{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T07:28:52Z","timestamp":1783582132145,"version":"3.55.0"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T00:00:00Z","timestamp":1733184000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T00:00:00Z","timestamp":1733184000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1652454"],"award-info":[{"award-number":["1652454"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2114464"],"award-info":[{"award-number":["2114464"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Robot Syst"],"DOI":"10.1007\/s10846-024-02185-1","type":"journal-article","created":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T09:16:43Z","timestamp":1733390203000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Intent-based Task-Oriented Shared Control for Intuitive Telemanipulation"],"prefix":"10.1007","volume":"110","author":[{"given":"Michael","family":"Bowman","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiucai","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2949-4644","authenticated-orcid":false,"given":"Xiaoli","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,3]]},"reference":[{"key":"2185_CR1","doi-asserted-by":"crossref","unstructured":"Losey, D.P., McDonald, C.G., Battaglia, E., O\u2019Malley, M.K.: A review of intent detection, arbitration, and communication aspects of shared control for physical human\u2013robot interaction. Appl. Mech. Rev. 70(1) (2018)","DOI":"10.1115\/1.4039145"},{"key":"2185_CR2","doi-asserted-by":"publisher","first-page":"1030","DOI":"10.1080\/01691864.2017.1365011","volume":"31","author":"R Ozawa","year":"2017","unstructured":"Ozawa, R., Tahara, K.: Grasp and dexterous manipulation of multi-fingered robotic hands: a review from a control view point. Adv. Robot. 31, 1030\u20131050 (2017)","journal-title":"Adv. Robot."},{"key":"2185_CR3","doi-asserted-by":"crossref","unstructured":"Rybarczyk, Y., Colle, E., Hoppenot, P.: Contribution of neuro-science to the teleoperation of rehabilitation robot. In: IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 6\u20134 (2002). IEEE","DOI":"10.1109\/ICSMC.2002.1173273"},{"issue":"2","key":"2185_CR4","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1162\/pres.17.2.199","volume":"17","author":"AN Healey","year":"2008","unstructured":"Healey, A.N.: Speculation on the neuropsychology of teleoperation: implications for presence research and minimally invasive surgery. Presence. 17(2), 199\u2013211 (2008)","journal-title":"Presence."},{"key":"2185_CR5","doi-asserted-by":"crossref","unstructured":"Lin, T.C., Krishnan, A.U., Li, Z.: Shared autonomous interface for reducing physical effort in robot teleoperation via human motion mapping. In: in 2020 IEEE International Conference on Robotics and Automation (ICRA), pp. 9157\u20139163 (2020). IEEE","DOI":"10.1109\/ICRA40945.2020.9197220"},{"key":"2185_CR6","doi-asserted-by":"crossref","unstructured":"Salvietti, G.: Replicating human hand synergies onto robotic hands: a review on software and hardware strategies. Front. Neurorobot. 12(JUN), 1\u20136 (2018)","DOI":"10.3389\/fnbot.2018.00027"},{"key":"2185_CR7","doi-asserted-by":"crossref","unstructured":"Bowman, M., Li, S., Zhang, X.: Intent-uncertainty-aware grasp planning for robust robotic assistance in telemanipulation. In: International Conference on Robotics and Automation(ICRA), pp. 409\u2013415. IEEE, Montreal,Canada (2019)","DOI":"10.1109\/ICRA.2019.8793819"},{"key":"2185_CR8","doi-asserted-by":"crossref","unstructured":"Dragan, A.D., Srinivasa, S.S.: A policy-blending formalism for shared control. Int. J. Robot. Res. (2013)","DOI":"10.1177\/0278364913490324"},{"key":"2185_CR9","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.robot.2017.04.013","volume":"94","author":"A Erdogan","year":"2017","unstructured":"Erdogan, A., Argall, B.D.: The effect of robotic wheelchair control paradigm and interface on user performance, effort and preference: an experimental assessment. Robot. Auton. Syst. 94, 282\u2013297 (2017). https:\/\/doi.org\/10.1016\/j.robot.2017.04.013","journal-title":"Robot. Auton. Syst."},{"key":"2185_CR10","doi-asserted-by":"crossref","unstructured":"Santello, M., Bianchi, M., Gabiccini, M., Ricciardi, E., Salvietti, G., Prattichizzo, D., Ernst, M., Moscatelli, A., Jorntell, H., Kappers, A.M., Kyriakopoulos, K., Albu-Schaffer, A., Castellini, C., A., B.: Hand synergies: integration of robotics and neuroscience for under-standing the control of biological and artificial hands. Phys. Life Rev. 1\u201323 (2016)","DOI":"10.1016\/j.plrev.2016.02.001"},{"key":"2185_CR11","doi-asserted-by":"crossref","unstructured":"Li, S., Ma, X., Liang, H., Gorner, M., Ruppel, P., Fang, B., Sun, F., Zhang, J.: Vision-based teleoperation of shadow dexterous hand using end-to-end deep neural network. In: 2019 International Conference on Robotics and Automation (ICRA), pp. 416\u2013422. IEEE, Montreal,Canada (2019)","DOI":"10.1109\/ICRA.2019.8794277"},{"key":"2185_CR12","doi-asserted-by":"crossref","unstructured":"Wang, X.: Hand gesture recognition using sparse autoencoder-based deep neural network based on electromyography measurements. In: Proc. SPIE 10597, Nano-, Bio-, Info-Tech Sensors, 3D Syst, vol. II, 105971D (2018)","DOI":"10.1117\/12.2296382"},{"key":"2185_CR13","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1109\/MRA.2017.2751662","volume":"24","author":"C Piazza","year":"2017","unstructured":"Piazza, C., Catalano, M.G., Godfrey, S.B., Rossi, M., Grioli, G., Bianchi, M., Zhao, K., Bicchi, A.: The softhand pro-h: a hybrid body-controlled, electrically powered hand prosthesis for daily living and working. IEEE Robot. Autom. Mag. 24, 87\u2013101 (2017)","journal-title":"IEEE Robot. Autom. Mag."},{"key":"2185_CR14","unstructured":"Elkoura, G., Singh, K.: Handrix: animating the human hand. In: 2003 ACM SIGGRAPH\/Eurographics Symposium on Computer Animation (2003)"},{"key":"2185_CR15","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1109\/MRA.2015.2408772","volume":"22","author":"M Malvezzi","year":"2015","unstructured":"Malvezzi, M., Gioioso, G., Salvietti, G., Prattichizzo, D.: Syngrasp: a matlab toolbox for underactuated and compliant hands. IEEE Robot. Autom. Mag. 22, 52\u201368 (2015). https:\/\/doi.org\/10.1109\/MRA.2015.2408772","journal-title":"IEEE Robot. Autom. Mag."},{"key":"2185_CR16","doi-asserted-by":"crossref","unstructured":"Lin, Y., Zhao, H., Zhang, Y., Ding, H.: A data-driven motion mapping method for space teleoperation of kinematically dissimilar master\/slave robots. In: 2018 IEEE Int. Conf. Robot, Biomimetics, ROBIO, pp. 862\u2013867 (2018)","DOI":"10.1109\/ROBIO.2018.8665119"},{"key":"2185_CR17","doi-asserted-by":"crossref","unstructured":"Liu, W., Daruna, A., Chernova, S.: Cage: context-aware grasping engine. In: in 2020 IEEE International Conference on Robotics and Automation (ICRA), pp. 2550\u20132556 (2020). IEEE","DOI":"10.1109\/ICRA40945.2020.9197289"},{"issue":"3","key":"2185_CR18","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1109\/70.34763","volume":"5","author":"M Cutkosky","year":"1989","unstructured":"Cutkosky, M.: On grasp choice, grasp models, and the design of hands for manufacturing tasks. IEEE Trans. Robot. Autom. 5(3), 269\u2013279 (1989)","journal-title":"IEEE Trans. Robot. Autom."},{"key":"2185_CR19","doi-asserted-by":"crossref","unstructured":"Song, D., Huebner, K., Kyrki, V., Kragic, D.: Learning task constraints for robot grasping using graphical models. In: International Conference on Intelligent Robots and Systems (IROS), pp. 1579\u20131585 (2010). IEEE","DOI":"10.1109\/IROS.2010.5649406"},{"issue":"3","key":"2185_CR20","doi-asserted-by":"publisher","first-page":"546","DOI":"10.1109\/TRO.2015.2409912","volume":"31","author":"D Song","year":"2015","unstructured":"Song, D., Ek, C.H., Huebner, K., Kragic, D.: Task-based robot grasp planning using probabilistic inference. IEEE Trans. Rob. 31(3), 546\u2013561 (2015)","journal-title":"IEEE Trans. Rob."},{"key":"2185_CR21","doi-asserted-by":"crossref","unstructured":"Song, D., Ek, C.H., Huebner, K., Kragic, D.: Multivariate discretization for bayesian network structure learning in robot grasping. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1944\u20131950 (2011). IEEE","DOI":"10.1109\/ICRA.2011.5979666"},{"issue":"4","key":"2185_CR22","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1109\/THMS.2017.2647882","volume":"47","author":"S Li","year":"2017","unstructured":"Li, S., Zhang, X.: Implicit intention communication in human-robot interaction through visual behavior studies. IEEE Trans. Human-Machine Syst. 47(4), 437\u2013448 (2017)","journal-title":"IEEE Trans. Human-Machine Syst."},{"issue":"12","key":"2185_CR23","doi-asserted-by":"publisher","first-page":"2824","DOI":"10.1109\/TBME.2017.2677902","volume":"64","author":"S Li","year":"2017","unstructured":"Li, S., Zhang, X., Webb, J.D.: 3-d-gaze-based robotic grasping through mimicking human visuomotor function for people with motion impairments. IEEE Trans. Biomed. Eng. 64(12), 2824\u20132835 (2017)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"2185_CR24","doi-asserted-by":"crossref","unstructured":"Handa, A., Wyk, K., Yang, W., Liang, J., Chao, Y.-W., Wan, Q., Birchfield, S., Ratliff, N., Fox, D.: Dexpilot: vision-based teleoperation of dexterous robotic hand-arm system. In: IEEE International Conference on Robotics and Automation (ICRA) (2020)","DOI":"10.1109\/ICRA40945.2020.9197124"},{"key":"2185_CR25","doi-asserted-by":"crossref","unstructured":"Song, D., Kyriazis, N., Oikonomidis, I., Papazov, C., Argyros, A., Burschka, D., Kragic, D.: Predicting human intention in visual observations of hand\/object interactions. In: Proceedings IEEE International Conference on Robotics and Automation (ICRA) (2013). IEEE","DOI":"10.1109\/ICRA.2013.6630785"},{"issue":"12","key":"2185_CR26","doi-asserted-by":"publisher","first-page":"13237","DOI":"10.1109\/TCYB.2021.3107357","volume":"52","author":"X Yu","year":"2022","unstructured":"Yu, X., Li, B., He, W., Feng, Y., Cheng, L., Silvestre, C.: Adaptive-constrained impedance control for human\u2013robot co-transportation. IEEE Transactions on Cybernetics. 52(12), 13237\u201313249 (2022). https:\/\/doi.org\/10.1109\/TCYB.2021.3107357","journal-title":"IEEE Transactions on Cybernetics."},{"key":"2185_CR27","doi-asserted-by":"crossref","unstructured":"Li, S., Bowman, M., Nobarani, H., Zhang, X.: Inference of manipulation intent in teleoperation for robotic assistance. J. Intell. Robot. Syst. (2020)","DOI":"10.1007\/s10846-019-01125-8"},{"key":"2185_CR28","doi-asserted-by":"crossref","unstructured":"Hatakeya, N., Furuta, K.: Bayesian network modeling of operator\u2019s intent inference. In: Human Factors Meeting., pp. 4\u201355 (2003). IEEE","DOI":"10.1109\/HFPP.2002.1042847"},{"key":"2185_CR29","doi-asserted-by":"publisher","first-page":"796","DOI":"10.1016\/j.chb.2016.06.016","volume":"63","author":"H Park","year":"2016","unstructured":"Park, H., Lee, S., Lee, M., Chang, M.S., Kwak, H.W.: Using eye movement data to infer human behavioral intentions. Comput. Hum. Behav. 63, 796\u2013804 (2016)","journal-title":"Comput. Hum. Behav."},{"key":"2185_CR30","doi-asserted-by":"crossref","unstructured":"S.Javdani, S.S., Bagnell, A.: Shared autonomy via hindsight optimization. In: Robotics, Science, and Systems, vol. XI (2015)","DOI":"10.15607\/RSS.2015.XI.032"},{"key":"2185_CR31","unstructured":"Reddy, S., Dragan, A.D., Levine, S.: Where do you think you\u2019re going? inferring beliefs about dynamics from behavior. In: Proceedings of the 32nd International Conference on Neural Information Processing Systems, pp. 1461\u20131472 (2018)"},{"issue":"1","key":"2185_CR32","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1109\/LRA.2016.2593928","volume":"2","author":"D Gopinath","year":"2017","unstructured":"Gopinath, D., Jain, S., Argall, B.D.: Human-in-the-loop optimization of shared autonomy in assistive robotics. IEEE Robot. Autom. Lett. 2(1), 247\u2013254 (2017)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"2185_CR33","doi-asserted-by":"crossref","unstructured":"Young, M., Miller, C., Bi, Y., Chen, W., Argall, B.D.: Formalized task characterization for human-robot autonomy allocation. In: IEEE International Conference on Robotics and Automation (ICRA) (2019)","DOI":"10.1109\/ICRA.2019.8793475"},{"key":"2185_CR34","doi-asserted-by":"crossref","unstructured":"Mulling, K., Venkatraman, A., Valois, J.-S., Downey, J., Weiss, J., Javdani, S., Hebert, M., Schwartz, A., Collinger, J., Bagnell, A.: Autonomy Infused Teleoperation with Application to BCI Manipulation. Science and Systems XI, Robotics (2015)","DOI":"10.15607\/RSS.2015.XI.039"},{"key":"2185_CR35","unstructured":"Abbott, J.J., Marayong, P., Okamura, A.M.: Haptic virtual fixtures for robot-assisted manipulation. Robot. Res. (2007)"},{"key":"2185_CR36","doi-asserted-by":"crossref","unstructured":"Webb, J.D., Li, S., Zhang, X.: Using visuomotor tendencies to increase control performance in teleoperation. In: American Control Conference (ACC), pp. 7110\u20137116 (2016)","DOI":"10.1109\/ACC.2016.7526794"},{"key":"2185_CR37","doi-asserted-by":"crossref","unstructured":"Feygin, D., Keehner, M., Tendick, F.: Haptic guidance: experimental evaluation of a haptic training method for a perceptual motor skill. In: HAPTICS IEEE, pp. 40\u201347 (2002)","DOI":"10.1109\/HAPTIC.2002.998939"},{"key":"2185_CR38","unstructured":"Li, M., Okamura, A.M.: Recognition of operator motions for real-time assistance using virtual fixtures. In: HAPTICS IEEE, pp. 125\u2013131 (2003)"},{"key":"2185_CR39","doi-asserted-by":"crossref","unstructured":"Abi-Farraj, F., Pacchierotti, C., Arenz, O., Neumann, G., Giordano, P.R.: A haptic shared-control architecture for guided multi-target robotic grasping. IEEE Transaction on Haptics, 270\u2013285 (2019)","DOI":"10.1109\/TOH.2019.2913643"},{"key":"2185_CR40","doi-asserted-by":"crossref","unstructured":"Parsa, S., Kamale, D., Mghames, S., Nazari, K., Pardi, T., Srinivasan, A.R., Neumann, G., Hanheide, M., Amir, G.E.: Haptic-guided shared control grasping: collision-free manipulation. In: IEEE International Conference on Automation Science and Engineering (CASE) (2020)","DOI":"10.1109\/CASE48305.2020.9216789"},{"key":"2185_CR41","unstructured":"Hu, H., Li, J., Xie, Z., Wang, B., Liu, H., Hirzinger, G.: A robot arm\/hand teleoperation system with telepresence and shared control. In: IEEE\/ASME International Conference on Advanced Intelligent Mechatronics, Monterey, CA (2005)"},{"key":"2185_CR42","doi-asserted-by":"publisher","unstructured":"Bowman, M., Zhang, X.: We-filter: adaptive acceptance criteria for filter-based shared autonomy. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 12528\u201312534 (2023). https:\/\/doi.org\/10.1109\/ICRA48891.2023.10161228","DOI":"10.1109\/ICRA48891.2023.10161228"},{"issue":"3","key":"2185_CR43","doi-asserted-by":"publisher","first-page":"1415","DOI":"10.1109\/LRA.2023.3239313","volume":"8","author":"M Bowman","year":"2023","unstructured":"Bowman, M., Zhang, X.: Dimension-specific shared autonomy for handling disagreement in telemanipulation. IEEE Robotics and Automation Letters. 8(3), 1415\u20131422 (2023). https:\/\/doi.org\/10.1109\/LRA.2023.3239313","journal-title":"IEEE Robotics and Automation Letters."},{"key":"2185_CR44","doi-asserted-by":"crossref","unstructured":"Oh, Y., Toussaint, M., Mainprice, J.: Learning to arbitrate human and robot control using disagreement between sub-policies. In: 2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5305\u20135311 (2021). IEEE","DOI":"10.1109\/IROS51168.2021.9636049"},{"key":"2185_CR45","unstructured":"Lugaresi, C., Tang, J., Nash, H., McClanahan, C., Uboweja, E., Hays, M., Zhang, F., Chang, C.-L., Yong, M., Lee, J., W.-T.Chang, W.H., Georg, M., Grundmann, M.: Mediapipe: a framework for perceiving and processing reality. In: Third Workshop on Computer Vision for AR\/VR at IEEE Computer Vision and Pattern Recognition, (2019)"},{"issue":"3","key":"2185_CR46","first-page":"136","volume":"1","author":"JR Lewis","year":"2006","unstructured":"Lewis, J.R., Sauro, J.: When 100% really isn\u2019t 100% improving the accuracy of small-sample estimates of completion rates. J. Usability Stud. 1(3), 136\u2013150 (2006)","journal-title":"J. Usability Stud."},{"key":"2185_CR47","doi-asserted-by":"crossref","unstructured":"Sauro, J., Lewis, J.R.: Estimating completion rates from small samples using binomial confidence intervals: comparisons and recommendations. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 49, pp. 2100\u20132103 (2005)","DOI":"10.1177\/154193120504902407"},{"key":"2185_CR48","doi-asserted-by":"crossref","unstructured":"Sauro, J., Lewis, J.R.: Average task times in usability tests: What to report? In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI \u201910, ACM, pp. 2347\u20132350 (2010)","DOI":"10.1145\/1753326.1753679"},{"key":"2185_CR49","doi-asserted-by":"publisher","unstructured":"Salvietti, G., Meli, L., Gioioso, G., Malvezzi, M., Prattichizzo, D.: Multicontact bilateral telemanipulation with kinematic asymmetries. IEEE\/ASME Transactions on Mechatronics. 22(1), 445\u2013456 (2017-02). https:\/\/doi.org\/10.1109\/TMECH.2016.2606895","DOI":"10.1109\/TMECH.2016.2606895"},{"key":"2185_CR50","doi-asserted-by":"crossref","unstructured":"Reddy, S., Dragan, A., Levine, S.: Shared autonomy via deep reinforcement learning. In: Proceedings of Robotics: Science and Systems, Pittsburgh, Pennsylvania (2018)","DOI":"10.15607\/RSS.2018.XIV.005"},{"issue":"1","key":"2185_CR51","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","volume":"43","author":"Z Cao","year":"2021","unstructured":"Cao, Z., Hidalgo, G., Simon, T., Wei, S.-E., Sheikh, Y.: Openpose: realtime multi-person 2d pose estimation using part affinity fields. IEEE Trans. Pattern Anal. Mach. Intell. 43(1), 172\u2013186 (2021). https:\/\/doi.org\/10.1109\/TPAMI.2019.2929257","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2185_CR52","unstructured":"Chen, K., Wang, J., Pang, J., Cao, Y., Xiong, Y., Li, X., Sun, S., Feng, W., Liu, Z., Xu, J., et al.: Mmdetection: open mmlab detection toolbox and benchmark (2019). arXiv preprint arXiv:1906.07155"},{"key":"2185_CR53","doi-asserted-by":"crossref","unstructured":"Broad, A., Abraham, I., Murphey, T., Argall, B.: Data-driven koopman operators for model-based shared control of human-machine systems. Int. J. Robot. Res. 39(9), 1178\u20131195 (2020)","DOI":"10.1177\/0278364920921935"},{"issue":"1","key":"2185_CR54","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s10514-021-10005-w","volume":"46","author":"DP Losey","year":"2022","unstructured":"Losey, D.P., Jeon, H.J., Li, M., Srinivasan, K., Mandlekar, A., Garg, A., Bohg, J., Sadigh, D.: Learning latent actions to control assistive robots. Auton. Robot. 46(1), 115\u2013147 (2022)","journal-title":"Auton. Robot."},{"key":"2185_CR55","doi-asserted-by":"crossref","unstructured":"Rakita, D., Mutlu, B., Gleicher, M., Hiatt, L.M.: Shared dynamic curves: a shared-control telemanipulation method for motor task training. In: Proceedings of the 2018 ACM\/IEEE International Conference on Human-Robot Interaction, pp. 23\u201331 (2018)","DOI":"10.1145\/3171221.3171278"},{"issue":"2","key":"2185_CR56","first-page":"3","volume":"8","author":"AM Lund","year":"2001","unstructured":"Lund, A.M.: Measuring usability with the use questionnaire. Usability interface. 8(2), 3\u20136 (2001)","journal-title":"Usability interface."}],"container-title":["Journal of Intelligent & Robotic Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10846-024-02185-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10846-024-02185-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10846-024-02185-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T03:18:52Z","timestamp":1736306332000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10846-024-02185-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,3]]},"references-count":56,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["2185"],"URL":"https:\/\/doi.org\/10.1007\/s10846-024-02185-1","relation":{},"ISSN":["1573-0409"],"issn-type":[{"value":"1573-0409","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,3]]},"assertion":[{"value":"18 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 December 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The experiments were approved by the Institutional Review Board (IRB) of Colorado School of Mines. Prior to participating in the study, a short introduction was provided to the participants, including technologies involved, the system setup, and the purpose of the study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval"}},{"value":"Written consent was obtained from all individual participants included in the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consents to Participate"}},{"value":"The participants have consented to the submission of the case report to the journal.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for Publication"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}}],"article-number":"167"}}