Inspiring Real-Time Evaluation and Optimization of Human–Robot Interaction with Psychological Findings from Human–Human Interaction

Round 1

Reviewer 1 Report

The authors address a really interesting topic: how to connect the ERP and BCI research. This is a clear gap in the field and a quite new idea. However, authors present a narrative review that aims to justify the plausibility of linking ERP and BCI in specific contexts more than suggest ways to integrate ERP analyses with BCI technology. First, a systematic review would be more informative for the audience that could be considering applying this idea. Besides, although authors review some relevant literature on ERPs related to how social interaction impacts people's performance and brain processing during performance, authors did not explore literature regarding the technical challenges that integrating ERPs and BCI may entail. I suggest authors to expand the review into this topic as well. A figure illustrating how to combine ERP analyses with BCI in practice would also help the reader to have a better idea on how this could be implemented. Finally, conclusions seems to be underdeveloped and I suggest authors to not only summarize the general idea but to comment on implications and future directions. 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Please, correct line 96. Delete ‘space’ after references [25-27] before ‘Interestingly’.

Author Response

The redundant ‘space’ in line 96 has been deleted.

Reviewer 3 Report

The paper is a rather comprehensive review of research on HRI based on psychological human-human interaction (HHI).

My general concern is that the paper addresses only the psychological/social science view of HRI. In the field of robotics, this view is important for any researcher working on collaborative robots, service robots, or other robots interacting with humans, so the topic is relevant. But the second part of the article, correlation of HHI parameters with EEG, seems rather weak (short, not very detailed, only a few references, which should not happen in a review article). If some more substantial and experiment-based results were presented, the paper would be a valuable reference for the Applied Sciences readers.

Author Response

To enrich the content of the second part, Section 5 has been further divided into 3 subsections, with Section 5.1 on “EEG signatures of the three psychological effects in HRI”, Section 5.2 on “Developing BCI systems for HRI evaluation and optimization” and Section 5.3 on “Application of BCI in different fields of HRI”. More findings on the EEG correlates of the psychological effects in HRI has been added with more references, such as the EEG findings related to the arousal element in social facilitation. The readers are referred to existing reviews for a comprehensive understanding of classical neural results such as mu rhythm. It should also be noted that the exploration of the neural substrates of these effects is still ongoing, resulting in limited number of established neuroscience findings and theories. The main purpose of summarizing the EEG correlates of these effects in existing studies is to provide the researchers with preliminary clues when they search for potential neural signatures to utilize in BCI application. However, as we point out in Section 5.2, the validity of these neural signatures in specific HRI tasks need further examination.

Round 2

Reviewer 1 Report

The manuscript have been improved following reviewers' suggestions and it seems to be ready for publication in its current version. I thank authors for considerring my comments.