[40] Andrea H Mason and Christine L MacKenzie. Grip forces when passing an object to a partner. Experimental brain research, 163(2):173-187, 2005.
[41] Lona Mody, Douglas K Miller, Joanne M McGloin, Marcie Freeman, Edward R Marcantonio, Jay Magaziner, and Stephanie Studenski. Recruitment and retention of older adults in aging research: (see editorial comments by dr. stephanie studenski, pp 2351-2352). Journal of the American Geriatrics Society, 56(12):2340-2348, 2008.
[42] AJung Moon, Daniel M Troniak, Brian Gleeson, Matthew KXJ Pan, Minhua Zheng, Benjamin A Blumer, Karon MacLean, and Elizabeth A Croft. Meet me where i'm gazing: how shared attention gaze affects human-robot handover timing. In HRI, pages 334–341, NJ, 2014. IEEE.
[43] NCSBN. NCSBN Research Projects Significant Nursing Workforce Shortages and Crisis. https://www.ncsbn.org/news/ncsbn-research-projects-significant-nursing-workforce-shortages-and-crisis, Apr 2023.
[44] Valerio Ortenzi, Akansel Cosgun, Tommaso Pardi, Wesley P Chan, Elizabeth Croft, and Dana Kulic. Object handovers: a review for robotics. ToR, 37(6):1855-1873, 2021.
[45] Matthew KXJ Pan, Elizabeth A Croft, and Günter Niemeyer. Exploration of geometry and forces occurring within human-to-robot handovers. In 2018 IEEE Haptics Symposium (HAPTICS), pages 327–333. IEEE, 2018.
[46] Sina Parastegari, Bahareh Abbasi, Ehsan Noohi, and Miloš Zefran. Modeling human reaching phase in human-human object handover with application in robot-human handover. In IROS, pages 3597-3602, NJ, 2017. IEEE.
[47] Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas. Pointnet: Deep learning on point sets for 3d classification and segmentation. arXiv preprint arXiv:1612.00593, 2016.
[48] Robin Rasch, Sven Wachsmuth, and Matthias König. Understanding movements of hand-over between two persons to improve humanoid robot systems. In Humanoids, pages 856-861, NJ, 2017. IEEE.
[49] Fadime Sener, Dibyadip Chatterjee, Daniel Shelepop, Kun He, Dipika Singhania, Robert Wang, and Angela Yao. Assembly101: A large-scale multi-view video dataset for understanding procedural activities. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 21096-21106, 2022.
[50] Kyle Strabala, Min Kyung Lee, Anca Dragan, Jodi Forlizzi, and Siddhartha S Srinivasa. Learning the communication of intent prior to physical collaboration. In RO-MAN, pages 968-973, NJ, 2012. IEEE.
[51] Omid Taheri, Nima Ghorbani, Michael J Black, and Dimitrios Tzionas. Grab: A dataset of whole-body human grasping of objects. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part IV 16, pages 581–600. Springer, 2020.
[52] Wouter Wolf, Jacques Launay, and Robin IM Dunbar. Joint attention, shared goals, and social bonding. British Journal of Psychology, 107(2):322-337, 2016.
[53] Jinyu Yang, Mingqi Gao, Zhe Li, Shang Gao, Fangjing Wang, and Feng Zheng. Track anything: Segment anything meets videos, 2023.
[54] Ruolin Ye, Wenqiang Xu, Zhendong Xue, Tutian Tang, Yanfeng Wang, and Cewu Lu. H2o: A benchmark for visual human-human object handover analysis. In ICCV, pages 15762-15771, NJ, 2021. IEEE.
[55] Minhua Zheng, AJung Moon, Elizabeth A Croft, and Max Q-H Meng. Impacts of robot head gaze on robot-to-human handovers. IJSR, 7(5):783-798, 2015.
[56] Christian Zimmermann, Duygu Ceylan, Jimei Yang, Bryan Russell, Max Argus, and Thomas Brox. Freihand: A dataset for markerless capture of hand pose and shape from single rgb images. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 813-822, 2019.