Prediction Error Negativity in Physical Human-Robot Collaboration

被引：4

作者：

Singh, Avinash Kumar ^{[1
]}

Aldini, Stefano ^{[2
]}

Leong, Daniel ^{[1
]}

Wang, Yu-Kai ^{[1
]}

Carmichael, Marc G. ^{[2
]}

Liu, Dikai ^{[2
]}

Lin, Chin-Teng ^{[2
]}

机构：

[1] Univ Technol Sydney, Fac Engn & Informat Technol, Ctr Artificial Intelligence, Sydney, NSW, Australia

[2] Univ Technol Sydney, Fac Engn & Informat Technol, Ctr Autonomous Syst, Sydney, NSW, Australia

来源：

2020 8TH INTERNATIONAL WINTER CONFERENCE ON BRAIN-COMPUTER INTERFACE (BCI) | 2020年

基金：

澳大利亚研究理事会;

关键词：

EEG; pHRC; Cognitive Conflict; PEN; ATTENTION; EEG;

D O I：

10.1109/bci48061.2020.9061616

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Cognitive conflict is a fundamental phenomenon of human cognition, particularly during interaction with the real world. Understanding and detecting cognitive conflict can help to improve interactions in a variety of applications, such as in human-robot collaboration (HRC), which involves continuously guiding the semi-autonomous robot to perform a task in given settings. There have been several works to detect cognitive conflict in HRC but without physical control settings. In this work, we have conducted the first study to explore cognitive conflict using prediction error negativity (PEN) in physical human-robot collaboration (pHRC). Our results show that there was a statistically significant (p = .047) higher PEN for conflict condition compared to normal conditions, as well as a statistically significant difference between different levels of PEN (p = .020). These results indicate that cognitive conflict can be detected in pHRC settings and, consequently, provide a window of opportunities to improve the interaction in pHRC.

引用

页码：58 / 63

页数：6

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