{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T07:28:42Z","timestamp":1743146922136,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031246692"},{"type":"electronic","value":"9783031246708"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-24670-8_26","type":"book-chapter","created":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T08:45:32Z","timestamp":1675241132000},"page":"288-298","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards a\u00a0Framework for\u00a0the\u00a0Whole-Body Teleoperation of\u00a0a\u00a0Humanoid Robot in\u00a0Healthcare Settings"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4866-5592","authenticated-orcid":false,"given":"Francesco","family":"Porta","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9550-3740","authenticated-orcid":false,"given":"Carmine Tommaso","family":"Recchiuto","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2338-8995","authenticated-orcid":false,"given":"Maura","family":"Casadio","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7789-4311","authenticated-orcid":false,"given":"Antonio","family":"Sgorbissa","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,2]]},"reference":[{"issue":"6","key":"26_CR1","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1080\/10447310802205776","volume":"24","author":"A Bangor","year":"2008","unstructured":"Bangor, A., Kortum, P.T., Miller, J.T.: An empirical evaluation of the system usability scale. International Journal of Human-Computer Interaction 24(6), 574\u2013594 (2008)","journal-title":"International Journal of Human-Computer Interaction"},{"key":"26_CR2","doi-asserted-by":"crossref","unstructured":"Bhaskar, S., et al.: Designing futuristic telemedicine using artificial intelligence and robotics in the covid-19 era. Front. Public Health 8 (2020)","DOI":"10.3389\/fpubh.2020.556789"},{"key":"26_CR3","unstructured":"Brooke, J.: SUS: a quick and dirty usability scale. Usability Eval. Ind. 189 (1995)"},{"issue":"1","key":"26_CR4","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","volume":"43","author":"Z Cao","year":"2019","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 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"26_CR5","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1016\/j.rcim.2017.04.001","volume":"48","author":"L Caruso","year":"2017","unstructured":"Caruso, L., Russo, R., Savino, S.: Microsoft Kinect V2 vision system in a manufacturing application. Rob. Comput. Integr. Manuf. 48, 174\u2013181 (2017)","journal-title":"Rob. Comput. Integr. Manuf."},{"key":"26_CR6","unstructured":"Dalin, E., Bergonzani, I., Anne, T., Ivaldi, S., Mouret, J.B.: Whole-body teleoperation of the TALOS humanoid robot: preliminary results. In: ICRA 2021\u20135th Workshop on Teleoperation of Dynamic Legged Robots in Real Scenarios (2021)"},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"Filiatrault, S., Cr\u00e9tu, A.: Human arm motion imitation by a humanoid robot. In: 2014 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Proceedings, pp. 31\u201336 (2014)","DOI":"10.1109\/ROSE.2014.6952979"},{"key":"26_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijhcs.2021.102707","volume":"156","author":"A Grabowski","year":"2021","unstructured":"Grabowski, A., Jankowski, J., Wodzy\u0144ski, M.: Teleoperated mobile robot with two arms: the influence of a human-machine interface, VR training and operator age. Int. J. Hum. Comput. Stud. 156, 102707 (2021)","journal-title":"Int. J. Hum. Comput. Stud."},{"key":"26_CR9","doi-asserted-by":"crossref","unstructured":"Hart, S.: Nasa-task load index (NASA-TLX); 20 years later. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 50 (2006)","DOI":"10.1037\/e577632012-009"},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Hart, S.G., Staveland, L.E.: Development of NASA-TLX (task load index): results of empirical and theoretical research. In: Hancock, P.A., Meshkati, N. (eds.) Human Mental Workload, Advances in Psychology, vol. 52, pp. 139\u2013183. North-Holland (1988)","DOI":"10.1016\/S0166-4115(08)62386-9"},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Iskakov, K., Burkov, E., Lempitsky, V., Malkov, Y.: Learnable triangulation of human pose. In: International Conference on Computer Vision (ICCV) (2019)","DOI":"10.1109\/ICCV.2019.00781"},{"issue":"1","key":"26_CR12","doi-asserted-by":"publisher","first-page":"212","DOI":"10.1109\/TSMCB.2008.2004505","volume":"39","author":"F Mastrogiovanni","year":"2009","unstructured":"Mastrogiovanni, F., Sgorbissa, A., Zaccaria, R.: Robust navigation in an unknown environment with minimal sensing and representation. IEEE Trans. Syst. Man Cybern. B Cybern. 39(1), 212\u2013229 (2009). https:\/\/doi.org\/10.1109\/TSMCB.2008.2004505","journal-title":"IEEE Trans. Syst. Man Cybern. B Cybern."},{"key":"26_CR13","unstructured":"Mei, B.D., Lega, I., Sampaolo, L., Valli, M.: Covid-19: stress management among healthcare workers (2020). https:\/\/www.epicentro.iss.it\/en\/coronavirus\/sars-cov-2-stress-management-healthcare-workers"},{"issue":"3","key":"26_CR14","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1109\/MRA.2018.2833157","volume":"25","author":"AK Pandey","year":"2018","unstructured":"Pandey, A.K., Gelin, R.: A mass-produced sociable humanoid robot: pepper: the first machine of its kind. IEEE Rob. Autom. Mag. 25(3), 40\u201348 (2018)","journal-title":"IEEE Rob. Autom. Mag."},{"key":"26_CR15","doi-asserted-by":"publisher","unstructured":"Papadopoulos, C., et al..: The caresses randomised controlled trial: exploring the health-related impact of culturally competent artificial intelligence embedded into socially assistive robots and tested in older adult care homes. Int. J. Soc. al Robotics 14(1), 245\u2013256 (2022). https:\/\/doi.org\/10.1007\/s12369-021-00781-x","DOI":"10.1007\/s12369-021-00781-x"},{"key":"26_CR16","series-title":"Human\u2013Computer Interaction Series","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/978-3-030-17107-0_10","volume-title":"Social Robots: Technological, Societal and Ethical Aspects of Human-Robot Interaction","author":"J Parviainen","year":"2019","unstructured":"Parviainen, J., Turja, T., Van Aerschot, L.: Social robots and human touch in care: the perceived usefulness of robot assistance among healthcare professionals. In: Korn, O. (ed.) Social Robots: Technological, Societal and Ethical Aspects of Human-Robot Interaction. HIS, pp. 187\u2013204. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-17107-0_10"},{"key":"26_CR17","doi-asserted-by":"crossref","unstructured":"Recchiuto, C., Sgorbissa, A., Zaccaria, R.: Visual feedback with multiple cameras in a UAVs human-swarm interface. Robot. Auton. Syst. 80(C), 43\u201354 (2016)","DOI":"10.1016\/j.robot.2016.03.006"},{"key":"26_CR18","doi-asserted-by":"crossref","unstructured":"Riley, M., Ude, A., Wade, K., Atkeson, C.: Enabling real-time full-body imitation: a natural way of transferring human movement to humanoids. In: 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422), vol. 2, pp. 2368\u20132374 (2003)","DOI":"10.1109\/ROBOT.2003.1241947"},{"key":"26_CR19","doi-asserted-by":"crossref","unstructured":"Rolley-Parnell, E., et al.: Bi-manual articulated robot teleoperation using an external rgb-d range sensor. In: 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), pp. 298\u2013304 (2018)","DOI":"10.1109\/ICARCV.2018.8581174"},{"issue":"8","key":"26_CR20","doi-asserted-by":"publisher","first-page":"1167","DOI":"10.1017\/S0263574718000309","volume":"36","author":"M Tomi\u0107","year":"2018","unstructured":"Tomi\u0107, M., Chevallereau, C., Jovanovi\u0107, K., Potkonjak, V., Rodi\u0107, A.: Human to humanoid motion conversion for dual-arm manipulation tasks. Robotica 36(8), 1167\u20131187 (2018)","journal-title":"Robotica"},{"key":"26_CR21","doi-asserted-by":"crossref","unstructured":"Wang, Z., Liang, R., Chen, Z., Liang, B.: Fast and intuitive kinematics mapping for human-robot motion imitating: a virtual-joint-based approach. IFAC-PapersOnLine 53(2), 10011\u201310018 (2020). 21st IFAC World Congress","DOI":"10.1016\/j.ifacol.2020.12.2720"},{"key":"26_CR22","series-title":"Springer Proceedings in Advanced Robotics","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1007\/978-3-030-28619-4_28","volume-title":"Robotics Research","author":"D Whitney","year":"2020","unstructured":"Whitney, D., Rosen, E., Phillips, E., Konidaris, G., Tellex, S.: Comparing robot grasping teleoperation across desktop and virtual reality with ROS reality. In: Amato, N.M., Hager, G., Thomas, S., Torres-Torriti, M. (eds.) Robotics Research. SPAR, vol. 10, pp. 335\u2013350. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-28619-4_28"},{"key":"26_CR23","doi-asserted-by":"crossref","unstructured":"Wu, H., Xiao, B.: 3D human pose estimation via explicit compositional depth maps. Proc. AAAI Conf. Artif. Intell. 34(07), 12378\u201312385 (2020)","DOI":"10.1609\/aaai.v34i07.6923"},{"key":"26_CR24","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Niu, Y., Yan, Z., Lin, S.: Real-time whole-body imitation by humanoid robots and task-oriented teleoperation using an analytical mapping method and quantitative evaluation. Appl. Sci. 8(10) (2018)","DOI":"10.3390\/app8102005"}],"container-title":["Lecture Notes in Computer Science","Social Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-24670-8_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,13]],"date-time":"2024-10-13T11:09:10Z","timestamp":1728817750000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-24670-8_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031246692","9783031246708"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-24670-8_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"2 February 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Social Robotics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Florence","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 December 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 December 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socrob2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.icsr2022.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EquinOCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"143","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"111","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"78% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}