Electrodes, multi-electrode patches, and electrodes for biomedical systems are provided. The electrode includes an adhesive film layer having a top surface and a bottom surface. A conductive element is substantially surrounded by the adhesive film layer. A conductive gel layer covers at least portion of a surface of the conductive element. The conducting gel comprises a material that does not result in significant skin irritation on a human subject after a period of at least about one week.

A device for the determination of at least one compression parameter during the administration of cardiopulmonary resuscitation (CPR) on a patient. The device includes a compression unit adapted to move in accordance with the chest of a patient and a surface unit adapted to move in accordance with a surface supporting the patient. The compression unit has one of a signal component and reference component, the surface unit has the other of the signal component and the reference component. The device also includes a processor configured to determine a relative measurement between the compression unit and the surface unit using data derived from the signal component and the reference component. The processor is further configured to determine the at least one compression parameter based on the relative measurement. The determined at least one compression parameter takes into account any motion and/or displacement of the surface.

A gel deployment device for use with an electrotherapy system is provided. The device includes a plurality of gel reservoirs disposed on a substrate, each of the plurality of gel reservoirs containing conductive gel. Each of the gel reservoirs are positioned adjacent to at least one seal such that the seal restricts flow of the conductive gel. The seal can be configured to release the conductive gel from the gel reservoir in response to pressure being applied about a perimeter of the seal at, for example, multiple points about the perimeter or substantially equally about the perimeter of the seal. In an example, each gel reservoir can be shaped such that the gel reservoir partially or fully surrounds a seal. In another example, multiple gel reservoirs can be arranged in clusters such that the multiple gel reservoirs are positioned about a single seal.

An envelope is comprised of two sheets of material that are placed one on top of each other with their interior sides facing each other with their edges sealed to each other with an adhesive to form an airtight enclosure. The envelope has at least one medical patch inside it that is attached to the interior side of at least one of the sheets and a layer of medical grade pressure sensitive adhesive surrounding the at least one medical patch. The pressure sensitive adhesive is applied to a part of the surface of the interior side of the sheet in order to attach the sheet of material and the at least one medical patch to the body of a patient. The medical patch can be an electrode for measuring a patient's vital signs or delivering an electric shock or a transdermal patch for delivering a drug to a patient.

A multi-axis defibrillator electrode band includes a stretchable band having a first end and a second end; and at least one pair of defibrillation electrodes embedded in the stretchable band between the first end and the second end, wherein a first electrode in the electrode pair is disposed opposite a second electrode in the electrode pair to define a conduction channel from the first electrode to the second electrode when the band is in a usage position for a defibrillation event.

Systems and methods related to the field of cardiac resuscitation, and in particular to devices for assisting rescuers in performing cardio-pulmonary resuscitation (CPR) are described herein.

A system including a medical device is provided. The medical device includes at least one sensor configured to acquire first data descriptive of a patient, first memory storing a plurality of templates, and at least one processor coupled to the at least one sensor and the first memory. The at least one processor is configured to identify a first template of the plurality of templates that is similar to the first data, to determine first difference data based on the first template and the first data, and to store the first difference data in association with the first template. The system may further include the programmable device.

Cardiac electrical activity is monitored from tissue of the patient using the plurality of external electrodes. One or more cardiac metrics of the patient are generated based on the monitored electrical activity. It is determined whether the patient is a candidate for a cardiac resynchronization therapy (CRT) device based on a first global dyssynchrony metric using the one or more cardiac metrics if the patient has a right bundle branch block. It is determined whether the patient is a candidate for a cardiac resynchronization therapy (CRT) device based on a second global dyssynchrony metric using the one or more cardiac metrics if the patient does not have a right bundle branch block.

A cardiac monitoring device includes: at least one sensing electrode for obtaining an electrocardiogram (ECG) signal from a patient; a processing unit comprising at least one processor operatively coupled to the at least one sensing electrode; and at least one non-transitory computer-readable medium comprising program instructions that, when executed by the at least one processor, causes the cardiac monitoring device to: obtain the ECG signal from the at least one sensing electrode; determine a transformed ECG signal based on the ECG signal; extract at least one value representing at least one feature of the transformed ECG signal; provide the at least one value to determine a score associated with the ECG signal, thereby providing an ECG-derived score; compare the ECG-derived score to a predetermined threshold score determined by machine learning; and provide an indication of a cardiac event if the ECG-derived score is one of above or below the predetermined threshold score determined by the machine learning.

Disclosed are embodiments directed to security methods applied to connections between components in a distributed (networked) system including medical and non-medical devices, providing secure authentication, authorization, patient and device data transfer, and patient data association and privacy for components of the system.