Machine learning-based systems and methods for breath monitoring and assistance of a patient

An apparatus for machine learning-based breath monitoring, the apparatus comprising at least one processor and at least one memory including program code, the at least one memory and the program code configured to, with the processor, cause the apparatus to at least:

• receive breathing pattern sensory data generated based at least in part on output of a breathing sensor monitoring a monitored individual's breathing;
• generate breathing waveform data reflecting a breathing cycle of inspiration and expiration of the monitored individual, based at least in part on the breathing pattern sensory data for the monitored individual;
• determine one or more splinting occurrences reflected within the breathing waveform data;
• map a stimulation schedule to the breathing waveform data, wherein the stimulation schedule defines one or more stimulation triggers reflected within the breathing waveform data and detectable within the breathing pattern sensory data for stimulating nerves of the monitored individual;
• and
• in response to detecting a stimulation trigger of the one or more stimulation triggers within the breathing pattern sensory data, cause a stimulator in contact with the monitored individual to emit a stimulation signal to the monitored individual, wherein the stimulation signal is characterized by stimulation parameters.

A computer program product for machine learning-based breath monitoring, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions configured to:

• receive breathing pattern sensory data generated based at least in part on output of a breathing sensor monitoring a monitored individual's breathing;
• generate breathing waveform data reflecting a breathing cycle of inspiration and expiration of the monitored individual, based at least in part on the breathing pattern sensory data for the monitored individual;
• determine one or more splinting occurrences reflected within the breathing waveform data;
• map a stimulation schedule to the breathing waveform data, wherein the stimulation schedule defines one or more stimulation triggers reflected within the breathing waveform data and detectable within the breathing pattern sensory data for stimulating nerves of the monitored individual;
• and
• in response to detecting a stimulation trigger of the one or more stimulation triggers within the breathing pattern sensory data, cause a stimulator in contact with the monitored individual to emit a stimulation signal to the monitored individual, wherein the stimulation signal is characterized by stimulation parameters.