Abstract: Systems and methods for providing resuscitative chest compressions to a chest of a patient are described. One exemplary system may include a chest compressor for administering chest compressions to the patient, one or more sensors for measuring and generating electrocardiogram (ECG) signals of the patient's heart. The system may include at least one processor coupled to memory and configured to receive and analyze the signals corresponding to the ECG, determine an intrinsic heart rate, identify at least one ECG waveform within the ECG signals, select a chest compression protocol from at least three or at least four predetermined chest compression protocols for administration to the patient based at least in part on the intrinsic heart rate of the patient, and control the chest compressor based on the selected chest compression protocol.

Abstract: An external defibrillator is provided. The external defibrillator includes therapy delivery circuitry configured to discharge electrotherapy to a patient, a chest compression sensor configured to acquire motion signals during and after administration of CPR to the patient, an ECG sensor configured to acquire ECG signals from the patient, and a processor coupled to the therapy delivery circuitry, the chest compression sensor, and the ECG sensor. The processor is configured to generate first ECG data from ECG signals acquired during a cycle of CPR, generate second ECG data from ECG signals acquired after the cycle of CPR, identify a plurality of temporally overlapping segments in the first ECG data, determine shock/no-shock guidance based on the plurality of temporally overlapping segments, confirm the shock/no-shock guidance based on the second ECG data, and control the therapy delivery circuitry to discharge the electrotherapy where the shock/no-shock guidance is confirmed to specify electrotherapy.

Abstract: Methods and systems that analyze electrocardiogram (ECG) data to identify whether it would be beneficial for a caregiver to administer an electric shock to the heart in an effort to get the heart back into a normal pattern and a consistent, strong beat. By conducting a running check for conditions that are pre-validated by a comprehensive patient database to have high predictive value (e.g., with a low false-positive rate), a shockable rhythm can be identified fast (e.g., less than 6 seconds, less than 3 seconds, possibly in less than a second) and without having to analyze ECG data for longer time segments than would otherwise be required using conventional methods.

Abstract: Methods and systems that analyze electrocardiogram (ECG) data to identify whether it would be beneficial for a caregiver to administer an electric shock to the heart in an effort to get the heart back into a normal pattern and a consistent, strong beat. By conducting a running check for conditions that are pre-validated by a comprehensive patient database to have high predictive value (e.g., with a low false-positive rate), a shockable rhythm can be identified fast (e.g., less than 6 seconds, less than 3 seconds, possibly in less than a second) and without having to analyze ECG data for longer time segments than would otherwise be required using conventional methods.

Abstract: In an example implementation, a system includes one or more memory devices configured to store computer readable instructions, and a treatment adjustment engine that includes one or more processing devices. The treatment adjustment engine is configured to obtain a first image of an eye of a subject, and a second image of the eye of the subject. The second image is captured in the presence of an electronic light source. The treatment adjustment engine is further configured to determine, based on the first and second images, one or more metrics representing shapes of the iris and pupil in the corresponding images, and determine, based on the one or more metrics, a pupillometry measure of the subject. The treatment adjustment engine is also configured to generate a signal for adjusting a cardiopulmonary therapy based on the determined pupillometry measure.

Abstract: Systems and method for providing chest compressions to a patient during cardiopulmonary resuscitation may comprise at least one ECG sensor configured to obtain ECG signals, an automated chest compressor configured to provide chest compressions and at least one processor, memory and associated circuitry of a medical device communicatively coupled with the at least one ECG sensor and the automated chest compressor. The at least one processor may be configured to receive and analyze the ECG signals, determine, based on the analysis, whether the patient is in a condition of unconscious hypotension with organized ECG, analyze, in response to a determination that the patient is in the condition of unconscious hypotension with organized ECG, the received ECG signals to detect a QRS complex, and generate an output to apply a chest compression at a predetermined time relative to the detected QRS complex.

Abstract: Methods and systems that analyze electrocardiogram (ECG) data to identify whether it would be beneficial for a caregiver to administer an electric shock to the heart in an effort to get the heart back into a normal pattern and a consistent, strong beat. By conducting a running check for conditions that are pre-validated by a comprehensive patient database to have high predictive value (e.g., with a low false-positive rate), a shockable rhythm can be identified fast (e.g., less than 6 seconds, less than 3 seconds, possibly in less than a second) and without having to analyze ECG data for longer time segments than would otherwise be required using conventional methods.

Abstract: Methods and systems that analyze electrocardiogram (ECG) data to identify whether it would be beneficial for a caregiver to administer an electric shock to the heart in an effort to get the heart back into a normal pattern and a consistent, strong beat. By conducting a running check for conditions that are pre-validated by a comprehensive patient database to have high predictive value (e.g., with a low false-positive rate), a shockable rhythm can be identified fast (e.g., less than 6 seconds, less than 3 seconds, possibly in less than a second) and without having to analyze ECG data for longer time segments than would otherwise be required using conventional methods.

Abstract: In an example implementation, a system includes one or more memory devices configured to store computer readable instructions, and a treatment adjustment engine that includes one or more processing devices. The treatment adjustment engine is configured to obtain a first image of an eye of a subject, and a second image of the eye of the subject. The second image is captured in the presence of an electronic light source. The treatment adjustment engine is further configured to determine, based on the first and second images, one or more metrics representing shapes of the iris and pupil in the corresponding images, and determine, based on the one or more metrics, a pupillometry measure of the subject. The treatment adjustment engine is also configured to generate a signal for adjusting a cardiopulmonary therapy based on the determined pupillometry measure.

Abstract: Methods and systems that analyze electrocardiogram (ECG) data to identify whether it would be beneficial for a caregiver to administer an electric shock to the heart in an effort to get the heart back into a normal pattern and a consistent, strong beat. By conducting a running check for conditions that are pre-validated by a comprehensive patient database to have high predictive value (e.g., with a low false-positive rate), a shockable rhythm can be identified fast (e.g., less than 6 seconds, less than 3 seconds, possibly in less than a second) and without having to analyze ECG data for longer time segments than would otherwise be required using conventional methods.