Physio-control, Inc.

Medtronic Physio-control Manufacturing Corporation

Cardiac Science Corporation

James W Taylor

Ronald Eugene Stickney

David R Hampton

Cynthia P Jayne

Patricia O'Hearn

Paula Lank

Tae Hong Joo

Daniel Yerkovich

William Edward Crone

Richard C Nova

Joseph Leo Sullivan

Fred William Chapman

Robert G Walker

Isabelle L Banville

Patrick F Kelly

Steven E Sjoquist

Karl F Gauglitz

Stephen J Prosser

Lee R Mason

Srikanth Thiagrajan

G Michael Losh

Kenneth C Craig, Jr

The defibrillator may include a heart rhythm detector to detect the heart rhythm of a patient, a manual mode controller structured to set the defibrillator in a synchronous shock operating mode or an asynchronous shock operating mode depending on an input from a human operator, a shock module to cause the defibrillator to deliver a shock to the patient according to the operating mode, and an automatic mode controller structured to, after the shock module has delivered the shock to the patient, set the external defibrillator to the synchronous shock operating mode or the asynchronous shock operating mode depending on the detected heart rhythm of the patient and without input from the human operator.

Intelligent synch mode for defibrillation

Intelligent sync mode for defibrillation

Appropriate cardiac therapy is determined by data sensed and analyzed by the disclosed defibrillators and other medical devices that one or both of treat and monitor a patient. The disclosed devices sense various patient physiological parameters including patient pulse and breathing data to determine whether the patient has a pulse and to determine if the patient is breathing. Depending on the analysis of the generated patient physiological data, the disclosed devices determine the appropriate therapy for the patient, which can include providing breathing assistance to the patient and providing electrotherapy and other therapies to the patient. Some of the disclosed medical devices can be wearable by the patient. The disclosed devices can include therapy modules like electrotherapy for delivering therapies to the patient while other devices monitor but do not deliver the therapies to the patient.

Pulse detection apparatus, software, and methods using patient physiological signals

The presence of a cardiac pulse in a patient is determined by evaluating fluctuations in an electrical signal that represents a measurement of the patient's transthoracic impedance. Impedance signal data obtained from the patient is analyzed for a feature indicative of the presence of a cardiac pulse. Whether a cardiac pulse is present in the patient is determined based on the feature in the impedance signal data. Electrocardiogram (ECG) data may also be obtained in time coordination with the impedance signal data. Various applications for the pulse detection of the invention include detection of PEA and prompting PEA-specific therapy, prompting defibrillation therapy and/or CPR, and prompting rescue breathing depending on detection of respiration.

Pulse detection method and apparatus using patient impedance

A cardiac pulse in a patient is determined by evaluating physiological signals in the patient. A medical device evaluates two or more different physiological signals, such as phonocardiogram (PCG) signals, electrocardiogram (ECG) signals, patient impedance signals, piezoelectric signals, and accelerometer signals for features indicative of the presence of a cardiac pulse. Using these features, the medical device determines whether a cardiac pulse is present in the patient. The medical device may also be configured to report whether the patient is in a VF, VT, asystole, or PEA condition, in addition to being in a pulseless condition, and prompt different therapies, such as chest compressions, rescue breathing, defibrillation, and PEA-specific electrotherapy, depending on the analysis of the physiological signals. Auto-capture of a cardiac pulse using pacing stimuli is further provided. The medical devices, or any portion thereof, can be worn by the patient or may be attached to the patient.

An automated external defibrillator (AED) and methods for a corrective CPR prompting system. The AED includes a sensor that obtains compression measurement data of CPR chest compressions and a control system including a microprocessor programmed to run a non-parametric, Information-Theoretic analysis of the compression measurement data. The analysis includes ranking provided compression measurement data, determining a prompt time Tfor review, locating the compression measurement data at Tin an initial expected histogram of depth and rate aspects of the compression data measurements with upper and lower limits, that divides the intervals of the histogram into a plurality of sections, weighting the compression measurement data based on a plurality of factors, deriving information content of the compression measurement data by mapping a probability density function into an information content function, and determining if a particular corrective prompt is necessary. The AED also includes a prompting device that provides corrective CPR.

Corrective prompting system for appropriate chest compressions

An external defibrillator includes a therapy delivery circuit, a sensor, and a processor. The therapy delivery circuit is configured to be electrically charged and to deliver electrical therapy to a patient. The sensor is configured to sense a physiological condition of the patient and generate data indicative of a probability that therapy will be delivered to the patient. The processor is configured to analyze data generated by the sensor to determine whether there is a threshold level of the probability that the therapy delivery will be delivered to the patient, if the probability is at least at the threshold level, charge the therapy delivery circuit, and determine whether therapy delivery is advisable based on the physiological condition of the patient after determining whether the probability is at least at the threshold level.

External defibrillator with charge advisory algorithm

The presence of a cardiac pulse in a patient is determined by evaluating physiological signals in the patient. In one embodiment, a medical device evaluates two or more different physiological signals, such as phonocardiogram (PCG) signals, electrocardiogram (ECG) signals, patient impedance signals, piezoelectric signals, and accelerometer signals for features indicative of the presence of a cardiac pulse. Using these features, the medical device determines whether a cardiac pulse is present in the patient. The medical device may also be configured to report whether the patient is in a VF, VT, asystole, or PEA condition, in addition to being in a pulseless condition, and prompt different therapies, such as chest compressions, rescue breathing, defibrillation, and PEA-specific electrotherapy, depending on the analysis of the physiological signals. Auto-capture of a cardiac pulse using pacing stimuli is further provided.

A method of delivering electrical therapy to a patient by a medical device includes activating the medical device and performing a first analysis of a first set of data signals sensed by the medical device. If the first analysis shows the first set of data signals meets a first criterion, then charging of an energy delivery circuit is commenced upon completion of the first analysis. A second analysis of a second set of data signals from the patient is performed, and if the second analysis determines that the second set of data signals meet a second criterion, the therapy is delivered. The steps of performing the first analysis and performing the second analysis may be begun at substantially the same time. The step of charging may overlap in time with the step of performing a second analysis. The medical device may be an external defibrillator and the therapy may be a defibrillating shock.

A method and apparatus determines the presence of a cardiac pulse in a patient by evaluating a physiological signal in the patient, preferably for the presence of characteristic heart sounds. The presence of a heart sound in a patient is determined by analyzing phonocardiogram (PCG) data obtained from the patient. Analyzing the PCG data may include evaluating temporal energy in the PCG data or evaluating spectral energy in the PCG data. Evaluating temporal energy in the PCG data may include estimating a first and second energy in the PCG data and comparing the first and second energy to determine a relative change in energy between them. Evaluating spectral energy in the PCG data may include calculating an energy spectrum of the PCG data and evaluating either the energy value or the frequency of a peak energy in the energy spectrum. The presence of a heart sound may also be determined by combining an evaluation of temporal energy with an evaluation of spectral energy in the PCG data. Electrocardiogram data obtained from the patient may further be used in connection with the PCG data to determine the presence of a cardiac pulse in the patient. An automated external defibrillator processing the physiological signal sensed in the patient automatically reports to an operator of the defibrillator whether a cardiac pulse is determined to be present.

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Sammamish, WA, United States of America

James W Taylor