Abstract: A ventilation device includes a mechanical ventilator (10), respiratory sensors (30, 32) configured to acquire measurements of respiratory variables including at least measurements of airway pressure and airway flow, and an electronic processor (14) programmed to perform a ventilation method including: operating the mechanical ventilator to provide mechanical ventilation controlled using measurements acquired by the respiratory sensors; performing a pause maneuver comprising closing at least one of an inhalation valve (38) and an exhalation valve (40) for a pause interval and estimating a respiratory mechanics index from one or more respiratory system parameters estimated from measurements acquired by the respiratory sensors during or after the pause interval; and triggering a pause maneuver in response to detecting a change in the estimated respiratory mechanics index.

Abstract: A system (100) for assessing fluid responsiveness includes an infusion pump (24) in communication with at least one processor (32), and a plurality of physiological monitors (40,42,44,46) operable to receive physiological signals from an associated patient. Physiological signals (48,50) acquired from the associated patient (10) during a fluid challenge are synchronized with a timing signal (54) of the infusion pump (24) administering the fluid challenge. One or more dynamic indices and/or features (58) is calculated from the synchronized physiological signals (50), and one or more dynamic indices and/or features (50) is calculated from baseline physiological signals (48) acquired from the associated patient (10) prior to the fluid challenge. A fluid responsiveness probability value (64) of the patient (10) is determined based on dynamic indices and/or features (58) from the synchronized physiological signals (50) and dynamic indices and/or features (50) from the baseline physiological signals (48).

Abstract: A method includes obtaining a first physiological parameter indicative of a non-invasively measured airway pressure of a subject, obtaining a second physiological parameter indicative of a non-invasively measured air flow into the lungs of the subject, and estimating a third physiological parameter indicative of an intra-pleural pressure of the subject based on the first and second physiological parameters and generating a signal indicative thereof. An other method includes obtaining a first physiological parameter indicative of a non-invasively estimated intra-pleural pressure of a subject, determining a second physiological parameter indicative of a lung volume of the subject that is based on a third physiological parameter indicative of a non-invasively measured air flow into the lungs of the subject, and determining a work of breathing based on the first and second physiological parameters and generating a signal indicative thereof.

Abstract: A ventilation device includes a mechanical ventilator (10), respiratory sensors (30, 32) configured to acquire measurements of respiratory variables including at least measurements of airway pressure and airway flow, and an electronic processor (14) programmed to perform a ventilation method including: operating the mechanical ventilator to provide mechanical ventilation controlled using measurements acquired by the respiratory sensors; performing a pause maneuver comprising closing at least one of an inhalation valve (38) and an exhalation valve (40) for a pause interval and estimating a respiratory mechanics index from one or more respiratory system parameters estimated from measurements acquired by the respiratory sensors during or after the pause interval; and triggering a pause maneuver in response to detecting a change in the estimated respiratory mechanics index.

Abstract: A medical modeling system and method predict a risk of a physiological condition, such as mortality, for a patient. Measurements of a plurality of predictive variables for the patient are received. The plurality of predictive variables are predictive of the risk of the physiological condition. The risk of the physiological condition is calculated by applying the received measurements to at least one model modeling the risk of the physiological condition using the plurality of predictive variables. The at least one model includes at least one of a hidden Markov model and a logistic regression model. An indication of the risk of the physiological condition is output to a clinician.

Abstract: In a medical ventilator system, a ventilator (10) delivers ventilation to a ventilated patient (12). Sensors (24, 26) acquire airway pressure and air flow data for the ventilated patient. A probabilistic estimator module (40) estimates respiratory parameters of the ventilated patient by fitting a respiration system model (50) to a data set comprising the acquired airway pressure and air flow data using probabilistic analysis, such as Bayesian analysis, in which the respiratory parameters are represented as random variables. A display component (22) displays the estimated respiratory parameters of the ventilated patient along with confidence or uncertainty data comprising or derived from probability density functions for the random variables representing the estimated respiratory parameters.

Abstract: A system (100) for assessing fluid responsiveness includes an infusion pump (24) in communication with at least one processor (32), and a plurality of physiological monitors (40,42,44,46) operable to receive physiological signals from an associated patient. Physiological signals (48,50) acquired from the associated patient (10) during a fluid challenge are synchronized with a timing signal (54) of the infusion pump (24) administering the fluid challenge. One or more dynamic indices and/or features (58) is calculated from the synchronized physiological signals (50), and one or more dynamic indices and/or features (50) is calculated from baseline physiological signals (48) acquired from the associated patient (10) prior to the fluid challenge. A fluid responsiveness probability value (64) of the patient (10) is determined based on dynamic indices and/or features (58) from the synchronized physiological signals (50) and dynamic indices and/or features (50) from the baseline physiological signals (48).

Abstract: A method includes obtaining a first physiological parameter indicative of a non-invasively measured airway pressure of a subject, obtaining a second physiological parameter indicative of a non-invasively measured air flow into the lungs of the subject, and estimating a third physiological parameter indicative of an intra-pleural pressure of the subject based on the first and second physiological parameters and generating a signal indicative thereof. An other method includes obtaining a first physiological parameter indicative of a non-invasively estimated intra-pleural pressure of a subject, determining a second physiological parameter indicative of a lung volume of the subject that is based on a third physiological parameter indicative of a non-invasively measured air flow into the lungs of the subject, and determining a work of breathing based on the first and second physiological parameters and generating a signal indicative thereof.

Abstract: A medical modeling system and method predict a risk of a physiological condition, such as mortality, for a patient. Measurements of a plurality of predictive variables for the patient are received. The plurality of predictive variables are predictive of the risk of the physiological condition. The risk of the physiological condition is calculated by applying the received measurements to at least one model modeling the risk of the physiological condition using the plurality of predictive variables. The at least one model includes at least one of a hidden Markov model and a logistic regression model. An indication of the risk of the physiological condition is output to a clinician.

Abstract: The invention relates to a portable vacuum connector device 100. The connector device can be attached to various surfaces such as surfaces of CT scanner or other medical equipment by means of vacuum cups or connectors 102. The vacuum connector device 100 has a connection structure 101 such as a rail to which a portable medical device can be attached via its connection feature 202, e.g. a hook. Accordingly, the connector device 100 makes may make it easier to let the portable medical device follow the patient as the patient is moved from location to location. An air pressure sensor 104 is provided for monitoring the vacuum level and for enabling generation of an alarm via an external monitoring device such as the portable medical device 201.