitting diodes
Artificial Neural Network
High Accuracy
Collision
Trajectories

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)
  • Neuroscience(all)

Cite this

Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation. / Liu, Ju Chi; Chou, Hung Chyun; Chen, Chien Hsiu; Lin, Yi Tseng; Kuo, Chung Hsien.

In: Computational Intelligence and Neuroscience, Vol. 2016, 3039454, 2016.

Research output: Contribution to journalArticle

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