Autonomous control of ventilation through closed-loop adaptive respiratory pacing

Abstract

Mechanical ventilation is the standard treatment when volitional breathing is insufficient, but drawbacks include muscle atrophy, alveolar damage, and reduced mobility. Respiratory pacing is an alternative approach using electrical stimulation-induced diaphragm contraction to ventilate the lung. Oxygenation and acid–base homeostasis are maintained by matching ventilation to metabolic needs; however, current pacing technology requires manual tuning and does not respond to dynamic user-specific metabolic demand, thus requiring re-tuning of stimulation parameters as physiological changes occur. Here, we describe respiratory pacing using a closed-loop adaptive controller that can self-adjust in real-time to meet metabolic needs. The controller uses an adaptive Pattern Generator Pattern Shaper (PG/PS) architecture that autonomously generates a desired ventilatory pattern in response to dynamic changes in arterial CO2 levels and, based on a learning algorithm, modulates stimulation intensity and respiratory cycle duration to evoke this ventilatory pattern. In vivo experiments in rats with respiratory depression and in those with a paralyzed hemidiaphragm confirmed that the controller can adapt and control ventilation to ameliorate hypoventilation and restore normocapnia regardless of the cause of respiratory dysfunction. This novel closed-loop bioelectronic controller advances the state-of-art in respiratory pacing by demonstrating the ability to automatically personalize stimulation patterns and adapt to achieve adequate ventilation.

Supervisory Algorithm for Autonomous Hemodynamic Management Systems

“…Quick control and monitoring of multiple interconnected sub-units as contained in SACM are critical for optimal utility of these systems, especially as more advanced artificial intelligence is developed. For instance, closed-loop systems are in development for ventilators [4][5][6] and anesthesia [12] devices as well as many other technologies. In trauma care, there is a precise interplay between these systems similar to how SACM monitors hemodynamic management that will need to be continuously monitored [13,14].…”

“…Because they can automatically execute rapid adjustments in care in response to a patient's needs, autonomous and semi-autonomous medical systems hold the promise of revolutionizing the practice and delivery of personalized medicine [1][2][3]. Rapid adjustments are particularly critical for patient management in the perioperative and intensive care setting, where closed-loop controllers have been developed for ventilator management [4][5][6] and fluid resuscitation [7][8][9][10], as well as pain control [11] and sedation [12]. In much the same way that a thermostat manages a household's temperature by controlling an air conditioner or heater, these closed-loop medical systems capture a physiological variable (etCO 2 , SpO 2 , MAP, EEG, etc.…”