Overall Objectives
Scientific Foundations
Application Domains
New Results

Section: Software


RdP to VHDL tool

Participants : David Andreu, Grégory Angles.

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). We started, through an INRIA ODL (Opération de Développement Logiciel), the development of an Eclipse-based version of HILECOP with the aim at making it accessible to the academic community.


Participants : David Andreu, Grégory Angles, Robin Passama.

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 also allows the manipulation of micro-programs from their edition to their remote control (Fig. 1 ; right).

Figure 1. Left) Example of SENIS Architecture managed through SENIS Manager. Right) Some windows available on SENISManager: (a) FES architecture management, (b) graphical editing of micro-programs, (c) console for remote control of the execution of micro-programs of which parameter values are displayed in real-time (d).


Participants : David Andreu, Robin Passama.

We designed and partially developed a software environment allowing the management and control of a heterogeneous technology based external FES architecture. This software environment eases the configuration and exploitation of the external FES platform since it ensures the interoperability of the heterogeneous entities implied within the platform. It is based on a middleware and a set of modules organized according to two-layer software architecture: the interaction layer and the control layer. The interaction layer directly pilots stimulators and sensors used in the platform, ensuring the communication with these entities according to their specific protocol-stacks. Its middleware contains a scheduler in charge of the scheduling, the activation and the monitoring of the corresponding modules. The control layer supports the development of control strategies, potentially based on a set of heterogeneous entities (stimulators and sensors), like closed-loop controllers and/or supervisory controllers. This software is already tested with stimulators used on patient under ethical comitee approval.

Figure 2. Schematic description of the software environment allowing the deployment of control strategies based on heterogeneous entities

A graphical interface will allow the end-user to manipulate the FES architecture (software entities and their associated hardware), at greater abstraction level.


Participants : Jérémy Laforêt, David Guiraud.

The software tool chain we set up to simulate the electrode-nerve interface is efficient but complex to use. It involves two different software (OpenMEEG and Neuron) and three ways of interaction: command line, Python scripts, and editing makefiles. To enable the use of this tool-chain by non specialist we designed a graphical interface managing the simulations. It is based only on free software technologies : Python, gtk and glade. It enables the user to define the model parameters and run the simulations. It takes into account the intermediate steps and thus can resume previous simulations or use part of them as basis for new ones.

Planning and Fast Re-Planning of safe motions

Participants : Sébastien Lengagne, Philippe Fraisse, Nacim Ramdani.

This algorithm allowing to generate optimal safe motion in term of balance is based on interval analysis. It can be downloaded at: .


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