A medical device includes a processor, an acceleration sensor, and memory. The acceleration sensor is configured to generate acceleration data that comprises a plurality of acceleration measurements. The memory comprises instructions that when executed by the processor, cause the processor to: obtain the acceleration data from the acceleration sensor; and determine, based on the acceleration data, that the medical device has flipped.

Computer implemented methods and systems are provided that comprise, under control of one or more processors of a medical device, where the one or more processors are configured with specific executable instructions. The methods and systems obtain motion data indicative of at least one of a posture or a respiration cycle; obtain cardiac activity (CA) signals for a series of beats; identify whether a characteristic of interest (COI) from at least a first segment of the CA signals exceeds a COI limit; analyze the motion data to determine whether at least one of the posture or respiration cycle at least in part caused the COI to exceed the COI limit. Based on the analyzing operation, the methods and systems automatically adjust a CA sensing parameter utilized by the medical device to detect R-waves in subsequent CA signals; and detect an arrhythmia based on a presence or absence of one or more of the R-waves in at least a second segment of the CA signals.

A multi sensor module especially designed for use in sleep-study applications includes a PVDF film piezoelectric transducer enclosed between an upper layer of a single-sided adhesive tape strip and a lower layer of a double-sided adhesive tape strip. Also adhesively affixed to the upper single-sided adhesive tape strip, but not overlaid by the lower double-sided adhesive tape strip are first and second conductive electrodes. The combination sensor module is adapted to be adhesively affixed to the chest area of a person and further included in an extension of the PVDF strip that is adapted to overlay the suprasternal notch of a person for producing signals responsive to respiratory activity of the person.

A medical system (100) is disclosed that provides a respiratory-based control of at least one medical procedure. In this regard, the medical system (100) includes one or more appropriate sensors (108) for providing respiratory data on a patient (104). This respiratory data is utilized by respiration assessment logic (116) to determine if the respiratory data has exceeded one or more respiration thresholds and which may be equated with a sudden respiratory event. Identification of such a sudden respiratory event by the logic (116) results in the suspension of the noted medical procedure. Patient respiration data may also be displayed, for instance in a color that depends upon its magnitude or level.

An apnea classification system provides for apnea monitoring and differentiation based on several sleep apnea related parameters for diagnostic and therapeutic purposes. Monitoring of such sleep apnea related parameters allows the apnea classification system to differentiate among the different types of apnea and hypopnea and to identify an occurrence of periodic respiration. This information may then be used to determine the best method of therapy, or adjust current therapy parameters to more effectively treat a subject.

A pneumocardial function monitor includes a carrier configured to be mounted about at least a part of a trunk of a body of a subject. A sensing arrangement is mounted on the carrier, the sensing arrangement including at least one element for monitoring changes in volume of the part of the subject's body. A signal processing module is in communication with the sensing arrangement for processing signals output from the sensing arrangement, the signal processing module having at least one output for outputting a signal related to respiratory function and/or cardiac function.

A system and method for automatically implementing a therapy for treating sleep disordered breathing.

In some examples, processing circuitry of a medical device system determines, for each of a plurality of patient parameters, a difference metric for a current period based on a value of a patient parameter determined for the current period and a value of the patient parameter determined for an immediately preceding period, and determines a score for the current period based on a sum of the difference metrics for at least some of the plurality of patient parameters. The processing circuitry determines a threshold for the current period based on scores determined for N periods that precede the current period, compares the score for the current period to the threshold, and determines whether to generate an alert indicating that an acute cardiac event of the patient, e.g., ventricular tachyarrhythmia, is predicted, and/or deliver a therapy configured to prevent the acute cardiac event, based on the comparison.

An electrode padset and a method of using the electrode padset are disclosed herein. The electrode padset is a single unit, consisting of multiple patient-contacting conductive pads arranged on a single piece of material. The padset is comprised of a plurality of conductive pads, at least one conductive pad adapted to emit an electrical signal and at least one other conductive pad adapted to receive an electrical signal, and an electrically conductive material coupling the conductive pads.

Systems and methods for monitoring patients with multiple chronic diseases are described. A system may include a health status monitor that receives diagnostic data including physiological signals sensed from a patient. The system may produce at least a first risk indication of the patient developing a first disease and a second risk indication of the patient developing a different second disease. The system may detect the first and second diseases from the physiological signals, and generate a composite health status indicator using the detections of the first and second diseases and the first and second risk indications. An alert of worsening health status may be generated if the composite detection score exceeds an alert threshold.