CRCNS: Computation-Enabled Adaptive Ventilatory Control System Grant

CRCNS: Computation-Enabled Adaptive Ventilatory Control System .


  • Approximately 270,000 Americans and 20,000 French are survivors of traumatic spinal cord injury (SCI), with 12,000 Americans and 1200 to 2000 French surviving new injuries each year. The cervical cord is the most common site of injury (54%) and people with cervical SCI can have partial or complete loss of ventilatory control. Most people with SCI that require ventilation management are initially supported with positive pressure-mechanical ventilation, which is associated with significant discomfort, diaphragm atrophy, atelectasis and barotrauma and can lead to respiratory diseases and prevent optimal recovery. Alternatively, ventilation can be achieved by diaphragmatic pacing by electrical phrenic nerve stimulation. More recently, intramuscular stimulation of multiple respiratory muscles has been proposed as a viable less surgically invasive approach, in particular for people with insufficient ventilation by diaphragmatic pacing alone. The open-loop stimulation strategy currently utilized for pacing has major limitations including the need for manual stimulation parameter tuning, and inability to alter stimulation parameters on muscle fatigue or changing metabolic demand. The intellectual merit of this proposal lies in the design, development and prototype realization of a novel closed-loop control system that utilizes the computational power of spike-based neuromorphic hardware to adaptively control dynamic processes in biological systems. It will specifically address the challenge of simultaneously adapting the rhythm and pattern of oscillatory drive to achieve effective and efficient control of complex biological functions. The work will focus on the specific problem of controlling ventilation in individuals with high-level SCI by electrically stimulating the motoneurons that drive respiratory musculature. This problem is particularly well-suited to assess our approach because it presents the challenge of delivering a pattern of stimuli to a set of actuators at very short timescales (spike frequencies) to drive coordinated actions that determine physiological outcomes that can only be assessed on a much longer timescale (breathing frequency). Development of the proposed computation-enabled adaptive ventilatory control system (CENAVEX) will benefit from the prior experience of the US (Jung) and French (Renaud) Co-PIs and their research teams. The US team has extensive research experience in implementation of a Pattern Generator/Pattern Shaper adaptive control strategy with on-line learning for computer control of functional electrical stimulation of limb movement after incomplete or complete paraplegia in people and rodents. The French team has extensive research experience in development of analog and mixed neuromorphic VLSI and real-time hardware simulation platforms of spiking neural networks on hybrid systems interfacing living and artificial neurons. To accomplish our objectives we will develop a lung-respiratory muscles computational model and test the abilities of the CENAVEX system, implement the control scheme in software for real-time computer-based control of ventilation in anesthetized intact rodents and those with chronic cervical incomplete SCI, and implement the scheme in neuromorphic hardware with spiking networks, synaptic learning and bio-interface hardware for standalone system assessment in rodents. The broader impact of this project lies in the production of strategies and neuromorphic designs that could be useful in a number of problems in which oscillatory rhythm and pattern across a set of actuators need to be coordinated on short timescales to control complex processes with dynamics over much longer timescales. Successful completion of the proposed project will pave the path for translation to an innovative respiratory pacing system capable of allowing adequate ventilation in people with SCI with impaired respiratory control, taking into account non-linear properties of muscle activation, muscle fatigue, and metabolic demand of the individual. It will also offer ease of deployment for the clinician and caregiver. By providing long duration respiratory exercise, the system could act as a rehabilitative tool in people with incomplete SCI improving the quality of life for the user. The multidisciplinary research effort will bridge disciplines and international institutions through international exchange of personnel and ideas. Florida International University, a minority and Hispanic serving institution, will provide access to a diverse student body and the project will directly support the training of a female postdoc, young investigator, graduate and undergraduate students. The training component will build transdisciplinary expertise in neuroscience, biomechanics, rehabilitation, neuromorphic engineering and neural control systems and will provide trainees with the skills to use computational neuroscience approaches to address complex challenges faced in developing embedded neuromorphic technology.

date/time interval

  • September 30, 2013 - August 31, 2017

administered by

sponsor award ID

  • 1R01NS086088-01

local award ID

  • AWD000000002915



  • Abdominal Muscles
  • Accounting
  • Acute
  • Address
  • Algorithms
  • American
  • Animals
  • Atelectasis
  • Atrophic
  • Biological Neural Networks
  • Biological Process
  • Biomechanics
  • Breathing
  • Carbon Dioxide
  • Caregivers
  • Cervical
  • Cervical spinal cord injury
  • analog
  • base
  • biological systems