Abstract
When hand motions in haptic exploration are investigated, the measurement methods used might actually restrict the movements or the perception. The perception might be reduced because the skin is covered, e.g. with a data glove. Also, the range of possible motions might be limited, e.g. by wired sensors. Here, a model of the hand is proposed that is calculated from data obtained from a small number of sensors (6). The palmar side of the hand is not covered by sensors or tape, leaving the skin free for cutaneous perception. The hand is then modeled as 16 rigid 3D segments, with a hand palm and 5 individual fingers with 3 phalanges each. This model can be used for movement analysis in object exploration and contact point analysis. A validation experiment of an object manipulation task and a contact analysis showed good qualitative agreement of the model with the control measurements. The calculations, assumptions and limitations of the model are discussed in comparison with other methods.
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References
Aristidou A, Lasenby J (2010) Motion capture with constrained inverse kinematics for real-time hand tracking. In: 4th International symposium on communications, control, and signal processing, ISCCSP 2010, IEEE, pp 1–5
Aristidou A, Lasenby J (2011) FABRIK: A fast, iterative solver for the Inverse Kinematics problem. Graphical Models 73(5):243–260
Braido P, Zhang X (2004) Quantitative analysis of finger motion coordination in hand manipulative and gestic acts. Hum Mov Sci 22(6):661–678
Bullock IM, Borras J, Dollar AM (2012) Assessing assumptions in kinematic hand models: A review. In: Proceedings of the IEEE RAS and EMBS international conference on biomedical robotics and biomechatronics, IEEE, pp 139–146
Cerveri P, De Momi E, Lopomo N, Baud-Bovy G, Barros RML, Ferrigno G (2007) Finger kinematic modeling and real-time hand motion estimation. Ann Biomed Eng 35(11):1989–2002
Dipietro L, Sabatini AM, Dario P (2008) A survey of glove-based systems and their applications. IEEE Trans Syst Man Cybern Part C: Appl Rev 38(4):461–482
Fu Q, Santello M (2010) Tracking whole hand kinematics using extended Kalman filter. In: 2010 Annual international conference of the IEEE engineering in medicine and biology society, EMBC’10, pp 4606–4609, doi:10.1109/IEMBS.2010.5626513
Gabiccini M, Stillfried G, Marino H, Bianchi M (2013) A data-driven kinematic model of the human hand with soft-tissue artifact compensation mechanism for grasp synergy analysis. In: IEEE International conference on intelligent robots and systems, pp 3738–3745, doi:10.1109/IROS.2013.6696890
Gustus A, Stillfried G, Visser J, Jörntell H, van der Smagt P (2012) Human hand modelling: kinematics, dynamics, applications. Biol Cybernet 106(11–12):741–755
Jansen SEM, Bergmann Tiest WM, Kappers AML (2015) Haptic exploratory behavior during object discrimination: A novel automatic annotation method. Plos One 10(2):e0117,017, doi:10.1371/journal.pone.0117017
Jansen SEM, Bergmann Tiest WM, Kappers AML (2013) Identifying haptic exploratory procedures by analyzing hand dynamics and contact force. IEEE Trans Haptics 6(4):464–472
Kahrimanovic M, Bergmann Tiest WM, Kappers AML (2011) Discrimination thresholds for haptic perception of volume, surface area, and weight. Atten Percept Psychophys 73(8):2649–2656
Kalagher H, Jones SS (2011) Young children’s haptic exploratory procedures. J Exp Child Psychol 110(4):592–602
Klatzky RL, Lederman SJ, Reed C (1989) Haptic integration of object properties—texture, hardness, and planar contour. J Exp Psychol Hum Percept Perform 15(1):45–57
Lederman SJ, Klatzky RL (1987) Hand movements—a window into haptic object recognition. Cogn Psychol 19(3):342–368
Lien CC, Huang CL (1998) Model-based articulated hand motion tracking for gesture recognition. Image Vision Comput 16(2):121–134
Liu H (2011) Exploring human hand capabilities into embedded multifingered object manipulation. IEEE Trans Ind Inform 7(3):389–398
Miyata N, Kouchi M, Hurihara T, Mochimaru M (2004) Modeling of human hand link structure from optical motion capture data. Intell Robots Syst 3:2129–2135
Nataraj R, Li ZMM (2013) Robust identification of three-dimensional thumb and index finger kinematics with a minimal set of markers. J Biomech Eng 135(9):91002
Overvliet KE, Smeets JBJ, Brenner E (2007) Haptic search with finger movements: using more fingers does not necessarily reduce search times. Exp Brain Res 182(3):427–434
Plaisier MA, Bergmann Tiest WM, Kappers AML (2008) Haptic pop-out in a hand sweep. Acta Psychol 128(2):368–377
Plaisier MA, Bergmann Tiest WM, Kappers AML (2009a) One, two, three, many—Subitizing in active touch. Acta Psychol 131(2):163–170
Plaisier MA, Bergmann Tiest WM, Kappers AML (2009b) Salient features in 3-D haptic shape perception. Atten Percept Psychophys 71(2):421–430
Sancho-Bru JL, Mora MC, León BE, Pérez-González A, Iserte JL, Morales A (2014) Grasp modelling with a biomechanical model of the hand. Comput Methods Biomech Biomed Eng 17(4):297–310
Smith AM, Gosselin G, Houde B (2002) Deployment of fingertip forces in tactile exploration. Exp Brain Res 147(2):209–218
Thakur PH, Bastian AJ, Hsiao SS (2008) Multidigit movement synergies of the human hand in an unconstrained haptic exploration task. J Neurosci 28(6):1271–1281
Todorov E (2007) Probabilistic inference of multijoint movements, skeletal parameters and marker attachments from diverse motion capture data. IEEE Trans Biomed Eng 54(11):1927–1939. doi:10.1109/TBME.2007.903521
van Polanen V, Bergmann Tiest WM, Kappers AML (2012a) Haptic pop-out of movable stimuli. Atten Percept Psychophys 74(1):204–215
van Polanen V, Bergmann Tiest WM, Kappers AML (2014) Target contact and exploration strategies in haptic search. Sci Reports 4:6254. doi:10.1038/srep06254
van Polanen V, Bergmann Tiest WM, Kappers AML (2012b) Haptic search for hard and soft spheres. PLOS ONE 7(10):e45298
Withagen A, Kappers AML, Vervloed MPJ, Knoors H, Verhoeven L (2013) The use of exploratory procedures by blind and sighted adults and children. Atten Percept Psychophys 75(7):1451–1464
Wu YWY, Huang T (1999) Capturing articulated human hand motion: a divide-and-conquer approach. In: Proceedings of the seventh IEEE International conference on computer vision, IEEE 1:606–611
Zhang X, Lee SW, Braido P (2003) Determining finger segmental centers of rotation in flexion-extension based on surface marker measurement. J Biomech 36(8):1097–1102
Acknowledgments
This work was supported by the European Commission with the Collaborative Project no. 248587, “THE Hand Embodied”, within the FP7-ICT-2009-4-2-1 program “Cognitive Systems and Robotics”.
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van Polanen, V., Bergmann Tiest, W.M., Kappers, A.M.L. (2016). A Simple Model of the Hand for the Analysis of Object Exploration. In: Bianchi, M., Moscatelli, A. (eds) Human and Robot Hands. Springer Series on Touch and Haptic Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-26706-7_14
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DOI: https://doi.org/10.1007/978-3-319-26706-7_14
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