System and method for neuromorphic controlled adaptive pacing of respiratory muscles and nerves

A method of adaptive pacing of muscles and nerves in a body, the method comprising:

• detecting at least one physiological parameter of the body;
• comparing the detected at least one physiological parameter with at least one desired physiological parameter to generate a first difference;
• updating, by a pattern generator of a controller, at least one stimulation parameter in response to the first difference, the pattern generator having a first neural network mimicking a simplified connectivity pattern of bulbospinal neurons of a brain stem;
• generating, by the pattern generator, a breathing pattern frequency based on a first biomimetic pattern generated by the first neural network in response to the at least one updated stimulation parameter;
• generating, by a pattern shaper of the controller, a stimulus control signal comprising at least one amplitude of at least one stimulus pulse and at least one frequency of the at least one stimulus pulse, the pattern shaper having a second neural network mimicking a simplified connectivity pattern of phrenic motor neurons, and the generating of the stimulus control signal being based on a second biomimetic pattern generated by the second neural network in response to the breathing pattern frequency;
• and
• actuating, based on the stimulus control signal, an electrode coupled to at least one tissue of the body.

A non-transitory computer-readable storage medium comprising computer executable program code stored thereon that, when executed by a processor, performs the following steps:

• detecting at least one physiological parameter of a body;
• comparing the detected at least one physiological parameter with at least one desired physiological parameter to generate a first difference;
• updating at least one stimulation parameter in response to the first difference using a pattern generator, the pattern generator having a first neural network mimicking a simplified connectivity pattern of bulbospinal neurons of a brain stem;
• generating a rhythmic breathing pattern frequency based on a first biomimetic pattern generated by the first neural network using the at least one updated stimulation parameter;
• generating a stimulus control signal using on a second biomimetic pattern generated by second neural network mimicking a simplified connectivity pattern of spinal cord neurons that determine at least one frequency of a stimulus pulse and at least one amplitude of the stimulus pulse, the generating of the stimulus control signal being based on the rhythmic breathing pattern frequency;
• and
• actuating an electrode coupled to at least one tissue of the body using the stimulus control signal.