Search Results - "Héliot, Rodolphe"
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A Magnetometer-Based Approach for Studying Human Movements
Published in IEEE transactions on biomedical engineering (01-07-2007)“…This paper investigates the use of body-mounted magnetic field sensors for the analysis of certain human movements. We demonstrate that, in several usual…”
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System Architecture for Stiffness Control in Brain-Machine Interfaces
Published in IEEE transactions on systems, man and cybernetics. Part A, Systems and humans (01-07-2010)“…Brain-machine interfaces (BMIs) provide a versatile tool for rehabilitation of severely disabled people. Current BMI systems focus on the control of kinematic…”
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3
Learning in Closed-Loop Brain-Machine Interfaces: Modeling and Experimental Validation
Published in IEEE transactions on systems, man and cybernetics. Part B, Cybernetics (01-10-2010)“…Closed-loop operation of a brain-machine interface (BMI) relies on the subject's ability to learn an inverse transformation of the plant to be controlled. In…”
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4
Gait Spectral index (GSI): a new quantification method for assessing human gait
Published in Health (London, England : 1997) (01-01-2010)“…This paper introduces a simple, quantitative assessment tool to follow up the recovery of gait. Today, micro-electro-mechanical systems (MEMS) technology…”
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A model of motor learning in closed-loop brain-machine interfaces: Predicting neural tuning changes
Published in 2009 IEEE International Conference on Systems, Man and Cybernetics (01-10-2009)“…This paper presents a model of the learning process occurring during operation of a closed-loop brain-machine interface (BMI). The learning model updates…”
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Conference Proceeding -
6
Decentralized optimization of energy exchanges in an electricity microgrid
Published in 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) (01-10-2016)“…We propose to control a local electricity grid, a "microgrid", in a decentralized fashion to reduce energy costs by coordinating the generation and consumption…”
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Low-power hardware for neural spike compression in BMIs
Published in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (01-01-2013)“…Within brain-machine interface systems, cortically implanted microelectrode arrays and associated hardware have a low-power budget for data sampling,…”
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Low-cost intracortical spiking recordings compression with classification abilities for implanted BMI devices
Published in 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (01-01-2012)“…Within Brain-Machine Interface systems, cortically implanted microelectrode arrays and associated hardware have a low power budget for data sampling,…”
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Classification from compressive representations of data
Published in 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO) (01-08-2012)“…Compressive sensing proposes simple compression of sparse data at the expense of difficult data reconstruction. We focus here on the opportunities in terms of…”
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10
Online generation of cyclic leg trajectories synchronized with sensor measurement
Published in Robotics and autonomous systems (31-05-2008)“…The generation of trajectories for a biped robot is a problem which has been largely studied for several years, and many satisfying offline solutions exist for…”
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Multisensor Input for CPG-Based Sensory---Motor Coordination
Published in IEEE transactions on robotics (01-02-2008)“…This paper describes a method for providing in real time a reliable synchronization signal for cyclical motions such as steady-state walking. The approach…”
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12
Stiffness control of 2-DOF exoskeleton for brain-machine interfaces
Published in 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (01-10-2008)“…Previous demonstrations of brain-machine interfaces have shown the potential for controlling a neuroprosthesis under pure motion control, i.e. predicting end…”
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13
Capacitance of TSVs in 3-D stacked chips a problem?: not for neuromorphic systems
Published in Proceedings of the 49th Annual Design Automation Conference (03-06-2012)“…In order to cope with increasingly stringent power and variability constraints, architects need to investigate alternative paradigms. Neuromorphic…”
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Sensing Valid Limb Attitude to Improve Deficient Limb Artificial Control
Published in Gait & posture (2005)Get full text
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15
Solving dynamical systems in neuromorphic hardware: simulation studies using balanced spiking networks
Published in BMC neuroscience (08-07-2013)“…Doc number: P382…”
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A robust and compact 65 nm LIF analog neuron for computational purposes
Published in 2011 IEEE 9th International New Circuits and systems conference (01-06-2011)“…Due to upcoming power and robustness issues related to decananometer silicon technologies, neuromorphic architectures are increasingly meaningful to perform…”
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Implementation of signal processing tasks on neuromorphic hardware
Published in The 2011 International Joint Conference on Neural Networks (01-07-2011)“…Because of power and reliability issues, computer architects are forced to explore new types of architectures, such as heterogeneous systems embedding hardware…”
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Capacitance of TSVs in 3-D stacked chips a problem? Not for neuromorphic systems
Published in DAC Design Automation Conference 2012 (01-06-2012)“…In order to cope with increasingly stringent power and variability constraints, architects need to investigate alternative paradigms. Neuromorphic…”
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Conference Proceeding -
19
Online adaptation of optimal control of externally controlled walking of a hemiplegic individual
Published in 2007 3rd International IEEE/EMBS Conference on Neural Engineering (01-05-2007)“…Bipedal walking is a quasi-cyclic activity where the movements of the ipsilateral leg and contralateral leg are time shifted for 50 percent of the gait cycle…”
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20
Adaptive Kalman filtering for closed-loop Brain-Machine Interface systems
Published in 2011 5th International IEEE/EMBS Conference on Neural Engineering (01-04-2011)“…Brain-Machine Interface (BMI) decoding algorithms are often trained offline, but this paradigm ignores both the non-stationarity of neural signals and the…”
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