Abstract:
A method and implantable medical device for determining an atrial arrhythmia event that includes sensing a cardiac signal, determining an atrial arrhythmia score for identifying the arrhythmia event in response to the sensed cardiac signal, determining a sensing window in response to the sensed cardiac signal, the sensing window having a first portion and a second portion, determining signal characteristics of the sensed cardiac signal within the first portion and within the second portion, determining whether the sensed cardiac signal within the first portion and within the second portion corresponds to a P-wave in response to the determined signal characteristics, determining whether a signal to noise ratio of the sensed cardiac signal within the first portion and the second portion of the sensing window is satisfied, determining whether to update the arrhythmia score in response to the determined P-wave and the determined signal to noise ratio, and determining whether to delivery an arrhythmia therapy in response to the updated arrhythmia score.
Abstract:
A method and implantable medical device for determining an atrial arrhythmia event that includes sensing a cardiac signal, determining an atrial arrhythmia score for identifying the arrhythmia event in response to the sensed cardiac signal, determining a sensing window in response to the sensed cardiac signal, the sensing window having a first portion and a second portion, determining signal characteristics of the sensed cardiac signal within the first portion and within the second portion, determining whether the sensed cardiac signal within the first portion and within the second portion corresponds to a P-wave in response to the determined signal characteristics, determining whether a signal to noise ratio of the sensed cardiac signal within the first portion and the second portion of the sensing window is satisfied, determining whether to update the arrhythmia score in response to the determined P-wave and the determined signal to noise ratio, and determining whether to delivery an arrhythmia therapy in response to the updated arrhythmia score.
Abstract:
A cardiac monitoring device for determining the occurrence of a sick sinus syndrome condition of a patient that includes a plurality of electrodes to sense a cardiac signal, a sensing module electrically coupled to the plurality of electrodes having circuitry positioned therein to receive the sensed cardiac signal, and a processor coupled to the sensing module and configured to determine an RR interval variability during an RR interval variability session in response to the sensed cardiac signal, determine whether a P-wave occurs during the RR interval variability session, determine whether a sick sinus indicator is satisfied in response to a P-wave occurring, increment a sick sinus count in response to the sick sinus indicator being satisfied, determine whether a sick sinus burden is satisfied in response to the sick sinus count being incremented, and determine the occurrence of sick sinus syndrome in response to the sick sinus burden being satisfied.
Abstract:
Provided is a method, system and/or apparatus for determining prospective heart failure event risk. Acquired from a device memory are a heart failure patient's current and preceding risk assessment periods. Counting detected data observations in the current risk assessment period for a current risk assessment total amount and counting detected data observations in the preceding risk assessment period for a preceding risk assessment period total amount. Associating the current risk assessment and preceding risk assessment total amounts with a lookup table to acquire prospective risk of heart failure (HF) event for the preceding risk assessment period and the current risk assessment period. Employing weighted sums of the prospective risk of the HF event for the preceding risk assessment period and the current risk assessment period to calculate a weighted prospective risk of the HF event for a patient. Displaying on a graphical user interface the weighted prospective risk of the HF event for the patient.
Abstract:
Techniques for using multiple physiological parameters to provide an early warning for worsening heart failure are described. A medical device monitors a primary diagnostic parameter that is indicative of worsening heart failure, such as intrathoracic impedance or pressure, and one or more secondary diagnostic parameters. The medical device detects worsening heart failure in the patient based on the primary diagnostic parameter when an index that is changed over time based on the primary diagnostic parameter value is outside a range of values, termed the threshold zone. When the index is within the threshold zone, the medical device detects worsening heart failure in the patient based on the one or more secondary diagnostic parameters. Upon detecting worsening heart failure, the medical device may, for example, provide an alert that enables the patient to seek medical attention before experiencing a heart failure event.
Abstract:
A medical device may be configured to determine heart rates of the patient based on the cardiac signal sensed during a first period. The medical device may detect one or more sleep apnea episodes of the patient occurring during the first period. The medical device may determine whether one or more verification conditions are satisfied. Responsive to determining that the one or more verification conditions are satisfied, the medical device may measure impedances of the patient during a second period subsequent to the first period, and use impedance to the measured impedances to detect one or more sleep apnea episodes of the patient occurring during the second period.
Abstract:
Methods and systems for seamless adjustment of treatment are disclosed. A determination is made as to whether to intervene with a patient's treatment. Implanted device memory data is acquired over a pre-specified time period. Risk status is determined from the device memory data. Another external device memory data is acquired over a pre-specified time period. A determination is made as to whether to adjust treatment of the patient in response to the risk status, the data acquired from the implanted device memory and the external device memory data.
Abstract:
This disclosure is directed to devices, systems, and techniques for determining an efficacy of a treatment program. For example, a medical device system includes a medical device including one or more sensors configured to generate a signal that indicates a parameter of a patient. Additionally, the medical device system includes processing circuitry configured to receive data indicative of a user selection of a reference time; determine a plurality of parameter values of the parameter based on a portion of the signal corresponding to a period of time including the reference time. Additionally, the processing circuitry is configured to identify, based on a first set of parameter values, a reference parameter value, calculate a parameter change value, and determine, based on the parameter change value, whether an improvement or a worsening of the patient has occurred responsive to a treatment administered beginning at the reference time.
Abstract:
A system and method for detecting and verifying bradycardia/asystole episodes includes sensing an electrogram (EGM) signal. The EGM signal is compared to a primary threshold to sense events in the EGM signal, and at least one of a bradycardia or an asystole is detected based on the comparison. In response to detecting at least one of a bradycardia or an asystole, the EGM signal is compared to a secondary threshold to sense events under-sensed by the primary threshold. The validity of the bradycardia or the asystole is determined based on the detected under-sensed events.
Abstract:
A system may measure, by one or more sensors, a biometric parameter associated with a subject. The system may determine values of a control parameter based on measuring the biometric parameter. The control parameter may include blood pressure of the subject. The system may perform a control measure based on a comparison of the values of the control parameters to a threshold. Performing the control measure may include delivering therapy treatment to the subject or outputting a notification indicating an action associated with treating a medical condition. Measuring the biometric parameter, determining the values of the control parameter, and performing the control measure may be in response to one or more trigger criteria.