Anomaly detection device and method for respiratory mechanics parameter estimation

1. A mechanical ventilation device, comprising:

a mechanical ventilator;

at least one airway sensor configured to measure at least one of airway pressure and airway air flow as a function of time for a patient on the mechanical ventilator;

at least one microprocessor programmed to:

analyze at least one of airway pressure and airway air flow measured by the airway sensor to detect a spontaneous respiration anomaly in respiratory muscle pressure as a function of time generated by a patient on the mechanical ventilator;

determine a time of ventilator cycling off from a signal received from the mechanical ventilator; and

identify a type of a patient-ventilator dyssynchrony based on position of peaks detected in the analyzed at least one airway flow and airway pressure respective to the time of ventilator cycling off; and

a display component configured to display an indication of the spontaneous respiration anomaly detected by the at least one microprocessor,

wherein:

the at least one airway sensor includes an airway pressure sensor configured to measure airway pressure as a function of time; and

the at least one microprocessor is programmed to analyze airway pressure measured by the airway pressure sensor to detect the spontaneous respiration anomaly comprising a double effort event as a double peak in the airway pressure as a function of time in which at least one peak of the double peak is not coincident with the mechanical ventilator cycling off.

2. The device of claim 1 wherein: the at least one microprocessor is programmed to analyze airway pressure measured by the airway pressure sensor to detect the spontaneous respiration anomaly comprising an early cycling off event as a double peak in the airway pressure as a function of time coincident with the mechanical ventilator cycling off.

3. The device of claim 2 wherein the at least one microprocessor receives a signal indicative of the mechanical ventilator cycling off and uses the signal to determine a time of the mechanical ventilator cycling off.

4. The device of claim 1 wherein: the at least one microprocessor is programmed to analyze airway pressure measured by the airway pressure sensor to detect the spontaneous respiration anomaly as a double peak in the airway pressure as a function of time within a single breath cycle.

5. The patient monitoring device of claim 1 , wherein the at least one airway sensor includes the airway pressure sensor configured to measure airway pressure and the air flow sensor configured to measure airway air flow, and the at least one microprocessor is further programmed to:

calculate one or more respiratory system variables including at least respiratory muscle pressure as a function of time based on the measured airway pressure and airway air flow; and

wherein the detection of the spontaneous respiration anomaly does not use the calculated respiratory muscle pressure as a function of time.

6. The patient monitoring device of claim 5 , wherein:

the at least one microprocessor is programmed to detect spontaneous respiration anomalies including at least an early cycling off anomaly, an active exhalation anomaly, and a double effort anomaly; and

the display component is configured to indicate unreliability of the calculated respiratory system variables if an early cycling off anomaly, an active exhalation anomaly, or a double effort anomaly is detected.

7. The patient monitoring device of claim 5 , wherein the display component is configured to display values of one or more respiratory system variables including at least respiratory muscle pressure as a function of time based on the measured airway pressure and airway air flow.

8. The patient monitoring device of claim 1 , further including a power of breathing closed-loop controller programmed to:

adjust an output of the mechanical ventilator responsive to at least one flag value responsive to a detection of at least one spontaneous respiration anomaly including an early cycling off anomaly, an active exhalation anomaly, and a double effort anomaly.

9. A mechanical ventilation device comprising:

a mechanical ventilator;

at least one airway sensor configured to measure at least one of airway pressure and airway air flow as a function of time for a patient on the mechanical ventilator, wherein the at least one airway sensor includes an airway pressure sensor configured to measure airway pressure as a function of time; and

at least one microprocessor programmed to:

analyze airway pressure measured by the airway pressure sensor to detect a spontaneous respiration anomaly in respiratory muscle pressure as a function of time generated by a patient on the mechanical ventilator, the spontaneous respiration anomaly comprising active exhalation detected as downward slope of the airway pressure following the mechanical ventilator cycling off which is larger than a threshold value;

determine a time of ventilator cycling off from a signal received from the mechanical ventilator; and

identify a type of a patient-ventilator dyssynchrony based on position of peaks detected in the analyzed at least one airway flow and airway pressure respective to the time of ventilator cycling off; and

a display component configured to display an indication of the spontaneous respiration anomaly detected by the at least one microprocessor.

10. The device of claim 9 , wherein: the at least one microprocessor is programmed to analyze airway pressure measured by the airway pressure sensor to detect the spontaneous respiration anomaly as a double peak in the airway pressure as a function of time within a single breath cycle.

11. The patient monitoring device of claim 9 , wherein the at least one airway sensor includes the airway pressure sensor configured to measure airway pressure and the air flow sensor configured to measure airway air flow, and the at least one microprocessor is further programmed to:

calculate one or more respiratory system variables including at least respiratory muscle pressure as a function of time based on the measured airway pressure and airway air flow; and

wherein the detection of the spontaneous respiration anomaly does not use the calculated respiratory muscle pressure as a function of time.

12. The patient monitoring device of claim 11 , wherein:

the at least one microprocessor is programmed to detect spontaneous respiration anomalies including at least an early cycling off anomaly, an active exhalation anomaly, and a double effort anomaly; and

the display component is configured to indicate unreliability of the calculated respiratory system variables if an early cycling off anomaly, an active exhalation anomaly, or a double effort anomaly is detected.

13. The patient monitoring device of claim 11 , wherein the display component is configured to display values of one or more respiratory system variables including at least respiratory muscle pressure as a function of time based on the measured airway pressure and airway air flow.

14. The patient monitoring device of claim 9 , further including a power of breathing closed-loop controller programmed to:

adjust an output of the mechanical ventilator responsive to at least one flag value responsive to a detection of at least one spontaneous respiration anomaly including an early cycling off anomaly, an active exhalation anomaly, and a double effort anomaly.

15. A non-transitory storage medium storing instructions readable and executable by one or more microprocessors to perform a method of detecting a spontaneous respiration anomaly, the method comprising:

detecting peaks in an airway pressure versus time signal acquired for a patient on a mechanical ventilator; and

detecting a patient-ventilator dyssynchrony indicated by a double peak in the airway pressure versus time signal within a single breath;

determining a time of ventilator cycling off from a signal received from a mechanical ventilator; and

identifying a type of the patient-ventilator dyssynchrony based on position of the double peak respective to the time of ventilator cycling off.

16. The non-transitory storage medium of claim 15 , wherein the identifying further includes:

identifying an early cycling off patient-ventilator dyssynchrony based on the position of the second peak of the double peak being after the time of ventilator cycling off.

17. The non-transitory storage medium of claim 15 , wherein the method further comprises:

identifying an early cycling off patient-ventilator dyssynchrony based on the double peak being the largest peak in the breath.

18. The non-transitory storage medium of claim 15 , wherein the method further comprises: calculating one or more respiratory system variables including at least respiratory muscle pressure as a function of time based on a measured airway pressure and airway air flow; and wherein the detection of the patient-ventilator dyssynchrony does not use the calculated respiratory muscle pressure as a function of time.

19. The non-transitory storage medium of claim 15 , wherein the method further comprises:

adjusting an output of the mechanical ventilator responsive to at least one flag value responsive to a detection of at least one spontaneous respiration anomaly including an early cycling off anomaly, an active exhalation anomaly, and a double effort anomaly.