Abstract: A system comprises a sensor device and processing circuitry. The sensor device comprises a housing configured to be disposed above shoulders of a patient, a plurality of electrodes on the housing, a motion sensor, and sensing circuitry configured to sense a brain electrical signal and a cardiac electrical signal via the electrodes, and a motion signal via the motion sensor. The processing circuitry is configured to determine values over time of one or more parameters from the brain electrical signal, determine values over time of one or more parameters from the cardiac electrical signal, and generate at least one of a detection, prediction, or a classification a condition of the patient based on the values and the motion signal.

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: A system comprises processing circuitry and memory comprising program instructions that, when executed by the processing circuitry, cause the processing circuitry to: apply a first set of rules to first patient parameter data for a first determination of whether sudden cardiac arrest of a patient is detected; determine that a one or more context criteria of the first determination are satisfied; and in response to satisfaction of the context criteria, apply a second set of rules to second patient parameter data for a second determination of whether sudden cardiac arrest of the patient is detected. At least the second set of rules comprises a machine learning model, and the second patient parameter data comprises at least one patient parameter that is not included in the first patient parameter data.

Abstract: Devices, systems, and techniques for detecting a sudden cardiac event based on respiratory parameter information. A method includes receiving periodic respiratory parameter information, where the respiratory parameter information includes respiratory effort of a patient; and determining, by the processing circuitry and based on the respiratory parameter information, whether a sudden cardiac arrest of the patient is detected.

Abstract: A device comprising a computer-readable medium having executable instructions stored thereon, configured to be executable by processing circuitry for causing the processing circuitry to: determine that a patient is experiencing or has experienced an acute health event; cause a motor to move a robotic device to a location proximate the patient; cause a sensor of the robotic device to gather physiological data from the patient; confirm that the patient is experiencing or has experienced the acute health event based on the physiological data; and generate an output in response to confirming that the patient is experiencing or has experienced the acute health event.

Abstract: Devices, systems, and techniques are disclosed for verifying the occurrence of an acute health event. An example device includes communication circuitry configured to receive a communication indicative of an acute health event of a patient and memory communicatively coupled to the communication circuitry and being configured to store the indication of the acute health event. The device includes processing circuitry communicatively coupled to the communication circuitry and the memory. The processing circuitry is configured to, in response to the communication, verify the acute health event and based on the verification of the acute health event, send an alert regarding the acute health event.

Abstract: Example devices, systems, and techniques are disclosed for providing guidance of a treatment of a patient. An example device includes processing circuitry and memory comprising instructions that, when executed by the processing circuitry, cause the processing circuitry to determine that a device detected an acute health event of a patient or delivery of cardiopulmonary resuscitation to the patient, and analyze sensed patient data in response to the determination. The instructions cause the processing circuitry to provide information for guidance of a treatment of the patient based on the analysis.

Abstract: A system comprising processing circuitry configured to receive a wirelessly-transmitted message from a medical device, the message indicating that the medical device detected an acute health event of the patient. In response to the message, the processing circuitry is configured to determine a location of the patient, determine an alert area based on the location of the patient, and control transmission of an alert of the acute heath event of the patient to any one or more computing devices of one or more potential responders within the alert area.

Abstract: An example device of a patient includes an antenna configured to wirelessly receive communication from a medical device; and processing circuitry coupled to the antenna and configured to: determine that the received communication indicates that a patient is experiencing an acute health event; in response to the determination, determine one or more physical states of the patient based on sensed data from one or more sensors; confirm that the patient is not experiencing the acute health event based on the determined one or more physical states; and output information based on the confirmation that the patient is not experiencing the acute health event.

Abstract: An example device of a patient includes an antenna configured to wirelessly receive communication from a medical device; and processing circuitry coupled to the antenna and configured to: determine that the received communication indicates that a patient is experiencing an acute health event; in response to the determination, determine one or more physical states of the patient based on sensed data from one or more sensors; confirm that the patient is not experiencing the acute health event based on the determined one or more physical states; and output information based on the confirmation that the patient is not experiencing the acute health event.

Abstract: A system coupled to a non-human subject comprising communication circuitry configured to communicatively couple to a medical device coupled to the subject and a remote computing system, the medical device configured to monitor physiological data of the non-human subject and the remote computing system configured to store historical data for the non-human subject; processing circuitry; and a memory comprising instructions that, when executed by the processing circuitry, cause the processing circuitry to: receive the monitored physiological data from the medical device; determine whether the medical device indicates that the monitored physiological data is in satisfaction of at least one condition triggering an upload of at least a portion of the monitored physiological data; and in response to the determination, generate, for communication to the remote computing system, output data comprising the at least a portion of the monitored physiological data.

Abstract: A system comprises processing circuitry and memory comprising program instructions that, when executed by the processing circuitry, cause the processing circuitry to: apply a first set of rules to first patient parameter data for a first determination of whether sudden cardiac arrest of a patient is detected; determine that a one or more context criteria of the first determination are satisfied; and in response to satisfaction of the context criteria, apply a second set of rules to second patient parameter data for a second determination of whether sudden cardiac arrest of the patient is detected. At least the second set of rules comprises a machine learning model, and the second patient parameter data comprises at least one patient parameter that is not included in the first patient parameter data.

Abstract: A system comprising processing circuitry configured to receive a wirelessly-transmitted message from a medical device, the message indicating that the medical device detected an acute health event of the patient. In response to the message, the processing circuitry is configured to determine a location of the patient, determine an alert area based on the location of the patient, and control transmission of an alert of the acute heath event of the patient to any one or more computing devices of one or more potential responders within the alert area.

Abstract: An example device of a patient includes an antenna configured to wirelessly receive communication from a medical device; and processing circuitry coupled to the antenna and configured to: determine that the received communication indicates that a patient is experiencing an acute health event; in response to the determination, determine one or more physical states of the patient based on sensed data from one or more sensors; confirm that the patient is not experiencing the acute health event based on the determined one or more physical states; and output information based on the confirmation that the patient is not experiencing the acute health event.

Abstract: A system comprises a sensor device and processing circuitry. The sensor device comprises a housing configured to be disposed above shoulders of a patient, a plurality of electrodes on the housing, a motion sensor, and sensing circuitry configured to sense a brain electrical signal and a cardiac electrical signal via the electrodes, and a motion signal via the motion sensor. The processing circuitry is configured to determine values over time of one or more parameters from the brain electrical signal, determine values over time of one or more parameters from the cardiac electrical signal, and generate at least one of a detection, prediction, or a classification a condition of the patient based on the values and the motion signal.

Abstract: In some examples, a device includes at least three electrodes a first pair of electrodes and a second pair of electrodes. The device also includes circuitry configured to generate a first cardiac signal based on a first differential signal received across the first pair, generate a first brain signal based on the first differential signal received across the first pair, generate a second cardiac signal based on a second differential signal received across the second pair, and generate a second brain signal based on the second differential signal received across the second pair. The circuitry is also configured to output a composite cardiac signal based on the first cardiac signal and the second cardiac signal and to output a composite brain signal based on the first brain signal and the second brain signal.

Abstract: A system for detecting strokes includes a sensor device configured to obtain physiological data from a patient, for example brain activity data. The sensor device can include electrodes configured to be disposed at the back of the patient's neck or base of the skull. The electrodes can detect electrical signals corresponding to brain activity in the P3, Pz, and/or P4 brain regions or other brain regions. A computing device communicatively coupled to the sensor device is configured to receive the physiological data and analyze it to indicate whether the patient has suffered a stroke.

Abstract: A system for detecting strokes includes a sensor device configured to obtain physiological data from a patient, for example brain activity data. The sensor device can include electrodes configured to be disposed at the back of the patient's neck or base of the skull. The electrodes can detect electrical signals corresponding to brain activity in the P3, Pz, and/or P4 brain regions or other brain regions. A computing device communicatively coupled to the sensor device is configured to receive the physiological data and analyze it to indicate whether the patient has suffered a stroke.

Abstract: In some examples, an electromechanical disassociation state (EMD) of a heart of a patient can be treated by delivering electrical stimulation to a tissue site to at least one of modulate afferent nerve activity or inhibit efferent nerve activity upon determining that the heart is in an electromechanical dissociation state, where the tissue site comprises at least one of a nonmyocardial tissue site or a nonvascular cardiac tissue site. The delivery of electrical stimulation may effectively treat the EMD state of the heart, e.g., by enabling effective mechanical contraction of the heart. In another example, an electromechanical disassociation state of a heart of a patient can be treated by determining autonomic nervous system activity associated with a detected EMD state of the heart of a patient, and delivering electrical stimulation therapy to the patient based on the determined autonomic nervous system activity of the patient associated with the EMD state.

Abstract: Electrical crosstalk between two implantable medical devices or two different therapy modules of a common implantable medical device may be evaluated, and, in some examples, mitigated. In some examples, one of the implantable medical devices or therapy modules delivers electrical stimulation to a nonmyocardial tissue site or a nonvascular cardiac tissue site, and the other implantable medical device or therapy module delivers cardiac rhythm management therapy to a heart of the patient.