Search Results - "Héliot, Rodolphe"

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  1. 1

    A Magnetometer-Based Approach for Studying Human Movements by Bonnet, Stephane, Heliot, Rodolphe

    “…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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    Journal Article
  2. 2

    System Architecture for Stiffness Control in Brain-Machine Interfaces by Heliot, Rodolphe, Orsborn, Amy L., Ganguly, Karunesh, Carmena, Jose M.

    “…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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    Journal Article
  3. 3

    Learning in Closed-Loop Brain-Machine Interfaces: Modeling and Experimental Validation by Héliot, R, Ganguly, K, Jimenez, J, Carmena, J M

    “…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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    Journal Article
  4. 4

    Gait Spectral index (GSI): a new quantification method for assessing human gait by Héliot, Rodolphe, Azevedo Coste, Christine, Schwirtlich, Laszlo, Espiau, Bernard

    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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    Journal Article
  5. 5

    A model of motor learning in closed-loop brain-machine interfaces: Predicting neural tuning changes by Heliot, R., Carmena, J.M.

    “…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. 6

    Decentralized optimization of energy exchanges in an electricity microgrid by Vinot, Benoit, Cadoux, Florent, Heliot, Rodolphe

    “…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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    Conference Proceeding
  7. 7

    Low-power hardware for neural spike compression in BMIs by Lapolli, Angelo C., Coppa, Bertrand, Heliot, Rodolphe

    “…Within brain-machine interface systems, cortically implanted microelectrode arrays and associated hardware have a low-power budget for data sampling,…”
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    Conference Proceeding Journal Article
  8. 8

    Low-cost intracortical spiking recordings compression with classification abilities for implanted BMI devices by Coppa, B., Heliot, R., Michel, O., Moisan, E., David, D.

    “…Within Brain-Machine Interface systems, cortically implanted microelectrode arrays and associated hardware have a low power budget for data sampling,…”
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    Conference Proceeding Journal Article
  9. 9

    Classification from compressive representations of data by Coppa, B., Heliot, R., David, D., Michel, O.

    “…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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    Conference Proceeding
  10. 10

    Online generation of cyclic leg trajectories synchronized with sensor measurement by Héliot, R., Espiau, B.

    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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    Journal Article
  11. 11

    Multisensor Input for CPG-Based Sensory---Motor Coordination by Heliot, R., Espiau, B.

    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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    Journal Article
  12. 12

    Stiffness control of 2-DOF exoskeleton for brain-machine interfaces by Heliot, R., Orsborn, A., Carmena, J.M.

    “…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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    Conference Proceeding
  13. 13

    Capacitance of TSVs in 3-D stacked chips a problem?: not for neuromorphic systems by Joubert, Antoine, Duranton, Marc, Belhadj, Bilel, Temam, Olivier, Héliot, Rodolphe

    “…In order to cope with increasingly stringent power and variability constraints, architects need to investigate alternative paradigms. Neuromorphic…”
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    Conference Proceeding
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    A robust and compact 65 nm LIF analog neuron for computational purposes by Joubert, A., Belhadj, B., Heliot, R.

    “…Due to upcoming power and robustness issues related to decananometer silicon technologies, neuromorphic architectures are increasingly meaningful to perform…”
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    Conference Proceeding
  17. 17

    Implementation of signal processing tasks on neuromorphic hardware by Temam, O., Heliot, R.

    “…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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    Conference Proceeding
  18. 18

    Capacitance of TSVs in 3-D stacked chips a problem? Not for neuromorphic systems by Joubert, A., Duranton, M., Belhadj, B., Temam, O., Heliot, R.

    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. 19

    Online adaptation of optimal control of externally controlled walking of a hemiplegic individual by Heliot, R., Dosen, S., Azevedo, C., Espiau, B., Popovic, D.B.

    “…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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    Conference Proceeding
  20. 20

    Adaptive Kalman filtering for closed-loop Brain-Machine Interface systems by Dangi, S., Gowda, S., Heliot, R., Carmena, J. M.

    “…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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    Conference Proceeding