PMID- 27378844
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20160706
LR  - 20201001
IS  - 1662-4548 (Print)
IS  - 1662-453X (Electronic)
IS  - 1662-453X (Linking)
VI  - 10
DP  - 2016
TI  - Bio-Inspired Controller on an FPGA Applied to Closed-Loop Diaphragmatic 
      Stimulation.
PG  - 275
LID - 10.3389/fnins.2016.00275 [doi]
LID - 275
AB  - 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.
FAU - Zbrzeski, Adeline
AU  - Zbrzeski A
AD  - Bordeaux INP, IMS, UMR 5218Talence, France; Univ. Bordeaux, IMS, UMR 5218Talence, 
      France.
FAU - Bornat, Yannick
AU  - Bornat Y
AD  - Bordeaux INP, IMS, UMR 5218Talence, France; Univ. Bordeaux, IMS, UMR 5218Talence, 
      France.
FAU - Hillen, Brian
AU  - Hillen B
AD  - Department of Biomedical Engineering, Florida International University Miami, FL, 
      USA.
FAU - Siu, Ricardo
AU  - Siu R
AD  - Department of Biomedical Engineering, Florida International University Miami, FL, 
      USA.
FAU - Abbas, James
AU  - Abbas J
AD  - School of Biological and Health Systems Engineering, Arizona State University 
      Tempe, AZ, USA.
FAU - Jung, Ranu
AU  - Jung R
AD  - Department of Biomedical Engineering, Florida International University Miami, FL, 
      USA.
FAU - Renaud, Sylvie
AU  - Renaud S
AD  - Bordeaux INP, IMS, UMR 5218Talence, France; Univ. Bordeaux, IMS, UMR 5218Talence, 
      France.
LA  - eng
GR  - R01 NS086088/NS/NINDS NIH HHS/United States
PT  - Journal Article
DEP - 20160616
PL  - Switzerland
TA  - Front Neurosci
JT  - Frontiers in neuroscience
JID - 101478481
PMC - PMC4909776
OTO - NOTNLM
OT  - assisted ventilation
OT  - bio-inspired controller
OT  - closed-loop paradigm
OT  - field programmable gate array (FPGA)
OT  - metabolic demands
OT  - spiking neural network (SNN)
OT  - spinal-cord injury (SCI)
OT  - ventilatory control system
EDAT- 2016/07/06 06:00
MHDA- 2016/07/06 06:01
PMCR- 2016/01/01
CRDT- 2016/07/06 06:00
PHST- 2016/02/03 00:00 [received]
PHST- 2016/06/01 00:00 [accepted]
PHST- 2016/07/06 06:00 [entrez]
PHST- 2016/07/06 06:00 [pubmed]
PHST- 2016/07/06 06:01 [medline]
PHST- 2016/01/01 00:00 [pmc-release]
AID - 10.3389/fnins.2016.00275 [doi]
PST - epublish
SO  - Front Neurosci. 2016 Jun 16;10:275. doi: 10.3389/fnins.2016.00275. eCollection 
      2016.