A wearable biological signal measuring element is attached to a garment and detachably connected to a controller, the wearable biological signal measuring element including: an electrode in contact with skin; an electric line connected to the electrode; an electric connector connected to the electric line, penetrating the garment, and detachably connected to the controller outside the garment; and a water supply mechanism including a water guiding mechanism and a first water tank connected to an opening of the water guiding mechanism inside the garment and including a through hole in a contact surface with the electrode.

A catheter includes: (i) a shaft for insertion into an organ of a patient, (ii) an expandable distal-end assembly, which is coupled to the shaft and includes multiple splines, (iii) at least an ablation electrode, which is configured: (a) to be coupled to a spline of the splines, and (b) when placed in contact with tissue of the organ, to apply an ablation signal to the tissue, and the ablation electrode includes a slot, and (iv) a temperature sensor, which is contained within the slot and is configured, when the ablation electrode is placed in contact with the tissue, to produce a thermal signal indicative of a temperature of the tissue.

Systems, methods, and devices are described herein for evaluation, adjustment, and delivery of adaptive cardiac therapy. The systems, methods, and devices may utilize electrical heterogeneity information to determine and/or select one or more pacing settings and pacing type or configurations for a plurality of different heart rates. The adaptive cardiac therapy may deliver cardiac therapy at selected pacing settings such as, for example, A-V and/or V-V intervals, according to a presently measured heart rate and switch between left ventricular-only or biventricular cardiac pacing therapy also according to the presently measured heart rate.

Disclosed herein are systems and methods for neural interfaces. Neural interfaces may form minimally invasive and high-scalable bidirectional brain-computer interfaces, which may be used in the treatment of a variety of disorders of the brain and nervous system. Disclosed are methods for a minimally invasive technique for implanting neural interfaces, a neural interface configured to be placed between the brain and the dura and configured to record from and/or stimulate the cortical surface. Also disclosed are methods for attaching a plurality of microelectrode arrays to form a neural interface device, and fabricating neural interfaces including microelectrode arrays and pockets to facilitate their insertion. The disclosed systems and methods also include neural decoding techniques.

Disclosed herein are systems and methods for neural interfaces. Neural interfaces may form minimally invasive and high-scalable bidirectional brain-computer interfaces, which may be used in the treatment of a variety of disorders of the brain and nervous system. Disclosed are methods for a minimally invasive technique for implanting neural interfaces, a neural interface configured to be placed between the brain and the dura and configured to record from and/or stimulate the cortical surface. Also disclosed are methods for attaching a plurality of microelectrode arrays to form a neural interface device, and fabricating neural interfaces including microelectrode arrays and pockets to facilitate their insertion. The disclosed systems and methods also include neural decoding techniques.

A system for assisting a rescuer with treatment of a patient is described. An example system includes a mobile computing device that includes a user interface and a processor coupled to memory. The processor is configured to cause the user interface to prompt the rescuer to select a proficiency level from among multiple proficiency levels including a basic proficiency level and at least one non-basic proficiency level. The basic proficiency level includes basic resuscitation instructions for the rescuer. The system is further configured to receive an input from the rescuer of the selected proficiency level. The system provides, if the rescuer selects the basic proficiency level, the basic resuscitation instructions to the rescuer, and provides, if the rescuer selects the at least one non-basic proficiency level, non-basic instructions to the rescuer. The system transmits signals to control a defibrillator according to the selected proficiency level.

A system for assisting a rescuer with treatment of a patient is described. An example system includes a mobile computing device that includes a user interface and a processor coupled to memory. The processor is configured to cause the user interface to prompt the rescuer to select a proficiency level from among multiple proficiency levels including a basic proficiency level and at least one non-basic proficiency level. The basic proficiency level includes basic resuscitation instructions for the rescuer. The system is further configured to receive an input from the rescuer of the selected proficiency level. The system provides, if the rescuer selects the basic proficiency level, the basic resuscitation instructions to the rescuer, and provides, if the rescuer selects the at least one non-basic proficiency level, non-basic instructions to the rescuer. The system transmits signals to control a defibrillator according to the selected proficiency level.

The EKG cord management system is a cable management system. The EKG cord management system is configured for use with the leads of an EKG machine. The EKG cord management system comprises a plurality of lead structures, a probe connector, and a housing. The EKG cord management system deploys the plurality of lead structures from the housing. The EKG cord management system retracts the plurality of lead structures into the housing. Each lead structure selected from the plurality of lead structures measures electrical activity in a human body. The probe connector electrically connects each of the plurality of lead structures to a machine known as an EKG machine.

An apparatus for estimating bio-information includes: an impedance sensor including a pair of input electrodes and a pair of receiving electrodes, and configured to measure bio-impedance of a user by applying a current to the pair of input electrodes and by measuring a voltage between the pair of receiving electrodes; and a processor configured to estimate bio-information by applying, to the measured bio-impedance, an estimation model that uses a correlation between the measured bio-impedance and the bio-information to be estimated.

An apparatus for estimating bio-information includes: an impedance sensor including a pair of input electrodes and a pair of receiving electrodes, and configured to measure bio-impedance of a user by applying a current to the pair of input electrodes and by measuring a voltage between the pair of receiving electrodes; and a processor configured to estimate bio-information by applying, to the measured bio-impedance, an estimation model that uses a correlation between the measured bio-impedance and the bio-information to be estimated.