Abstract: An implantable or other ambulatory medical apparatus comprises a posture sensing circuit, a physiologic sensing circuit that senses a time varying physiologic signal, and a processor circuit. The processor circuit includes a posture calculation circuit and a measurement circuit. The posture calculation circuit determines a posture of the subject using posture data obtained using the posture signal and determines when the posture of the subject is steady state. The measurement circuit derives a physiologic measurement using physiologic data extracted from the physiologic signal during at least one time period when posture is determined to be steady state and provides the physiologic measurement to at least one of a user and a process in association with the determined steady state posture.

Abstract: An apparatus comprises plurality of sensors and a processor. Each sensor provides a sensor signal that includes physiological information and at least one sensor is implantable. The processor includes a physiological change event detection module that detects a physiological change event from a sensor signal and produces an indication of occurrence of one or more detected physiological change events, and a heart failure (HF) detection module. The HF detection module determines, using a first rule, whether the detected physiological change event indicative of a change in HF status of a subject, determines whether to override the first rule HF determination using a second rules, and declares whether the change in HF status occurred according to the first and second rules.

Abstract: Patient posture information can be received, such as to indicate a change in patient posture by at least a threshold amount. A transient response signal indicative of a change in a physiological parameter can be received at multiple instances near a change in patient posture. Waveform morphology features can be extracted from a transient response signal and used to provide an indication of a cardiac status, such as a heart failure status.

Abstract: An apparatus may include a sensing circuit and a processor. The sensing circuit is configured to generate a sensed physiological signal, wherein the physiological signal includes respiration information of a subject. The processor includes an end expiratory volume (EEV) module configured to determine a value of EEV of the subject using the sensed physiological signal, and a lung hyperinflation detection module configured to generate an indication of lung hyperinflation of the subject according to the value of EEV and provide the indication to at least one of a user or process.

Abstract: A system may include a port, at least one sensing circuit, and at least one processor. The port is configured to receive an indication of dosing of medication to treat a pulmonary condition of a heart failure (HF) subject and the at least one sensing circuit configured to sense at least one physiological signal, wherein the physiological signal includes physiological information of the HF subject. The at least one processor includes a parameter module configured to extract values of at least one physiological parameter indicative of health status of the HF subject, and a trending module configured to trend extracted values of the at least one physiological parameter and detect an effect of the dosing of the medication on the HF subject using the trending of the extracted values of the at least one physiological parameter.

Abstract: Systems and methods for detecting a worsening of patient's heart failure condition based, at least in part, on an increasing trend in a representative rapid shallow breathing index (RSBI) value over multiple days. The RSBI value may be a minimum RSBI, and more particularly may be a minimum RSBI value determined for an afternoon portion of each of the multiple days. The minimum RSBI value measured during an afternoon portion of the day may be more sensitive to changes in a patient's respiration, particularly when a patient is expected to be more active, and thus, may more readily exhibit an increasing trend when patient's heart failure is in decline.

Abstract: A physiological response to activity (PRA) during a subject's activities of daily living (ADL) can be used, such as to generate useful diagnostic information about the subject. This can involve using a template, such as an impulse response template. The technique can be used with an implantable or other ambulatory medical monitoring or therapy device, such as a cardiac function management device, or with a local or remote external interface device.

Abstract: An apparatus comprises plurality of sensors and a processor. Each sensor provides a sensor signal that includes physiological information and at least one sensor is implantable. The processor includes a physiological change event detection module that detects a physiological change event from a sensor signal and produces an indication of occurrence of one or more detected physiological change events, and a heart failure (HF) detection module. The HF detection module determines, using a first rule, whether the detected physiological change event indicative of a change in HF status of a subject, determines whether to override the first rule HF determination using a second rules, and declares whether the change in HF status occurred according to the first and second rules.

Abstract: An apparatus comprises plurality of sensors and a processor. Each sensor provides a sensor signal that includes physiological information and at least one sensor is implantable. The processor includes a physiological change event detection module that detects a physiological change event from a sensor signal and produces an indication of occurrence of one or more detected physiological change events, and a heart failure (HF) detection module. The HF detection module determines, using a first rule, whether the detected physiological change event is indicative of a change in HF status of a subject, determines whether to override the first rule HF determination using a second rules, and declares whether the change in HF status occurred according to the first and second rules.

Abstract: An apparatus comprises plurality of sensors and a processor. Each sensor provides a sensor signal that includes physiological information and at least one sensor is implantable. The processor includes a physiological change event detection module that detects a physiological change event from a sensor signal and produces an indication of occurrence of one or more detected physiological change events, and a heart failure (HF) detection module. The HF detection module determines, using a first rule, whether the detected physiological change event is indicative of a change in HF status of a subject, determines whether to override the first rule HF determination using a second rules, and declares whether the change in HF status occurred according to the first and second rules.

Abstract: An apparatus comprises plurality of sensors and a processor. Each sensor provides a sensor signal that includes physiological information and at least one sensor is implantable. The processor includes a physiological change event detection module that detects a physiological change event from a sensor signal and produces an indication of occurrence of one or more detected physiological change events, and a heart failure (HF) detection module. The HF detection module determines, using a first rule, whether the detected physiological change event is indicative of a change in HF status of a subject, determines whether to override the first rule HF determination using a second rules, and declares whether the change in HF status occurred according to the first and second rules.

Abstract: Patient posture information can be received, such as to indicate a change in patient posture by at least a threshold amount. A transient response signal indicative of a change in a physiological parameter can be received at multiple instances near a change in patient posture. Waveform morphology features can be extracted from a transient response signal and used to provide an indication of a cardiac status, such as a heart failure status.

Abstract: A system may include a port, at least one sensing circuit, and at least one processor. The port is configured to receive an indication of dosing of medication to treat a pulmonary condition of a heart failure (HF) subject and the at least one sensing circuit configured to sense at least one physiological signal, wherein the physiological signal includes physiological information of the HF subject. The at least one processor includes a parameter module configured to extract values of at least one physiological parameter indicative of health status of the HF subject, and a trending module configured to trend extracted values of the at least one physiological parameter and detect an effect of the dosing of the medication on the HF subject using the trending of the extracted values of the at least one physiological parameter.

Abstract: An apparatus may include a sensing circuit and a processor. The sensing circuit is configured to generate a sensed physiological signal, wherein the physiological signal includes respiration information of a subject. The processor includes an end expiratory volume (EEV) module configured to determine a value of EEV of the subject using the sensed physiological signal, and a lung hyperinflation detection module configured to generate an indication of lung hyperinflation of the subject according to the value of EEV and provide the indication to at least one of a user or process.

Abstract: Devices and methods for detecting heart failure (HF) events or identifying patient at elevated risk of developing future HF events are described. A medical device can detect contextual condition associated with a patient, such as an environmental context or a physiologic context, sense a heart sound signal, and perform multiple measurements of heart sound features in response to the detected patient contextual condition meeting specified criterion. The contextual condition includes information correlating to or indicative of a change in metabolic demand of a patient. The medical device can use the physiologic signals to calculate one or more signal metrics indicative of diastolic function of the heart such as a trend of the heart sound features. The medical device can use the signal metrics to detect an HF event or to predict the likelihood of the patient later developing an HF event.

Abstract: Various method embodiments of the present invention concern sensing patient-internal pressure measurements indicative of physiological exertion, identifying one or more steady state periods of physiological exertion based on the patient-internal pressure measurements, sensing extra-cardiac response data and cardiac response data corresponding to the one or more physiological exertion steady state periods, respectively comparing the extra-cardiac response data and the cardiac response data to extra-cardiac response information and cardiac response information associated with equivalent levels of physiological exertion intensity of the one or more steady state periods, and determining the likelihood that myocardial ischemia occurred during the one or more steady state periods based on the comparison of the extra-cardiac response data to the extra-cardiac response information and the cardiac response data to the cardiac response information.

Abstract: An apparatus comprises a physiologic sensing circuit and a control circuit. The physiologic sensing circuit is configured to sense an electrical respiration signal representative of respiration of a subject. The control circuit includes a respiration monitor circuit and a therapy circuit. The respiration monitor circuit is configured to extract a respiration parameter from the respiration signal and detect that a value of the respiration parameter is outside of a target value range for the respiration parameter. The therapy circuit is configured to deliver neural stimulation to the carotid sinus of the subject to stimulate respiration and to adjust respiration to maintain the value of the respiration parameter within the target value range.

Abstract: Systems and methods for detecting a worsening of a patient's heart failure condition based, at least in part, on a declining trend in a representative tidal volume value over multiple days. The tidal volume value may be a maximum tidal volume, and more particularly, a maximum tidal volume determined for an afternoon portion of each of the multiple days or a selected portion of each of the multiple days that excludes a night portion. The maximum tidal volume during these portions of the day may be more sensitive to changes in a patient's respiration, particularly when a patient is expected to be more active, and thus, may more readily exhibit a declining trend when the patient's heart failure status is in decline.

Abstract: Systems and methods for detecting a worsening of patient's heart failure condition based, at least in part, on an increasing trend in a representative rapid shallow breathing index (RSBI) value over multiple days. The RSBI value may be a minimum RSBI, and more particularly may be a minimum RSBI value determined for an afternoon portion of each of the multiple days. The minimum RSBI value measured during an afternoon portion of the day may be more sensitive to changes in a patient's respiration, particularly when a patient is expected to be more active, and thus, may more readily exhibit an increasing trend when patient's heart failure is in decline.

Abstract: An inspiratory muscle stimulation system uses an implantable medical device to deliver stimulation to control diaphragmatic contractions for slower and deeper breathing, thereby conditioning and strengthening inspiratory muscles. In various embodiments, respiratory and/or cardiac performance are monitored for controlling parameters of the stimulation.