Uday Phutane
Uday Phutane
- 2011 B.Eng. in Mechanical Engineering, Sardar Patel College of Engineering, University of Mumbai, India
- 2011 – 2013 Assistant Manager, CAE – Vehicle Dynamics, Mahindra and Mahindra, Chennai, India
- 2013 – 2015 M.Sc. in Computational Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg
- 2016 – 2021 doctoral candidate, Institute of Applied Dynamics, Friedrich-Alexander-Universität Erlangen-Nürnberg
theses
2015
On the comparison of different muscle model dynamics using variational integrators (Master thesis, 2015)
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reviewed journal publications
2021
Evaluation of Optical and Radar Based Motion Capturing Technologies for Characterizing Hand Movement in Rheumatoid Arthritis — A Pilot Study
In: Sensors 21 (2021), Article No.: 1208
ISSN: 1424-8220
DOI: 10.3390/s21041208
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conferences and proceedings
2022
Feasibility of using optoelectronic measurement of hand movement for characterizing hand function in rheumatoid arthritis
75th EULAR (European Alliance of Associations for Rheumatology), European Congress of Rheumatology 2022 (Copenhagen, 2022-06-01 - 2022-06-04)
DOI: 10.1136/annrheumdis-2022-eular.1741
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Evaluation of marker-based motion capturing to charactherize basic hand movements in rheumatic patients
27th Congress of the European Society of Biomechanics (Porto, 2022-06-26 - 2022-06-29)
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Establishment and evaluation of a sensor-based method to assess hand function in patients with rheumatoid arthritis
conference, World Biomechanics Congress 2022 (Taipei (online), 2022-07-10 - 2022-07-14)
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Towards optimal control grasping simulations with the full hand
conference, 9th GACM Colloquium on Computational Mechanics - for Young Scientists from Academia and Industry (Essen, 2022-09-21 - 2022-09-23)
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Comparison of different approaches for the personalization of a kinematic hand model
conference, World Biomechanics Congress 2022 (Taipei (Online), 2022-07-10 - 2022-07-14)
URL: https://www.wcb2022.com
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2021
Geometric numerical integration in simulation and optimal control of biomechanical motion
Invited lecture, GAMM Annual Meeting (Kassel, 2021-03-15 - 2021-03-19)
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2020
Optimal Control of Grasping Problem Using Postural Synergies
6th International Digital Human Modeling Symposium (Skövde, 2020-08-31 - 2020-09-02)
In: Proceedings of the 6th International Digital Human Modeling Symposium 2020
DOI: 10.3233/ATDE200026
URL: http://ebooks.iospress.nl/volume/dhm2020-proceedings-of-the-6th-international-digital-human-modeling-symposium
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2019
Optimal control simulations of two-finger precision grasps
ECCOMAS Thematic Conference on Mutlibody Dynamics (Duisburg, 2019-07-15 - 2019-07-18)
In: Proceedings of the ECCOMAS Thematic Conference on Mutlibody Dynamics 2019
DOI: 10.1007/978-3-030-23132-3_8
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On grasp based objectives in human grasping simulation
GAMM Annual Meeting (Vienna, 2019-02-18 - 2019-02-22)
In: Proc. Appl. Math. Mech. (PAMM) 2019
DOI: 10.1002/pamm.201900226
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2018
Optimal control simulations of tip pinch and lateral pinch grasping
European Consortium for Mathematics in Industry (ECMI) Conference (Budapest, 2018-06-18 - 2018-06-22)
In: Mathematics in Industry 2018
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Optimal control simulations of two finger grasping
GAMM Annual Meeting (Munich, 2018-03-19 - 2018-03-23)
In: Proc. Appl. Math. Mech (PAMM) 2018
DOI: 10.1002/pamm.201800358
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2017
Investigating human thumb models via their range of motion volumes
GAMM Annual Meeting (Weimar, 2017-03-06 - 2017-03-10)
In: Proc. Appl. Math. Mech (PAMM) 2017
DOI: 10.1002/pamm.201710077
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Kinematic validation of a human thumb model
ECCOMAS Thematic Conference on Multibody Dynamics (Prague, 2017-06-19 - 2017-06-22)
In: Proceedings of the ECCOMAS Thematic Conference on Mutlibody Dynamics 2017
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further publications
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Optimal control of biomechanical MBS-Digital Human Models for simulation in the virtual assembly planning
(Third Party Funds Single)
Term: 2015-11-01 - 2018-03-31
Funding source: Industrie
URL: https://www.emma-cc.com/de/teilprojekte-partner/biomechanik-optimalsteuerung.htmlThe goal of this project is to apply techniques of biomechanics and optimal control to generate realistic human-like motions of the DHM from generic working instructions like for example move a box from A to B. Such a model would enable the engineers to take into account physical workloads and reachability issues in virtual assembly planning.
The digital human is modeled as a biomechanical multibody system with muscles as actuators. The motions of the DHM for specific working instructions are predicted with the help of optimal control, where an objective function accounting for physiological quantities that are relevant for humans is minimized. This new approach enables the user to make quantitative statements about muscle forces and joint loads during assembly, which are important indicators for ergonomic assessment.