Bio-inspired controller on an fpga applied to closed-loop diaphragmatic stimulation

Adeline Zbrzeski, Yannick Bornat, Brian Hillen, Ricardo Siu, James Abbas, Ranu Jung, Sylvie Renaud

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Cervical spinal cord injury can disrupt connections between the brain respiratory network and the respiratory muscles which can lead to partial or complete loss of ventilatory control and require ventilatory assistance. Unlike current open-loop technology, a closed-loop diaphragmatic pacing system could overcome the drawbacks of manual titration as well as respond to changing ventilation requirements. We present an original bio-inspired assistive technology for real-time ventilation assistance, implemented in a digital configurable Field Programmable Gate Array (FPGA). The bio-inspired controller, which is a spiking neural network (SNN) inspired by the medullary respiratory network, is as robust as a classic controller while having a flexible, low-power and low-cost hardware design. The system was simulated in MATLAB with FPGA-specific constraints and tested with a computational model of rat breathing; the model reproduced experimentally collected respiratory data in eupneic animals. The open-loop version of the bio-inspired controller was implemented on the FPGA. Electrical test bench characterizations confirmed the system functionality. Open and closed-loop paradigm simulations were simulated to test the FPGA system real-time behavior using the rat computational model. The closed-loop system monitors breathing and changes in respiratory demands to drive diaphragmatic stimulation. The simulated results inform future acute animal experiments and constitute the first step toward the development of a neuromorphic, adaptive, compact, low-power, implantable device. The bio-inspired hardware design optimizes the FPGA resource and time costs while harnessing the computational power of spike-based neuromorphic hardware. Its real-time feature makes it suitable for in vivo applications.

Original languageEnglish (US)
Article number275
JournalFrontiers in Neuroscience
Issue numberJUN
StatePublished - Jun 16 2016


  • Assisted ventilation
  • Bio-inspired controller
  • Closed-loop paradigm
  • Field programmable gate array (FPGA)
  • Metabolic demands
  • Spiking neural network (SNN)
  • Spinal-cord injury (SCI)
  • Ventilatory control system

ASJC Scopus subject areas

  • Neuroscience(all)


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