RdP to VHDL tool

Participants : David Andreu, Thierry Gil, Robin Passama, Baptiste Colombani, Thibaut Possompes.

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 units 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 Eclipse-based version of HILECOP (registered at the french Agence de Protection des Programmes (APP)) is regulary updated.

Undergoing work concerns the integration, in the HILECOP tool, of the formalism evolutions that allow behavior agregation as well as exception handling, both for analysis and implementation sides (H. Leroux PhD thesis).

Specification of GALS systems (Globally Asynchronous Locally Synchronous) is also an ongoing work, the aim being to take into account deployment properties like connecting different clocks to HILECOP components within a same FPGA, or on a set of interconnected FPGAs (and thus interconnecting them by means of asynchronous signals).

SENISManager

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. This environment allows the manipulation of micro-programs from their edition to their remote control. It also allows the programming of control sequences executed by an external controller in charge of automatically piloting a stimulator.

SENISManager (registered at the french Agence de Protection des Programmes (APP) with the industrial partner) has been transferred to the industrial partner that develops a new version according to an Eclipse-based design.

Synergy Neurostimulation Software

Participants : David Andreu, Amandine Pantel, Arthur Hiairrassary.

We are developing a specific software environment called Synergy Neurostimulation Software allowing to remotely manage a stimulation architecture based on one controller piloting a set of distributed stimulation units, connected by means of a dedicated network. The controller embeds the set of FES functions according to which it controls stimulation units, in real-time.

This FES distributed architecture is based on our last version of stimulation units that embed stimulation sequencing and a more efficient modulation mechanism.

Synergy Neurostimulation Software will be soon registered at the french Agence de Protection des Programmes (APP).

MOS2SENS: Model Optimization and Simulation To Selective Electrical Neural Stimulation

Participants : Melissa Dali, Olivier Rossel, David Guiraud.

SENSBIOTK

As low cost and highly portable sensors, inertial measurements units (IMU) have become increasingly used in different topics, such as gait analysis, embodying an efficient alternative to motion capture systems. Meanwhile, being able to compute reliably accurate spatial parameters using few sensors remains a relatively complex problematic. The use of inertial data calls on various algorithms able to compute from raw sensors (accelerometer, magnetometer and gyrometer) different features (position, angle, etc...). SensbioTK (for Tool Kit) has been implemented using a Python programming environment. This opensource library provides to any IMU user a set of tools enabling the following functions :