Overview
INRIA is the French national institute for research in computer science and control. The Institute's strategy closely combines scientific excellence and technology transfer. INRIA's seven priority domains are: (i) Modeling, simulation and optimization of complex dynamic systems, (ii) Programming: security and reliability of computing systems, (iii) Communication, information, and ubiquitous computing, (iv) Interaction with real and virtual worlds, (v) Computational engineering, (vi) Computational sciences, and (vii) Computational medicine.
DEMAR project's research interests are centered on the human sensory motor modeling, including muscles, sensory feedbacks, and neural motor networks. Final goal of this team is oriented towards the development of advanced neuroprotheses to restore deficient functions.
Descriptif du poste
Identification of biomechanical dynamics and muscle dynamics for neurologically damaged patient is already challenging as the system response can drastically vary depending on the degree of the patient deficiencies. The extracted information with System Identification technique is finally to be used for the understanding of motor control function in such patient and for motion synthesis and control using FES (Functional Electrical Stimulation). However, In FES, movement synthesis and control are still a challenging task due to the complexity of whole body dynamics computation and the nonlinearity of stimulated muscle dynamics. For the motion synthesis, recently some optimization technique started to be applied in whole body simulation platform where the desired criteria can be defined and evaluated through an accurate numeric simulation such as OpenSim software of Stanford Univ. For the control, one of the challenge concerns the feedback (torque, EMG, joint angle) that can be used to control joint angle, torque or stiffness. Moreover, control strategies have to be designed in order to be performed on portable architecture and tuned through advanced modeling and simulation.
Disadvantage of numerical optimization is its high computation cost. Real-time performance cannot be expected, then in order to obtain stimulation patterns for a given movement corresponding to current patient posture condition, both off-line optimization for movement synthesis and online closed control are needed. In this context, the goal of this PhD work is to study the optimization-based motion synthesis and real-time control framework which can generate stimulation patterns from the pre-computed motion synthesis database. Motion capture system together with the estimation of the Center of Mass would be used to assess the strategies. This work aims at the development of automatic method to establish deficient limb stability in computer-aided rehabilitation.
This PhD work is performed under the collaborative project named @walk (artificial walking) between INRIA DEMAR project and AI lab of Stanford University. http://www.lirmm.fr/~fraisse/@WALK/
Experimental protocols will be carried out with our clinical partners.
[1] M. Hayashibe, Q. Zhang, D. Guiraud, C. Fattal, P. Fraisse. Modeling and Experimental Identification for Muscular force Estimation Based on Evoked EMG in FES. Abstracts of the International Conference on Orthopaedic Biomechanics, Clinical Applications and Surgery (OBCAS). Journal of Biomechanics 43, Supp. 1, June 2010, pp. S66.
[2] Q. Zhang, M. Hayashibe, M. Papaiordanidou, P. Fraisse, C. Fattal and D. Guiraud. Torque Prediction Using Stimulus Evoked EMG and its Identification for Different Muscle Fatigue States in SCI Subjects. IEEE Engineering in Medicine and Biology Society EMBC 2010.
[3] M. Eckert, M. Hayashibe, D. Guiraud, P.B. Wieber, P. Fraisse, "Simulating the Human Motion under Functional Electrical Stimulation using the HuMAnS Toolbox", Recent Advances in the 3D Physiological Human, pp.121-131, 2009.
[4] S.Cotton, A.Murray, P.Fraisse, "Estimation of the Center of Mass: From Humanoid Robots to Human Beings" ,IEEE/ASME Transactions on Mechatronics, Vol 14, No 6, December 2009, pp707-712.
Profil recherché
Master in control engineering, computer science, biomechanics, robotics or related disciplines.
- good knowledge of C/C++ programming and matlab.
Avantages
the net salary is 1597 euros and includes social security.
This salary does not include possible additionnal activities.
Informations complémentaires
Durée du contrat : 36 mois
- Duration: 3 years
- Starting date: between Sept. 1st 2011 and Jan. 1st 2012
Lieu de travail :
LIRMM (Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier)
http://www.lirmm.fr/xml/en/0001-01.html
Montpellier, France
Personne a contacter dans l'EPI (émail) :
Mitsuhiro Hayashibe, Philippe Fraisse
Mitsuhiro.Hayashibe@inria.fr
page Web EPI:
http://www.lirmm.fr/~fraisse/@WALK/
http://www.lirmm.fr/demar/
Please quote Scholarization.blogspot.com on your application when applying for this scholarship
INRIA is the French national institute for research in computer science and control. The Institute's strategy closely combines scientific excellence and technology transfer. INRIA's seven priority domains are: (i) Modeling, simulation and optimization of complex dynamic systems, (ii) Programming: security and reliability of computing systems, (iii) Communication, information, and ubiquitous computing, (iv) Interaction with real and virtual worlds, (v) Computational engineering, (vi) Computational sciences, and (vii) Computational medicine.
DEMAR project's research interests are centered on the human sensory motor modeling, including muscles, sensory feedbacks, and neural motor networks. Final goal of this team is oriented towards the development of advanced neuroprotheses to restore deficient functions.
Descriptif du poste
Identification of biomechanical dynamics and muscle dynamics for neurologically damaged patient is already challenging as the system response can drastically vary depending on the degree of the patient deficiencies. The extracted information with System Identification technique is finally to be used for the understanding of motor control function in such patient and for motion synthesis and control using FES (Functional Electrical Stimulation). However, In FES, movement synthesis and control are still a challenging task due to the complexity of whole body dynamics computation and the nonlinearity of stimulated muscle dynamics. For the motion synthesis, recently some optimization technique started to be applied in whole body simulation platform where the desired criteria can be defined and evaluated through an accurate numeric simulation such as OpenSim software of Stanford Univ. For the control, one of the challenge concerns the feedback (torque, EMG, joint angle) that can be used to control joint angle, torque or stiffness. Moreover, control strategies have to be designed in order to be performed on portable architecture and tuned through advanced modeling and simulation.
Disadvantage of numerical optimization is its high computation cost. Real-time performance cannot be expected, then in order to obtain stimulation patterns for a given movement corresponding to current patient posture condition, both off-line optimization for movement synthesis and online closed control are needed. In this context, the goal of this PhD work is to study the optimization-based motion synthesis and real-time control framework which can generate stimulation patterns from the pre-computed motion synthesis database. Motion capture system together with the estimation of the Center of Mass would be used to assess the strategies. This work aims at the development of automatic method to establish deficient limb stability in computer-aided rehabilitation.
This PhD work is performed under the collaborative project named @walk (artificial walking) between INRIA DEMAR project and AI lab of Stanford University. http://www.lirmm.fr/~fraisse/@WALK/
Experimental protocols will be carried out with our clinical partners.
[1] M. Hayashibe, Q. Zhang, D. Guiraud, C. Fattal, P. Fraisse. Modeling and Experimental Identification for Muscular force Estimation Based on Evoked EMG in FES. Abstracts of the International Conference on Orthopaedic Biomechanics, Clinical Applications and Surgery (OBCAS). Journal of Biomechanics 43, Supp. 1, June 2010, pp. S66.
[2] Q. Zhang, M. Hayashibe, M. Papaiordanidou, P. Fraisse, C. Fattal and D. Guiraud. Torque Prediction Using Stimulus Evoked EMG and its Identification for Different Muscle Fatigue States in SCI Subjects. IEEE Engineering in Medicine and Biology Society EMBC 2010.
[3] M. Eckert, M. Hayashibe, D. Guiraud, P.B. Wieber, P. Fraisse, "Simulating the Human Motion under Functional Electrical Stimulation using the HuMAnS Toolbox", Recent Advances in the 3D Physiological Human, pp.121-131, 2009.
[4] S.Cotton, A.Murray, P.Fraisse, "Estimation of the Center of Mass: From Humanoid Robots to Human Beings" ,IEEE/ASME Transactions on Mechatronics, Vol 14, No 6, December 2009, pp707-712.
Profil recherché
Master in control engineering, computer science, biomechanics, robotics or related disciplines.
- good knowledge of C/C++ programming and matlab.
Avantages
the net salary is 1597 euros and includes social security.
This salary does not include possible additionnal activities.
Informations complémentaires
Durée du contrat : 36 mois
- Duration: 3 years
- Starting date: between Sept. 1st 2011 and Jan. 1st 2012
Lieu de travail :
LIRMM (Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier)
http://www.lirmm.fr/xml/en/0001-01.html
Montpellier, France
Personne a contacter dans l'EPI (émail) :
Mitsuhiro Hayashibe, Philippe Fraisse
Mitsuhiro.Hayashibe@inria.fr
page Web EPI:
http://www.lirmm.fr/~fraisse/@WALK/
http://www.lirmm.fr/demar/
Please quote Scholarization.blogspot.com on your application when applying for this scholarship
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