{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T13:44:21Z","timestamp":1762868661948,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,30]],"date-time":"2021-10-30T00:00:00Z","timestamp":1635552000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004239","name":"Pozna\u0144 University of Technology","doi-asserted-by":"publisher","award":["0614\/SBAD\/1547"],"award-info":[{"award-number":["0614\/SBAD\/1547"]}],"id":[{"id":"10.13039\/501100004239","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Research focused on signals derived from the human organism is becoming increasingly popular. In this field, a special role is played by brain-computer interfaces based on brainwaves. They are becoming increasingly popular due to the downsizing of EEG signal recording devices and ever-lower set prices. Unfortunately, such systems are substantially limited in terms of the number of generated commands. This especially applies to sets that are not medical devices. This article proposes a hybrid brain-computer system based on the Steady-State Visual Evoked Potential (SSVEP), EOG, eye tracking, and force feedback system. Such an expanded system eliminates many of the particular system shortcomings and provides much better results. The first part of the paper presents information on the methods applied in the hybrid brain-computer system. The presented system was tested in terms of the ability of the operator to place the robot\u2019s tip to a designated position. A virtual model of an industrial robot was proposed, which was used in the testing. The tests were repeated on a real-life industrial robot. Positioning accuracy of system was verified with the feedback system both enabled and disabled. The results of tests conducted both on the model and on the real object clearly demonstrate that force feedback improves the positioning accuracy of the robot\u2019s tip when controlled by the operator. In addition, the results for the model and the real-life industrial model are very similar. In the next stage, research was carried out on the possibility of sorting items using the BCI system. The research was carried out on a model and a real robot. The results show that it is possible to sort using bio signals from the human body.<\/jats:p>","DOI":"10.3390\/s21217244","type":"journal-article","created":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T22:24:22Z","timestamp":1635805462000},"page":"7244","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Use of Force Feedback Device in a Hybrid Brain-Computer Interface Based on SSVEP, EOG and Eye Tracking for Sorting Items"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6353-5801","authenticated-orcid":false,"given":"Arkadiusz","family":"Kubacki","sequence":"first","affiliation":[{"name":"Institute of Mechanical Technology, Poznan University of Technology, ul. Piotrowo 3, 60-965 Pozna\u0144, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,30]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Rezeika, A., Benda, M., Stawicki, P., Gembler, F., Saboor, A., and Volosyak, I. (2018). Brain\u2014Computer Interface Spellers: A Review. Brain Sci., 8.","key":"ref_1","DOI":"10.3390\/brainsci8040057"},{"doi-asserted-by":"crossref","unstructured":"Mezzina, G., and Venuto, D.D. (2020, January 9\u201313). Semi-Autonomous Personal Care Robots Interface driven by EEG Signals Digitization. Proceedings of the 2020 Design, Automation Test in Europe Conference Exhibition, Grenoble, France.","key":"ref_2","DOI":"10.23919\/DATE48585.2020.9116499"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"031012","DOI":"10.1115\/1.4002138","article-title":"Wireless Point-of-Care Diagnosis for Sleep Disorder With Dry Nanowire Electrodes","volume":"1","author":"Varadan","year":"2010","journal-title":"J. Nanotechnol. Eng. Med."},{"doi-asserted-by":"crossref","unstructured":"Choi, J., Kim, K.T., Jeong, J.H., Kim, L., Lee, S.J., and Kim, H. (2020). Developing a Motor Imagery-Based Real-Time Asynchronous Hybrid BCI Controller for a Lower-Limb Exoskeleton. Sensors, 20.","key":"ref_4","DOI":"10.3390\/s20247309"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"101687","DOI":"10.1016\/j.bspc.2019.101687","article-title":"A hybrid BCI-controlled smart home system combining SSVEP and EMG for individuals with paralysis","volume":"56","author":"Chai","year":"2020","journal-title":"Biomed. Signal. Proces."},{"doi-asserted-by":"crossref","unstructured":"Chai, X., Zhang, Z., Lu, Y., Liu, G., Zhang, T., and Niu, H. (2018, January 3\u20138). A Hybrid BCI-Based Environmental Control System Using SSVEP and EMG Signals. Proceedings of the Congress on Medical Physics and Biomedical Engineering, Prague, Czech Republic.","key":"ref_6","DOI":"10.1007\/978-981-10-9023-3_11"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jneumeth.2018.11.010","article-title":"An EEG-EMG correlation-based brain-computer interface for hand orthosis supported neuro-rehabilitation","volume":"312","author":"Chowdhury","year":"2019","journal-title":"J. Neurosci. Meth."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"012033","DOI":"10.1088\/1742-6596\/1528\/1\/012033","article-title":"EEG-EMG based bio-robotics elbow orthotics control","volume":"1528","author":"Ferdiansyah","year":"2020","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3081","DOI":"10.1007\/s11277-020-07518-5","article-title":"A Hybrid Approach for Extracting EMG signals by Filtering EEG Data for IoT Applications for Immobile Persons","volume":"114","author":"Kurapa","year":"2020","journal-title":"Wireless Pers. Commun."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"105326","DOI":"10.1016\/j.cmpb.2020.105326","article-title":"A novel hybrid BCI speller based on RSVP and SSVEP paradigm","volume":"187","author":"Jalilpour","year":"2020","journal-title":"Comput. Meth. Prog. Bio."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.cogsys.2019.09.014","article-title":"An optimized facial stimuli paradigm for hybrid SSVEP+P300 brain computer interface","volume":"59","author":"Kapgate","year":"2020","journal-title":"Cogn. Syst. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"101884","DOI":"10.1016\/j.bspc.2020.101884","article-title":"A novel hybrid paradigm based on steady state visually evoked potential & P300 to enhance information transfer rate","volume":"59","author":"Katyal","year":"2020","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2050003","DOI":"10.4015\/S1016237220500039","article-title":"SSVEP-P300 hybrid paradigm optimization for enhanced information transfer rate","volume":"32","author":"Katyal","year":"2020","journal-title":"Biomed. Eng. Appl. Basis Commun."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1840005","DOI":"10.1142\/S2424922X18400053","article-title":"Nonfatigating Brain\u2013Computer Interface Based on SSVEP and ERD to Command an Autonomous Car","volume":"10","author":"Bastos","year":"2018","journal-title":"Adv. Data Sci. Adapt. Data Anal."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"100994","DOI":"10.1016\/j.aei.2019.100994","article-title":"A high performance hybrid SSVEP based BCI speller system","volume":"42","author":"Saravanakumar","year":"2019","journal-title":"Adv. Eng. Info."},{"doi-asserted-by":"crossref","unstructured":"Saravanakumar, D., and Reddy, M.R. (2018, January 3\u20135). A Novel Visual Keyboard System for Disabled People\/Individuals Using Hybrid SSVEP Based Brain Computer Interface. Proceedings of the 2018 International Conference on Cyberworlds (CW), Singapore.","key":"ref_16","DOI":"10.1109\/CW.2018.00054"},{"doi-asserted-by":"crossref","unstructured":"Kubacki, A. (2018, January 20\u201324). Hybrid Brain-Computer Interface (BCI) Based on Electrooculography (EOG) and Center Eye Tracking. Proceedings of the Conference on Automation 2018, Munich, Germany.","key":"ref_17","DOI":"10.1007\/978-3-319-77179-3_27"},{"doi-asserted-by":"crossref","unstructured":"Antoniou, E., Bozios, P., Christou, V., Tzimourta, K.D., Kalafatakis, K., Tsipouras, M.G., Giannakeas, N., and Tzallas, A.T. (2021). EEG-Based Eye Movement Recognition Using Brain\u2013Computer Interface and Random Forests. Sensors, 21.","key":"ref_18","DOI":"10.3390\/s21072339"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1109\/THMS.2020.3047597","article-title":"A Self-Paced BCI With a Collaborative Controller for Highly Reliable Wheelchair Driving: Experimental Tests With Physically Disabled Individuals","volume":"51","author":"Cruz","year":"2021","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"unstructured":"Sun, X., Wang, J., and Bertino, E. (2020, January 17\u201320). A Simulation Platform for the Brain-Computer Interface (BCI) Based Smart Wheelchair. Proceedings of the Artificial Intelligence and Security, Hohhot, China.","key":"ref_20"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"761","DOI":"10.20965\/jrm.2020.p0761","article-title":"Indirect Control of an Autonomous Wheelchair Using SSVEP BCI","volume":"32","author":"Ng","year":"2020","journal-title":"J. Robot. Mechatron."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"265","DOI":"10.3389\/fnhum.2020.00265","article-title":"Wheelchair Control in a Virtual Environment by Healthy Participants Using a P300-BCI Based on Tactile Stimulation: Training Effects and Usability","volume":"14","author":"Eidel","year":"2020","journal-title":"Front. Hum. Neurosci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"e4909685","DOI":"10.1155\/2016\/4909685","article-title":"Driving a Semiautonomous Mobile Robotic Car Controlled by an SSVEP-Based BCI","volume":"2016","author":"Stawicki","year":"2016","journal-title":"Comput. Intell. Neurosci."},{"doi-asserted-by":"crossref","unstructured":"Liu, C., Xie, S., Xie, X., Duan, X., Wang, W., and Obermayer, K. (2018, January 15\u201317). Design of a Video Feedback SSVEP-BCI System for Car Control Based on Improved MUSIC Method. Proceedings of the 6th International Conference on Brain-Computer Interface (BCI), Gangwon, Korea.","key":"ref_24","DOI":"10.1109\/IWW-BCI.2018.8311499"},{"key":"ref_25","first-page":"2191","article-title":"Implementation of Brain Controlled Robotic Car to Assist Paralytic and Physically Challenged People by Analyzing EEG Signals","volume":"7","author":"Basha","year":"2020","journal-title":"Eur. J. Mol. Clin. Med."},{"doi-asserted-by":"crossref","unstructured":"Park, J., Park, J., Shin, D., and Choi, Y. (2021). A BCI Based Alerting System for Attention Recovery of UAV Operators. Sensors, 21.","key":"ref_26","DOI":"10.3390\/s21072447"},{"doi-asserted-by":"crossref","unstructured":"Christensen, S.M., Holm, N.S., and Puthusserypady, S. (2019). An Improved Five Class MI Based BCI Scheme for Drone Control Using Filter Bank CSP. Proceedings of the 7th International Winter Conference on Brain-Computer Interface (BCI), High 1 Resort, Korea, 18\u201320 February 2019, Institute of Electrical and Electronics Engineers, Inc.","key":"ref_27","DOI":"10.1109\/IWW-BCI.2019.8737263"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1109\/THMS.2018.2830647","article-title":"A Survey on Unmanned Aerial Vehicle Remote Control Using Brain\u2013Computer Interface","volume":"48","author":"Nourmohammadi","year":"2018","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1661","DOI":"10.1007\/s12555-020-0069-6","article-title":"Positioning of the Robotic Arm Using Different Reinforcement Learning Algorithms","volume":"19","author":"Lindner","year":"2021","journal-title":"Int. J. Control Autom. Syst."},{"doi-asserted-by":"crossref","unstructured":"Achic, F., Montero, J., Penaloza, C., and Cuellar, F. (2016, January 8\u201310). Hybrid BCI System to Operate an Electric Wheelchair and a Robotic Arm for Navigation and Manipulation Tasks. Proceedings of the 2016 IEEE Workshop on Advanced Robotics and Its Social Impacts, Shanghai, China.","key":"ref_30","DOI":"10.1109\/ARSO.2016.7736290"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e8316485","DOI":"10.1155\/2017\/8316485","article-title":"Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System","volume":"2017","author":"Gao","year":"2017","journal-title":"BioMed Res. Int."},{"doi-asserted-by":"crossref","unstructured":"Ha, J., Park, S., Im, C.-H., and Kim, L. (2021). A Hybrid Brain\u2013Computer Interface for Real-Life Meal-Assist Robot Control. Sensors, 21.","key":"ref_32","DOI":"10.3390\/s21134578"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"e5708937","DOI":"10.1155\/2017\/5708937","article-title":"Towards Rehabilitation Robotics: Off-the-Shelf BCI Control of Anthropomorphic Robotic Arms","volume":"2017","author":"Athanasiou","year":"2017","journal-title":"BioMed Res. Int."},{"doi-asserted-by":"crossref","unstructured":"Wang, X., Xiao, Y., Deng, F., Chen, Y., and Zhang, H. (2021). Eye-Movement-Controlled Wheelchair Based on Flexible Hydrogel Biosensor and WT-SVM. Biosensors, 11.","key":"ref_34","DOI":"10.3390\/bios11060198"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1109\/TNSRE.2009.2039594","article-title":"A Self-Paced and Calibration-Less SSVEP-Based Brain\u2013Computer Interface Speller","volume":"18","author":"Cecotti","year":"2010","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"e702357","DOI":"10.1155\/2010\/702357","article-title":"A Survey of Stimulation Methods Used in SSVEP-Based BCIs","volume":"2010","author":"Zhu","year":"2010","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2610","DOI":"10.1109\/TBME.2006.886577","article-title":"Frequency Recognition Based on Canonical Correlation Analysis for SSVEP-Based BCIs","volume":"53","author":"Lin","year":"2006","journal-title":"IEEE Trans. BioMed. Eng."},{"doi-asserted-by":"crossref","unstructured":"Hamrol, A., Ciszak, O., Legutko, S., and Jurczyk, M. (2018, January 11\u201313). Development of Force Feedback Controller For the Loader Crane. Proceedings of the Advances in Manufacturing, Sk\u00f6vde, Sweden.","key":"ref_38","DOI":"10.1007\/978-3-319-68619-6"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"020032","DOI":"10.1063\/1.5066494","article-title":"Controlling the Industrial Robot Model with the Hybrid BCI Based on EOG and Eye Tracking","volume":"2029","author":"Kubacki","year":"2018","journal-title":"AIP Conf. Proc."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/21\/7244\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:23:41Z","timestamp":1760167421000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/21\/7244"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,30]]},"references-count":39,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["s21217244"],"URL":"https:\/\/doi.org\/10.3390\/s21217244","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2021,10,30]]}}}