Literature DB >> 23132432

Human hand modelling: kinematics, dynamics, applications.

Agneta Gustus1, Georg Stillfried, Judith Visser, Henrik Jörntell, Patrick van der Smagt.   

Abstract

An overview of mathematical modelling of the human hand is given. We consider hand models from a specific background: rather than studying hands for surgical or similar goals, we target at providing a set of tools with which human grasping and manipulation capabilities can be studied, and hand functionality can be described. We do this by investigating the human hand at various levels: (1) at the level of kinematics, focussing on the movement of the bones of the hand, not taking corresponding forces into account; (2) at the musculotendon structure, i.e. by looking at the part of the hand generating the forces and thus inducing the motion; and (3) at the combination of the two, resulting in hand dynamics as well as the underlying neurocontrol. Our purpose is to not only provide the reader with an overview of current human hand modelling approaches but also to fill the gaps with recent results and data, thus allowing for an encompassing picture.

Entities:  

Mesh:

Year:  2012        PMID: 23132432     DOI: 10.1007/s00422-012-0532-4

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  13 in total

1.  How pigeons couple three-dimensional elbow and wrist motion to morph their wings.

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2.  Muscle synergies for predicting non-isometric complex hand function for commanding FES neuroprosthetic hand systems.

Authors:  Natalie M Cole; A Bolu Ajiboye
Journal:  J Neural Eng       Date:  2019-08-21       Impact factor: 5.379

3.  [Accuracy of key point matrix technology based contactless automatic measurement for joint motion of hand].

Authors:  Lulu Lü; Jiantao Yang; Fanbin Gu; Jingyuan Fan; Chaoyang Wang; Qingtang Zhu; Xiaolin Liu
Journal:  Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi       Date:  2022-05-15

4.  A synergy-based hand control is encoded in human motor cortical areas.

Authors:  Andrea Leo; Giacomo Handjaras; Matteo Bianchi; Hamal Marino; Marco Gabiccini; Andrea Guidi; Enzo Pasquale Scilingo; Pietro Pietrini; Antonio Bicchi; Marco Santello; Emiliano Ricciardi
Journal:  Elife       Date:  2016-02-15       Impact factor: 8.140

Review 5.  A structured overview of trends and technologies used in dynamic hand orthoses.

Authors:  Ronald A Bos; Claudia J W Haarman; Teun Stortelder; Kostas Nizamis; Just L Herder; Arno H A Stienen; Dick H Plettenburg
Journal:  J Neuroeng Rehabil       Date:  2016-06-29       Impact factor: 4.262

6.  Real-time inverse kinematics for the upper limb: a model-based algorithm using segment orientations.

Authors:  Bence J Borbély; Péter Szolgay
Journal:  Biomed Eng Online       Date:  2017-01-17       Impact factor: 2.819

Review 7.  Hand Rehabilitation Robotics on Poststroke Motor Recovery.

Authors:  Zan Yue; Xue Zhang; Jing Wang
Journal:  Behav Neurol       Date:  2017-11-02       Impact factor: 3.342

8.  Effects of vibrotactile feedback and grasp interface compliance on perception and control of a sensorized myoelectric hand.

Authors:  Andres E Pena; Liliana Rincon-Gonzalez; James J Abbas; Ranu Jung
Journal:  PLoS One       Date:  2019-01-16       Impact factor: 3.240

9.  A large calibrated database of hand movements and grasps kinematics.

Authors:  Néstor J Jarque-Bou; Manfredo Atzori; Henning Müller
Journal:  Sci Data       Date:  2020-01-09       Impact factor: 6.444

10.  A calibrated database of kinematics and EMG of the forearm and hand during activities of daily living.

Authors:  Néstor J Jarque-Bou; Margarita Vergara; Joaquín L Sancho-Bru; Verónica Gracia-Ibáñez; Alba Roda-Sales
Journal:  Sci Data       Date:  2019-11-11       Impact factor: 6.444

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