Abstract: This disclosure describes systems and methods for monitoring ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. For example, many clinicians may not easily identify or recognize data patterns and correlations indicative of a fluctuation in resistance during mechanical ventilation of a patient. Furthermore, clinicians may not easily determine potential causes for the fluctuation in resistance and/or steps for mitigating the fluctuation in resistance. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect fluctuations in resistance and may issue suitable notifications and recommendations to the clinician based on potential causes of the fluctuation, ventilatory and/or patient data, etc.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of asynchrony during ventilation.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a non-triggering patient.

Abstract: This disclosure describes systems and methods for a ventilator-derived CPAP system that mimics the flow and/or pressure oscillations or fluctuations of the B-CPAP system creating a breath type referred to herein as a mimicked-bubble-CPAP (M-CPAP) mode. Further, the disclosure describes systems and methods for delivery of other breath types with flow and/or pressure oscillations or fluctuations that mimic the oscillation observed during ventilation with the B-CPAP system, referred to herein as adjusted breath types.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a non-triggering patient exhibiting an obstructive component.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. Modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during various types of pressure ventilation of a patient exhibiting an obstructive component.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a triggering patient exhibiting an obstructive component.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. Modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during various types of pressure ventilation.

Abstract: This disclosure describes systems and methods for monitoring ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. For example, many clinicians may not easily identify or recognize data patterns and correlations indicative of a fluctuation in resistance during mechanical ventilation of a patient. Furthermore, clinicians may not easily determine potential causes for the fluctuation in resistance and/or steps for mitigating the fluctuation in resistance. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect fluctuations in resistance and may issue suitable notifications and recommendations to the clinician based on potential causes of the fluctuation, ventilatory and/or patient data, etc.

Abstract: This disclosure describes systems and methods for piloting a pneumatic valve using one or more piezoelectric blowers. According to embodiments, the one or more piezoelectric blowers may be coupled to the pneumatic valve to form a small, light-weight pneumatic valve that may be placed proximal to a ventilated patient, e.g., at the patient wye or the patient interface. Due to the close coupling of the one or more piezoelectric blowers, the pneumatic valve has a substantially shorter response time than traditional pneumatically piloted valves. Moreover, when piezoelectric blowers are coupled to the pneumatic valve in parallel, response time may be further decreased. Additionally or alternatively, when piezoelectric blowers are coupled to the pneumatic valve in series, pilot pressure may be increased as a function of the number of piezoelectric blowers in the series.

Abstract: A method of providing high frequency ventilation to a patient, comprises delivering a flow of breathing gas to the patient, the flow of breathing gas having a first positive pressure level and a second positive pressure level, the first and second positive pressure levels alternating with one another in a plurality of cycles in the flow of breathing gas to have a frequency and an amplitude, the flow of breathing gas to the patient generating a mean airway pressure; determining whether the patient is breathing spontaneously or is trying to breath spontaneously; and, in response to the determination that the patient is breathing spontaneously or trying to breath spontaneously or according to the user settings for HFV and user intervention for non-spontaneous breathing patient, adjusting the mean airway pressure, modulating the frequency and duty cycle of the flow of breathing gas, or modulating the level of flow and pressure amplitude of the breathing gas, or two or more thereof.

Abstract: This disclosure describes systems and methods for ventilating a patient. The disclosure describes novel systems and methods for preventing and/or reducing the likelihood of a patient from receiving too much oxygen during a selected limited increase in oxygen concentration for a set period of time.

Abstract: The present disclosure describes a mode of ventilation that makes an automatic determination of an appropriate mandatory breath type in response to one or more patient based criteria. Specifically, the ventilator during the delivery a mandatory breath type determines whether predetermined ventilatory criteria have been met. Based on the determination, the ventilator may deliver one of any number of mandatory breath types. Further, the present disclosure also combines the advantages of a hybrid mode of ventilation with this automatic determination of an appropriate mandatory breath type in response to one or more patient based criteria.

Abstract: This disclosure describes novel systems and methods for monitoring volumetric CO2 during ventilation of a patient being ventilated by a medical ventilator. The disclosure describes more accurate, more cost effective, and/or less burdensome non-invasive methods and systems for calculating volumetric CO2 than previously utilized methods and systems. The disclosure describes estimating a flow rate in a breathing circuit to calculate a volumetric CO2. Further, the disclosure describes synchronizing the estimated flow rate with a measured CO2 to calculate a volumetric CO2. Additionally, the disclosure describes synchronizing a measured flow rate from within the breathing circuit with a measured CO2 to calculate a volumetric CO2.

Abstract: This disclosure describes novel systems and methods for monitoring volumetric CO2 during ventilation of a patient being ventilated by a medical ventilator. The disclosure describes more accurate, more cost effective, and/or less burdensome non-invasive methods and systems for calculating volumetric CO2 than previously utilized methods and systems. The disclosure describes estimating a flow rate in a breathing circuit to calculate a volumetric CO2. Further, the disclosure describes synchronizing the estimated flow rate with a measured CO2 to calculate a volumetric CO2. Additionally, the disclosure describes synchronizing a measured flow rate from within the breathing circuit with a measured CO2 to calculate a volumetric CO2.

Abstract: This disclosure describes systems and methods for controlling pressure and/or flow during exhalation. The disclosure describes novel exhalation modes for ventilating a patient.

Abstract: A ventilation mask storage device (300, 400, 500) includes a first (310, 410, 510) and second body members (320, 420, 520); a hinge (330, 430, 530) connecting the first and second body members so the first and second body members can be brought together to define an enclosed space (305, 405, 505) for receiving a ventilation mask (10); a clasp (340, 440, 540) connected to the first and second body members to hold the first and second body members together when the clasp is engaged; an aperture (300, 400, 500) in at least one of the first and second body members to permit a circuit (15) to be connected to the ventilation mask when it is disposed within the enclosed space; and a connector (360, 460, 560) provided with at least one of the first and second body members to attach the device to a ventilator or ventilator cart.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory data to provide useful notifications and/or recommendations. Indeed, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions or the effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate adjustments that may address certain patient conditions or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the occurrence of high-delivered VT during various types of ventilation. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect an occurrence of and potential causes for high-delivered VT and may subsequently issue suitable notifications and/or recommendations.

Abstract: The present disclosure combines the advantages of a hybrid mode of ventilation with an automatic determination of an appropriate spontaneous breath type in response to one or more patient based criteria. Specifically, when the ventilator is delivering a spontaneous breath type, a determination may be made as to whether predetermined ventilatory criteria have been met. Based on the determination the ventilator may deliver one of any number of spontaneous breath types.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of inadequate flow during ventilation.