EEG-Based Empathic Safe Cobot

被引:6
|
作者
Borboni, Alberto [1 ]
Elamvazuthi, Irraivan [2 ]
Cusano, Nicoletta [1 ,3 ]
机构
[1] Univ Brescia, Mech & Ind Engn Dept, Via Branze 38, I-25073 Brescia, Italy
[2] Univ Teknol Petronas, Dept Elect & Elect Engn, Seri Iskandar 32610, Perak, Malaysia
[3] Univ Int Roma, Fac Polit Sci & Sociopsychol Dynam, Via Cristoforo Colombo 200, I-00147 Rome, Italy
关键词
empathy; empathic; cobot; robot; EEG; electroencephalographic; BCI; brain-computer interface; safe; safety; EMOTION RECOGNITION; FACE; SYSTEMS; ASYMMETRY; TRACKING; GESTURE; MODELS;
D O I
10.3390/machines10080603
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页数:34
相关论文
共 50 条
  • [1] Enabling Safe ITS: EEG-Based Microsleep Detection in VANETs
    Chougule, Amit
    Shah, Jash
    Chamola, Vinay
    Kanhere, Salil
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (12) : 15773 - 15783
  • [2] Advances in EEG-Based Biometry
    Ferreira, Antonio
    Almeida, Carlos
    Georgieva, Petia
    Tome, Ana
    Silva, Filipe
    IMAGE ANALYSIS AND RECOGNITION, 2010, PT II, PROCEEDINGS, 2010, 6112 : 287 - 295
  • [3] EEG-based seizure detection
    Baumgartner, C.
    EUROPEAN JOURNAL OF NEUROLOGY, 2017, 24 : 748 - 748
  • [4] PNN for EEG-based Emotion Recognition
    Zhang, Jianhai
    Chen, Ming
    Hu, Sanqing
    Cao, Yu
    2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2016, : 2319 - 2323
  • [5] EEG-based functional networks in schizophrenia
    Jalili, Mahdi
    Knyazeva, Maria G.
    COMPUTERS IN BIOLOGY AND MEDICINE, 2011, 41 (12) : 1178 - 1186
  • [6] EEG-based Speech Activity Detection
    Kocturova, Marianna
    Juhar, Jozef
    ACTA POLYTECHNICA HUNGARICA, 2021, 18 (01) : 65 - 77
  • [7] Multitask Learning for EEG-Based Biometrics
    Sun, Shiliang
    19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6, 2008, : 2743 - 2746
  • [8] EEG-based Emotion Word Recognition
    Dong, Weiwei
    Wang, Panpan
    Zhang, Yazhou
    Wang, Tianshu
    Niu, Jiabin
    Zhang, Shengnan
    PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON ADVANCED CONTROL, AUTOMATION AND ARTIFICIAL INTELLIGENCE (ACAAI 2018), 2018, 155 : 121 - 124
  • [9] EEG-based model and antidepressant response
    Nilsonne, Gustav
    Harrell, Frank E., Jr.
    NATURE BIOTECHNOLOGY, 2021, 39 (01) : 27 - 27
  • [10] EEG-based model and antidepressant response
    Gustav Nilsonne
    Frank E. Harrell
    Nature Biotechnology, 2021, 39 : 27 - 27