Abstract: Disclosed herein are techniques for implementing an intelligent assistance (“IA”) or extended intelligence (“EI”) ecosystem for soft tissue luminal applications. In various embodiments, a computing system analyzes first layer input data (indicating movement, position, and/or relative distance for a person(s) and object(s) in a room) and second layer input data. The second layer input data includes sensor and/or imaging data of a patient. Based on the analysis, the computing system generates one or more recommendations for guiding a medical professional in navigating a surgical device(s) with respect to one or more soft tissue luminal portions of the patient. The recommendation(s) include at least one mapped guide toward, in, and/or around the one or more soft tissue luminal portions. The mapped guide can include data corresponding to at least three dimensions, e.g., a 3D image/video. The computing system can present the recommendation(s) as image-based output, using a user experience device.

Abstract: Novel tools and techniques are provided for implementing intelligent assistance (“IA”) or extended intelligence (“EI”) ecosystem for pulmonary procedures. In various embodiments, a computing system might analyze received one or more first layer input data (i.e., room content-based data) and received one or more second layer input data (i.e., patient and/or tool-based data), and might generate one or more recommendations for guiding a medical professional in guiding a surgical device(s) toward and within a lung of the patient to perform a pulmonary procedure, based at least in part on the analysis, the generated one or more recommendations comprising 3D or 4D mapped guides toward, in, and around the lung of the patient. The computing system might then generate one or more XR images, based at least in part on the generated one or more recommendations, and might present the generated one or more XR images using a UX device.

Abstract: A nerve integrity monitoring device includes a control module and a physical layer module. The control module is configured to generate a payload request. The payload request (i) requests a data payload from a sensor in a wireless nerve integrity monitoring network, and (ii) indicates whether a stimulation probe device is to generate a stimulation pulse. The physical layer module is configured to (i) wirelessly transmit the payload request to the sensor and the stimulation probe device, or (ii) transmit the payload request to a console interface module. The physical layer module is also configured to, in response to the payload request, (i) receive the data payload from the sensor, and (ii) receive stimulation pulse information from the stimulation probe device. The data payload includes data corresponding to an evoked response of a patient. The evoked response is generated based on the stimulation pulse.

Abstract: In some examples, an apparatus configured to be worn by a patient for cardiac defibrillation comprises sensing electrodes configured to sense a cardiac signal of the patient, defibrillation electrodes, therapy delivery circuitry configured to deliver defibrillation therapy to the patient via the defibrillation electrodes, communication circuitry configured to receive data of at least one physiological signal of the patient from at least one sensing device separate from the apparatus, a memory configured to store the data, the cardiac signal, and a machine learning algorithm, and processing circuitry configured to apply the machine learning algorithm to the data and the cardiac signal to probabilistically-determine at least one state of the patient and determine whether to control delivery of the defibrillation therapy based on the at least one probabilistically-determined patient state.

Abstract: Apnea events may be detected based on a primary biomarker, e.g., respiration, in the one or more physiological signals. The apnea events may be characterized as one of an obstructive sleep apnea (OSA) event, a central sleep apnea (CSA) event, or a combination OSA/CSA event based on a secondary biomarker, e.g., a frequency spectrum or a morphology of the respirations in the one or more physiological signals. A first electrical stimulation may be provided to treat OSA in response to a first one or more of the apnea events being characterized as OSA events. A second electrical stimulation may be provided to treat CSA in response to a second one or more of apnea events being characterized as CSA events. A third electrical stimulation may be provided to treat combination OSA/CSA in response to a third one or more of the apnea events being characterized as combination OSA/CSA events.

Abstract: Disclosed is a system for stimulation of a subject. The stimulation may be to provide therapy to treat the subject. Stimulation may be of selected muscle groups and/or portions.

Abstract: An embodiment of a sensor device includes a base substrate, a circuit pattern formed overlying the interior surface of the substrate, a physiological characteristic sensor element on the exterior surface of the substrate, conductive plug elements located in vias formed through the substrate, each conductive plug element having one end coupled to a sensor electrode, and having another end coupled to the circuit pattern, a multilayer component stack carried on the substrate and connected to the circuit pattern, the stack including features and components to provide processing and wireless communication functionality for sensor data obtained in association with operation of the sensor device, and an enclosure structure coupled to the substrate to enclose the interior surface of the substrate, the circuit pattern, and the stack.

Abstract: A stimulation probe device including a first electrode, a stimulation module, a control module and a physical layer module. The stimulation module is configured to (i) wirelessly receive a payload signal from a console interface module or a nerve integrity monitoring device, and (ii) supply a voltage or an amount of current to the first electrode to stimulate a nerve or a muscle in a patient. The control module is configured to generate a parameter signal indicating the voltage or the amount of current supplied to the electrode. The physical layer module is configured to (i) upconvert the parameter signal to a first radio frequency signal, and (ii) wirelessly transmit the first radio frequency signal from the stimulation probe to the console interface module or the nerve integrity monitoring device.

Abstract: Apnea events may be detected based on a primary biomarker, e.g., respiration, in the one or more physiological signals. The apnea events may be characterized as one of an obstructive sleep apnea (OSA) event, a central sleep apnea (CSA) event, or a combination OSA/CSA event based on a secondary biomarker, e.g., a frequency spectrum or a morphology of the respirations in the one or more physiological signals. A first electrical stimulation may be provided to treat OSA in response to a first one or more of the apnea events being characterized as OSA events. A second electrical stimulation may be provided to treat CSA in response to a second one or more of apnea events being characterized as CSA events. A third electrical stimulation may be provided to treat combination OSA/CSA in response to a third one or more of the apnea events being characterized as combination OSA/CSA events.

Abstract: A method includes cutting a septal wall between a right atrium and left atrium of a heart of a patient to form a multi-cuspid valvular shunt, and ablating septal wall tissue of at least a portion of the multi-cuspid valvular shunt to cause the ablated portion of the multi-cuspid valvular shunt to be biostable.

Abstract: This disclosure is directed to systems and techniques for detecting change in patient health based upon patient data. In one example, a medical system comprising processing circuitry communicably coupled to a glucose sensor and configured to generate continuous glucose sensor measurements of a patient. The processing circuitry is further configured to: extract at least one feature from the continuous glucose sensor measurements over at least one time period, wherein the at least one feature comprises one or more of an amount of time within a pre-determined glucose level range, a number of hypoglycemia events, a number of hyperglycemia events, or one or more statistical metrics corresponding to the continuous glucose sensor measurements; apply a machine learning model to the at least one extracted feature to produce data indicative of a risk of a cardiovascular event; and generate output data based on the risk of the cardiovascular event.

Abstract: Novel tools and techniques are provided for implementing intelligent assistance (“IA”) or extended intelligence (“EI”) ecosystem to placement procedures for cardiac implantable electronic device (“CIED”). In various embodiments, a computing system might analyze received one or more first layer input data (i.e., room content-based data) and received one or more second layer input data (i.e., patient and/or tool-based data), and might generate one or more recommendations for guiding a medical professional in performing a CIED placement procedure in a heart of the patient, based at least in part on the analysis, the generated one or more recommendations comprising 3D or 4D mapped guides toward, in, and around the heart of the patient. The computing system might then generate one or more XR images, based at least in part on the generated one or more recommendations, and might present the generated one or more XR images using a UX device.

Abstract: An embodiment of a sensor device includes a base substrate, a circuit pattern formed overlying the interior surface of the substrate, a physiological characteristic sensor element on the exterior surface of the substrate, conductive plug elements located in vias formed through the substrate, each conductive plug element having one end coupled to a sensor electrode, and having another end coupled to the circuit pattern, a multilayer component stack carried on the substrate and connected to the circuit pattern, the stack including features and components to provide processing and wireless communication functionality for sensor data obtained in association with operation of the sensor device, and an enclosure structure coupled to the substrate to enclose the interior surface of the substrate, the circuit pattern, and the stack.

Abstract: Apnea events may be detected based on a primary biomarker, e.g., respiration, in the one or more physiological signals. The apnea events may be characterized as one of an obstructive sleep apnea (OSA) event, a central sleep apnea (CSA) event, or a combination OSA/CSA event based on a secondary biomarker, e.g., a frequency spectrum or a morphology of the respirations in the one or more physiological signals. A first electrical stimulation may be provided to treat OSA in response to a first one or more of the apnea events being characterized as OSA events. A second electrical stimulation may be provided to treat CSA in response to a second one or more of apnea events being characterized as CSA events. A third electrical stimulation may be provided to treat combination OSA/CSA in response to a third one or more of the apnea events being characterized as combination OSA/CSA events.

Abstract: A system comprises electrocardiogram sensing, glucose sensing circuitry, and processing circuitry. The sensing circuitry is configured to sense an electrocardiogram of a patient. The glucose sensing circuitry is configured to sense glucose levels of the patient. The processing circuitry configured to detect atrial fibrillation of the patient during a time unit based on the electrocardiogram of the patient, determine a first metric, wherein the first metric is associated with atrial fibrillation the patient experiences during the time unit, determine a second metric, wherein the second metric is associated with glucose levels of the patient during the time unit, and generate a health metric, wherein the health metric is determined based on the first and second metrics.

Abstract: A system comprises a memory, a plurality of electrodes, sensing circuitry, and processing circuitry. The sensing circuitry configured to determine one or more tissue impedance values via the electrodes, wherein the tissue impedance values vary as a function of ejection fraction of a heart of a patient. The processing circuitry configured to determine, at least based on the one or more tissue impedance values, a stroke metric indicative of a stroke status of the patient, and store the stroke metric in a memory.

Abstract: A method of implanting a lead includes inserting a needle through tissue near a chin of a patient and through a tongue of the patient, inserting an introducer through an opening created by the needle, and inserting the lead through the introducer, the lead comprising an elongated member and one or more electrodes in a distal portion of the elongated member such that the one or more electrodes are implantable proximate to one or more motor points of a protrusor muscle within the tongue of the patient, wherein inserting the lead comprises inserting the lead to have a shape of one of a helix, a compound helix, a wave shape, or saw-tooth shape, or to have a loop in the lead.

Abstract: A system for monitoring a patient includes one or more processors and a sensor device implemented in circuitry. The system is configured to measure, using the sensor device, an impedance of tissue of the patient and determine, using one or more processors, a physiological parameter comprising at least one of a heart rate, cardiac output, vascular tone, perfusion level, fluid status, respiration effort, or respiration rate of the patient based on the impedance of the tissue of the patient. The system is configured to facilitate therapy, using the one or more processors, based on the determined physiological parameter.

Abstract: A system for sleep apnea treatment includes an implantable medical device (IMD) coupled to a first lead and a second lead, wherein the IMD comprises a processor and stimulation circuitry, and wherein the processor is configured to cause the stimulation circuitry of IMD to: transmit a first stimulation signal to the first lead to stimulate at least one of an ansa cervicalis, a glossopharyngeal nerve, tensor veli, levator veli, and digastric anterior of a patient, and transmit a second stimulation signal to the second lead to stimulate at least one a hypoglossal nerve or a phrenic nerve of the patient.

Abstract: A lead for delivering electrical stimulation therapy is described. The lead includes an elongated member defining a longitudinal axis, one or more electrodes disposed at a distal end of the elongated member, a plurality of collars located along the longitudinal axis, and one or more fixation members. At least one of the fixation members is a bow-like member having a first connection point to a first collar of the plurality of collars and a second connection point to a second collar of the plurality of collars. The distal end of the elongated member is configured for insertion in a tongue of a patient such that the one or more electrodes are implanted proximate to one or more motor points of a protrusor muscle within the tongue of the patient and the bow-like member of the one or more fixation members is implanted within tissue of the tongue.