Literature DB >> 31146654

Restoring Ventilatory Control Using an Adaptive Bioelectronic System.

Ricardo Siu1, James J Abbas2, Brian K Hillen1, Jefferson Gomes1, Stefany Coxe3, Jonathan Castelli4, Sylvie Renaud4, Ranu Jung1.   

Abstract

Ventilatory pacing by electrical stimulation of the phrenic nerve or of the diaphragm has been shown to enhance quality of life compared to mechanical ventilation. However, commercially available ventilatory pacing devices require initial manual specification of stimulation parameters and frequent adjustment to achieve and maintain suitable ventilation over long periods of time. Here, we have developed an adaptive, closed-loop, neuromorphic, pattern-shaping controller capable of automatically determining a suitable stimulation pattern and adapting it to maintain a desired breath-volume profile on a breath-by-breath basis. The system adapts the pattern of stimulation parameters based on the error between the measured volume sampled every 40 ms and a desired breath volume profile. In vivo studies in anesthetized male Sprague-Dawley rats without and with spinal cord injury by spinal hemisection at C2 indicated that the controller was capable of automatically adapting stimulation parameters to attain a desired volume profile. Despite diaphragm hemiparesis, the controller was able to achieve a desired volume in the injured animals that did not differ from the tidal volume observed before injury (p = 0.39). Closed-loop adaptive pacing partially mitigated hypoventilation as indicated by reduction of end-tidal CO2 values during pacing. The closed-loop controller was developed and parametrized in a computational testbed before in vivo assessment. This bioelectronic technology could serve as an individualized and autonomous respiratory pacing approach for support or recovery from ventilatory deficiency.

Entities:  

Keywords:  closed-loop; neuromorphic; respiratory pacing; spinal cord injury; stimulation

Mesh:

Year:  2019        PMID: 31146654      PMCID: PMC6892433          DOI: 10.1089/neu.2018.6358

Source DB:  PubMed          Journal:  J Neurotrauma        ISSN: 0897-7151            Impact factor:   5.269


  50 in total

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Authors:  E C Stites; J J Abbas
Journal:  IEEE Trans Biomed Eng       Date:  2000-09       Impact factor: 4.538

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Authors:  James S Walter; Robert D Wurster; Qianlong Zhu; Franco Laghi
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Review 3.  Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data.

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Authors:  Carlos B Mantilla; Yasin B Seven; Wen-Zhi Zhan; Gary C Sieck
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5.  An IC-based controllable stimulator for respiratory muscle stimulation investigations.

Authors:  Jonathan Castelli; Florian Kolbl; Ricardo Siu; Gilles N'Kaoua; Yannick Bornat; Ashwin Mangalore; Brian Hillen; James J Abbas; Sylvie Renaud; Ranu Jung; Noelle Lewis
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2017-07

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Authors:  M L Nochomovitz; A F Dimarco; J T Mortimer; N S Cherniack
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Journal:  Biol Psychiatry       Date:  2001-04-01       Impact factor: 13.382

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Authors:  Raymond P Onders
Journal:  Handb Clin Neurol       Date:  2012

9.  Mechanical Ventilation and Diaphragmatic Atrophy in Critically Ill Patients: An Ultrasound Study.

Authors:  Massimo Zambon; Paolo Beccaria; Jun Matsuno; Marco Gemma; Elena Frati; Sergio Colombo; Luca Cabrini; Giovanni Landoni; Alberto Zangrillo
Journal:  Crit Care Med       Date:  2016-07       Impact factor: 7.598

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Authors:  Sanford Levine; Taitan Nguyen; Nyali Taylor; Michael E Friscia; Murat T Budak; Pamela Rothenberg; Jianliang Zhu; Rajeev Sachdeva; Seema Sonnad; Larry R Kaiser; Neal A Rubinstein; Scott K Powers; Joseph B Shrager
Journal:  N Engl J Med       Date:  2008-03-27       Impact factor: 91.245

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  1 in total

1.  Autonomous control of ventilation through closed-loop adaptive respiratory pacing.

Authors:  Ricardo Siu; James J Abbas; David D Fuller; Jefferson Gomes; Sylvie Renaud; Ranu Jung
Journal:  Sci Rep       Date:  2020-12-14       Impact factor: 4.379

  1 in total

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