Next Article in Journal
Fractional Order KDHD Impedance Control of the Stewart Platform
Next Article in Special Issue
Numerical Shape Planning Algorithm for Hyper-Redundant Robots Based on Discrete Bézier Curve Fitting
Previous Article in Journal
A Novel Ensemble of Arithmetic Optimization Algorithm and Harris Hawks Optimization for Solving Industrial Engineering Optimization Problems
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

EEG-Based Empathic Safe Cobot

by
Alberto Borboni
1,*,
Irraivan Elamvazuthi
2 and
Nicoletta Cusano
1,3
1
Mechanical and Industrial Engineering Department, University of Brescia, Via Branze 38, 25073 Brescia, Italy
2
Department of Electrical and Electronic Engineering, Universiti Teknologi Petronas, Seri Iskandar 32610, Malaysia
3
Faculty of Political Science and Sociopsychological Dynamics, Università degli Studi Internazionali di Roma, Via Cristoforo Colombo 200, 00147 Rome, Italy
*
Author to whom correspondence should be addressed.
Machines 2022, 10(8), 603; https://doi.org/10.3390/machines10080603
Submission received: 10 June 2022 / Revised: 19 July 2022 / Accepted: 21 July 2022 / Published: 24 July 2022

Abstract

An empathic collaborative robot (cobot) was realized through the transmission of fear from a human agent to a robot agent. Such empathy was induced through an electroencephalographic (EEG) sensor worn by the human agent, thus realizing an empathic safe brain-computer interface (BCI). The empathic safe cobot reacts to the fear and in turn transmits it to the human agent, forming a social circle of empathy and safety. A first randomized, controlled experiment involved two groups of 50 healthy subjects (100 total subjects) to measure the EEG signal in the presence or absence of a frightening event. The second randomized, controlled experiment on two groups of 50 different healthy subjects (100 total subjects) exposed the subjects to comfortable and uncomfortable movements of a collaborative robot (cobot) while the subjects’ EEG signal was acquired. The result was that a spike in the subject’s EEG signal was observed in the presence of uncomfortable movement. The questionnaires were distributed to the subjects, and confirmed the results of the EEG signal measurement. In a controlled laboratory setting, all experiments were found to be statistically significant. In the first experiment, the peak EEG signal measured just after the activating event was greater than the resting EEG signal (p < 10−3). In the second experiment, the peak EEG signal measured just after the uncomfortable movement of the cobot was greater than the EEG signal measured under conditions of comfortable movement of the cobot (p < 10−3). In conclusion, within the isolated and constrained experimental environment, the results were satisfactory.
Keywords: empathy; empathic; cobot; robot; EEG; electroencephalographic; BCI; brain-computer interface; safe; safety empathy; empathic; cobot; robot; EEG; electroencephalographic; BCI; brain-computer interface; safe; safety

Share and Cite

MDPI and ACS Style

Borboni, A.; Elamvazuthi, I.; Cusano, N. EEG-Based Empathic Safe Cobot. Machines 2022, 10, 603. https://doi.org/10.3390/machines10080603

AMA Style

Borboni A, Elamvazuthi I, Cusano N. EEG-Based Empathic Safe Cobot. Machines. 2022; 10(8):603. https://doi.org/10.3390/machines10080603

Chicago/Turabian Style

Borboni, Alberto, Irraivan Elamvazuthi, and Nicoletta Cusano. 2022. "EEG-Based Empathic Safe Cobot" Machines 10, no. 8: 603. https://doi.org/10.3390/machines10080603

APA Style

Borboni, A., Elamvazuthi, I., & Cusano, N. (2022). EEG-Based Empathic Safe Cobot. Machines, 10(8), 603. https://doi.org/10.3390/machines10080603

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop