Section: Software


FES muscle modeling in opensim framework

Participants : Mitsuhiro Hayashibe, Philippe Fraisse, Emel Demircan, Oussama Khatib (INRIA Equipe Associee, Stanford Univ.).

In FES, movement synthesis and control are still challenging tasks due to the complexity of whole body dynamics computation and the nonlinearity of stimulated muscle dynamics. An efficient movement synthesis means that criteria can be defined and evaluated through an accurate numeric simulation. We perform the implementation of muscle model representing the electrically stimulated muscle into the OpenSim framework which has whole body musculoskeletal geometry. We would like to develop the FES simulator using Stanford Operational Space Whole-Body Controller which allows the real-time motion generation with virtual FES and finally we aim at the development of motion correction controller to find the appropriate FES signals against a disabled motor function.

Further development of gom2n software - a toolchain to simulate and investigate selective stimulation strategies for FES

Participants : Guillaume Jourdain, Pawel Maciejasz, Jeremy Laforet, Christine Azevedo Coste, David Guiraud.

Concurrently with the experiments on selective stimulation of nerve fibres, performed on earthworms (see section 6.1.6 ), also the gom2n toolchain developed previously by our team was further developed. Main objective of this work was to be able to simulate similar behaviour of nerve fibres, as observed during electrical stimulation of the giant nerve fibres of earthworms, and therefore to be able to compare computational and experimental results. Main improvements which has been implemented in the new version of the gom2n toolchain are:

  • improved and more intuitive users interface

  • possibility to perform concurrently multiple simulations for various stimulation parameters, as well as various diameters and locations of nerve fibres within the nerve.

Further work is however still needed to adapt electrical properties of simulated fibres, since electrical properties of the earthworm's giant nerve fibres are different that properties of mammalian nerve fibres."

RdP to VHDL tool

Participants : Gregory Angles, David Andreu, Thierry Gil.

Our SENIS (Stimulation Electrique Neurale dIStribuee) based FES architecture relies on distributed stimulation units (DSU) which are interconnected by means of a 2-wire based network. A DSU is a complex digital system since its embeds among others a dedicated processor (micro-machine with a specific reduced instruction set), a monitoring module and a 3-layer protocol stack. To face the complexity of the unit’s digital part and to ease its prototyping on programmable digital devices (e.g. FPGA), we developed an approach for high level hardware component programming (HILECOP). To support the modularity and the reusability of sub-parts of complex hardware systems, the HILECOP methodology is based on components. An HILECOP component has: a Petri Net (PN) based behavior, a set of functions whose execution is controlled by the PN, and a set of variables and signals. Its interface contains places and transitions from which its PN model can be inter-connected as well as signals it exports or imports. The interconnection of those components, from a behavioral point out view, consists in the interconnection of places and/or transitions according to well-defined mechanisms: interconnection by means of oriented arcs or by means of the "merging" operator (existing for both places and transitions).

The development of an Eclipse-based version of HILECOP has been achieved. This new version of HILECOP has been registered (new deposit) in september 2011, at the french Agence de Protection des Programmes (APP) with the IDDN.FR.001.380008.000.S.P.2011.000.31235.

It will be accessible to the academic community at the beginning of 2012.


Participants : Robin Passama, David Andreu.

We developed a specific software environment called SENISManager allowing to remotely manage and control a network of DSUs, i.e. the distributed FES architecture. SENISManager performs self-detection of the architecture being deployed (Fig. 1; left). This environment allows the manipulation of micro-programs from their edition to their remote control (Fig. 1; right). It also allows the programming of control sequences executed by an external controller in charge of automatically piloting a stimulator.

This new version of SENIS Manager has been registered (updated deposit) in september 2011, at the french Agence de Protection des Programmes (APP), with the IDDN.FR.001.320011.001.S.P.2009.000.31500