{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,26]],"date-time":"2026-04-26T13:48:25Z","timestamp":1777211305941,"version":"3.51.4"},"reference-count":43,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurorobot."],"abstract":"<jats:p>In human-robot collaboration scenarios with shared workspaces, a highly desired performance boost is offset by high requirements for human safety, limiting speed and torque of the robot drives to levels which cannot harm the human body. Especially for complex tasks with flexible human behavior, it becomes vital to maintain safe working distances and coordinate tasks efficiently. An established approach in this regard is reactive servo in response to the current human pose. However, such an approach does not exploit expectations of the human's behavior and can therefore fail to react to fast human motions in time. To adapt the robot's behavior as soon as possible, predicting human intention early becomes a factor which is vital but hard to achieve. Here, we employ a recently developed type of brain-computer interface (BCI) which can detect the focus of the human's overt attention as a predictor for impending action. In contrast to other types of BCI, direct projection of stimuli onto the workspace facilitates a seamless integration in workflows. Moreover, we demonstrate how the signal-to-noise ratio of the brain response can be used to adjust the velocity of the robot movements to the vigilance or alertness level of the human. Analyzing this adaptive system with respect to performance and safety margins in a physical robot experiment, we found the proposed method could improve both collaboration efficiency and safety distance.<\/jats:p>","DOI":"10.3389\/fnbot.2022.1068274","type":"journal-article","created":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T12:27:12Z","timestamp":1669897632000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Coordinating human-robot collaboration by EEG-based human intention prediction and vigilance control"],"prefix":"10.3389","volume":"16","author":[{"given":"Jianzhi","family":"Lyu","sequence":"first","affiliation":[]},{"given":"Alexander","family":"Ma\u00fde","sequence":"additional","affiliation":[]},{"given":"Michael","family":"G\u00f6rner","sequence":"additional","affiliation":[]},{"given":"Philipp","family":"Ruppel","sequence":"additional","affiliation":[]},{"given":"Andreas K.","family":"Engel","sequence":"additional","affiliation":[]},{"given":"Jianwei","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"1965","published-online":{"date-parts":[[2022,12,1]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1109\/TRO.2019.2914350","article-title":"Human-humanoid collaborative carrying","volume":"35","author":"Agravante","year":"2019","journal-title":"IEEE Trans. Robot"},{"key":"B2","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1109\/TNSRE.2009.2039495","article-title":"BCI demographics: how many (and what kinds of) people can use an SSVEP BCI?","volume":"18","author":"Allison","year":"2010","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng"},{"key":"B3","doi-asserted-by":"publisher","first-page":"102137","DOI":"10.1016\/j.rcim.2021.102137","article-title":"EEG based arm movement intention recognition towards enhanced safety in symbiotic human-robot collaboration","volume":"70","author":"Buerkle","year":"2021","journal-title":"Robot. Comput. Integr. Manufact"},{"key":"B4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1475-925X-13-28","article-title":"Objective evaluation of fatigue by EEG spectral analysis in steady-state visual evoked potential-based brain-computer interfaces","volume":"13","author":"Cao","year":"2014","journal-title":"Biomed. Eng. Online"},{"key":"B5","doi-asserted-by":"publisher","first-page":"4113","DOI":"10.3390\/s21124113","article-title":"Trends of human-robot collaboration in industry contexts: handover, learning, and metrics","volume":"21","author":"Castro","year":"2021","journal-title":"Sensors"},{"key":"B6","doi-asserted-by":"publisher","first-page":"026012","DOI":"10.1088\/1741-2552\/aaf594","article-title":"Combination of high-frequency SSVEP-based BCI and computer vision for controlling a robotic arm","volume":"16","author":"Chen","year":"2019","journal-title":"J. Neural Eng"},{"key":"B7","doi-asserted-by":"publisher","first-page":"1850018","DOI":"10.1142\/S0129065718500181","article-title":"Control of a 7-DOF robotic arm system with an SSVEP-based BCI","volume":"28","author":"Chen","year":"2018","journal-title":"Int. J. Neural Syst"},{"key":"B8","doi-asserted-by":"publisher","first-page":"2602","DOI":"10.1109\/LRA.2020.2972874","article-title":"Towards efficient human-robot collaboration with robust plan recognition and trajectory prediction","volume":"5","author":"Cheng","year":"2020","journal-title":"IEEE Robot. Autom. Lett"},{"key":"B9","doi-asserted-by":"publisher","first-page":"eabg1308","DOI":"10.1126\/scirobotics.abg1308","article-title":"The relevance of signal timing in human-robot collaborative manipulation","volume":"6","author":"Cini","year":"2021","journal-title":"Sci. Robot"},{"key":"B10","volume-title":"Practical Nonparametric Statistics","author":"Conover","year":"1999"},{"key":"B11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/ICHMS49158.2020.9209543","article-title":"An EEG investigation on planning human-robot handover tasks","volume-title":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","author":"Cooper","year":"2020"},{"key":"B12","doi-asserted-by":"publisher","first-page":"1016","DOI":"10.1093\/cercor\/bhj044","article-title":"Attentional modulation of SSVEP power depends on the network tagged by the flicker frequency","volume":"16","author":"Ding","year":"2005","journal-title":"Cereb. Cortex"},{"key":"B13","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1109\/TRO.2015.2430053","article-title":"Variable impedance control of redundant manipulators for intuitive human-robot physical interaction","volume":"31","author":"Ficuciello","year":"2015","journal-title":"IEEE Trans. Robot"},{"key":"B14","doi-asserted-by":"publisher","first-page":"116146","DOI":"10.1016\/j.neuroimage.2019.116146","article-title":"Attention differentially modulates the amplitude of resonance frequencies in the visual cortex","volume":"203","author":"Gulbinaite","year":"2019","journal-title":"NeuroImage"},{"key":"B15","doi-asserted-by":"publisher","first-page":"1722","DOI":"10.1109\/TCBB.2020.3039834","article-title":"Predicting human intention-behavior through EEG signal analysis using multi-scale CNN","volume":"18","author":"Huang","year":"2020","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform"},{"key":"B16","doi-asserted-by":"publisher","first-page":"6917","DOI":"10.1523\/JNEUROSCI.21-17-06917.2001","article-title":"Eye-hand coordination in object manipulation","volume":"21","author":"Johansson","year":"2001","journal-title":"J. Neurosci"},{"key":"B17","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/10.553713","article-title":"Estimating alertness from the EEG power spectrum","volume":"44","author":"Jung","year":"1997","journal-title":"IEEE Trans. Biomed. Eng"},{"key":"B18","doi-asserted-by":"publisher","first-page":"016066","DOI":"10.1088\/1741-2552\/ab4dc6","article-title":"An online SSVEP-BCI system in an optical see-through augmented reality environment","volume":"17","author":"Ke","year":"2020","journal-title":"J. Neural Eng"},{"key":"B19","doi-asserted-by":"publisher","first-page":"eabl7022","DOI":"10.1126\/scirobotics.abl7022","article-title":"Effective and natural human-robot interaction requires multidisciplinary research","volume":"6","author":"Kragic","year":"2021","journal-title":"Sci. Robot"},{"key":"B20","doi-asserted-by":"publisher","first-page":"1311","DOI":"10.1068\/p2935","article-title":"The roles of vision and eye movements in the control of activities of daily living","volume":"28","author":"Land","year":"1999","journal-title":"Perception"},{"key":"B21","doi-asserted-by":"crossref","first-page":"5012","DOI":"10.1109\/ICRA.2019.8793580","article-title":"Safe and efficient high dimensional motion planning in space-time with time parameterized prediction","volume-title":"2019 International Conference on Robotics and Automation (ICRA)","author":"Li","year":"2019"},{"key":"B22","doi-asserted-by":"crossref","first-page":"5548","DOI":"10.1109\/EMBC.2019.8857859","article-title":"An SSVEP-BCI in augmented reality","volume-title":"2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","author":"Liu","year":"2019"},{"key":"B23","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1007\/s10514-017-9655-8","article-title":"Unsupervised early prediction of human reaching for human-robot collaboration in shared workspaces","volume":"42","author":"Luo","year":"2018","journal-title":"Auton. Robots"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1109\/TCDS.2022.3215093","article-title":"Efficient and collision-free human-robot collaboration based on intention and trajectory prediction","author":"Lyu","year":"2022","journal-title":"IEEE Trans. Cogn. Dev. Syst"},{"key":"B25","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1016\/0013-4694(88)90019-3","article-title":"Spatial gradients of visual attention: behavioral and electrophysiological evidence","volume":"70","author":"Mangun","year":"1988","journal-title":"Electroencephalogr. Clin. Neurophysiol"},{"key":"B26","doi-asserted-by":"publisher","first-page":"1026","DOI":"10.1109\/TNSRE.2017.2666479","article-title":"Utilizing retinotopic mapping for a multi-target SSVEP BCI with a single flicker frequency","volume":"25","author":"Maye","year":"2017","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng"},{"key":"B27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/B978-0-08-035735-5.50006-1","article-title":"Model predictive control: theory and practice","volume":"21","author":"Morari","year":"1988","journal-title":"IFAC Proc"},{"key":"B28","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1177\/0278364918812981","article-title":"I-planner: Intention-aware motion planning using learning-based human motion prediction","volume":"38","author":"Park","year":"2019","journal-title":"Int. J. Robot. Res"},{"key":"B29","doi-asserted-by":"crossref","first-page":"6175","DOI":"10.1109\/ICRA.2015.7140066","article-title":"Fast target prediction of human reaching motion for cooperative human-robot manipulation tasks using time series classification","volume-title":"2015 IEEE International Conference on Robotics and Automation (ICRA)","author":"P\u00e9rez-D'Arpino","year":"2015"},{"key":"B30","doi-asserted-by":"publisher","first-page":"6663","DOI":"10.1109\/TII.2022.3159583","article-title":"A cybertwin based multimodal network for ECG patterns monitoring using deep learning","volume":"18","author":"Qi","year":"2022","journal-title":"IEEE Trans. Indus. Informatics"},{"key":"B31","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1007\/s41315-018-0051-0","article-title":"Gaze and motion information fusion for human intention inference","volume":"2","author":"Ravichandar","year":"2018","journal-title":"Int. J. Intell. Robot. Appl"},{"key":"B32","doi-asserted-by":"crossref","first-page":"5417","DOI":"10.1109\/IROS45743.2020.9340966","article-title":"Learning object manipulation with dexterous hand-arm systems from human demonstration","volume-title":"2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","author":"Ruppel","year":"2020"},{"key":"B33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12984-020-00675-5","article-title":"Prediction of gait intention from pre-movement EEG signals: a feasibility study","volume":"17","author":"Shafiul Hasan","year":"2020","journal-title":"J. NeuroEng. Rehabil"},{"key":"B34","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1007\/BF01135443","article-title":"Steady-state visually evoked potential topography associated with a visual vigilance task","volume":"3","author":"Silberstein","year":"1990","journal-title":"Brain Topogr"},{"key":"B35","doi-asserted-by":"publisher","first-page":"32","DOI":"10.3389\/fnbot.2020.00032","article-title":"A practical EEG-based human-machine interface to online control an upper-limb assist robot","volume":"14","author":"Song","year":"2020","journal-title":"Front. Neurorobot"},{"key":"B36","doi-asserted-by":"publisher","first-page":"3786","DOI":"10.3390\/s21113786","article-title":"A review of EEG signal features and their application in Driver drowsiness detection systems","volume":"21","author":"Stancin","year":"2021","journal-title":"Sensors"},{"key":"B37","doi-asserted-by":"publisher","first-page":"1452","DOI":"10.1109\/TRO.2020.2992987","article-title":"Online hybrid motion planning for dyadic collaborative manipulation via bilevel optimization","volume":"36","author":"Stouraitis","year":"2020","journal-title":"IEEE Trans. Robot"},{"key":"B38","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1016\/j.neunet.2020.07.033","article-title":"Improved recurrent neural network-based manipulator control with remote center of motion constraints: experimental results","volume":"131","author":"Su","year":"2020","journal-title":"Neural Netw"},{"key":"B39","doi-asserted-by":"crossref","first-page":"7009","DOI":"10.1109\/IROS40897.2019.8968171","article-title":"Multimodal uncertainty reduction for intention recognition in human-robot interaction","volume-title":"2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","author":"Trick","year":"2019"},{"key":"B40","first-page":"329","article-title":"Decision-making for bidirectional communication in sequential human-robot collaborative tasks","volume-title":"2020 15th ACM\/IEEE International Conference on Human-Robot Interaction (HRI)","author":"Unhelkar","year":"2020"},{"key":"B41","doi-asserted-by":"publisher","first-page":"1206","DOI":"10.3389\/fnins.2021.684547","article-title":"Decoding different reach-and-grasp movements using noninvasive electroencephalogram","volume":"15","author":"Xu","year":"2021","journal-title":"Front. Neurosci"},{"key":"B42","doi-asserted-by":"publisher","first-page":"3033","DOI":"10.1109\/TCYB.2019.2905157","article-title":"Making sense of spatio-temporal preserving representations for EEG-based human intention recognition","volume":"50","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Cybern"},{"key":"B43","doi-asserted-by":"crossref","first-page":"4349","DOI":"10.23919\/ACC45564.2020.9147277","article-title":"Experimental evaluation of human motion prediction toward safe and efficient human robot collaboration","volume-title":"2020 American Control Conference (ACC)","author":"Zhao","year":"2020"}],"container-title":["Frontiers in Neurorobotics"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnbot.2022.1068274\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T12:27:18Z","timestamp":1669897638000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnbot.2022.1068274\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,1]]},"references-count":43,"alternative-id":["10.3389\/fnbot.2022.1068274"],"URL":"https:\/\/doi.org\/10.3389\/fnbot.2022.1068274","relation":{},"ISSN":["1662-5218"],"issn-type":[{"value":"1662-5218","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,1]]},"article-number":"1068274"}}