An electrode-equipped band includes a first band section and a second band section extending along a longitudinal direction. The second band section includes a first stretchable section, an electrode, a second stretchable section, a ring member, a fold-back section, and a joining section. The first stretchable section has first stretchability along the longitudinal direction. The electrode is provided on a first surface of the first stretchable section. The second stretchable section overlaps with the first stretchable section on a side of a second surface of the first stretchable section, and has second stretchability that allows greater stretch along the longitudinal direction than the first stretchable section. The ring member is provided at a position corresponding to a band end along the longitudinal direction of the second band section, and may be connected to the first band section.

A device for skin-contact biological measurement includes one or more electrodes to enable signal transmission through a skin contact and a control mechanism coupled to the one or more electrodes to adjust an electrode-to-skin impedance (ESI). The control mechanism is configured to implement the ESI adjustment using a thermal actuator.

A device for skin-contact biological measurement includes one or more electrodes to enable signal transmission through a skin contact and a control mechanism coupled to the one or more electrodes to adjust an electrode-to-skin impedance (ESI). The control mechanism is configured to implement the ESI adjustment using a thermal actuator.

Embodiments of a wearable monitoring device system can include one or more dry ECG electrodes and a processor that can be configured with one or more algorithms for detecting atrial fibrillation (AF) from sensed ECG signals sensed by the one or more dry ECG electrodes, and optionally other signals. In some embodiments the algorithms include one or more AF detection algorithms and optionally a noise detection algorithm. In some embodiments the wearable monitoring device or a remote system that receives data from the wearable medical device may calculate and/or characterize AF burden from ECG signals sensed by the one or more dry ECG electrodes.

Technologies and implementations for a wearable healthcare system including one or more electrodes, which may detect and determine smart leads off conditions of the one or more electrodes. The wearable healthcare system may include a leads off monitor module, which may be configured to learn when and when not to cause a leads off alert.

Technologies and implementations for a wearable healthcare system including one or more electrodes, which may detect and determine smart leads off conditions of the one or more electrodes. The wearable healthcare system may include a leads off monitor module, which may be configured to learn when and when not to cause a leads off alert.

A method of determining and treating disordered tissue in a patient incites energy signal generation from disordered tissue. An energy sensor structure obtains an energy signal from tissue of a patient. The obtained energy signal is compared in a processor circuit to a known energy signal of the same tissue under normal functioning of the tissue. The tissue is identified as disordered tissue when the comparing step determines that the obtained energy signal is different from the known energy signal. The disordered tissue is localized within the patient via the energy signal. A bodily disorder caused by the localized disordered tissue is diagnosed by an AI module. The bodily disorder is then treated.

A method of determining and treating disordered tissue in a patient incites energy signal generation from disordered tissue. An energy sensor structure obtains an energy signal from tissue of a patient. The obtained energy signal is compared in a processor circuit to a known energy signal of the same tissue under normal functioning of the tissue. The tissue is identified as disordered tissue when the comparing step determines that the obtained energy signal is different from the known energy signal. The disordered tissue is localized within the patient via the energy signal. A bodily disorder caused by the localized disordered tissue is diagnosed by an AI module. The bodily disorder is then treated.

A tissue disorder monitoring system includes at least two electrodes constructed and arranged to obtain analog electrical signals from a patient. An amplifier amplifies the analog electrical signals. Filter structure filters the amplified analog electrical signal. An A/D converter converts the amplified and filtered analog electrical signals to digitized electrical signals. A microprocessor circuit is constructed and arranged to execute an application that analyzes the digitized electrical signals to identify and to determine treatment data including a specific location and/or propagation of disordered tissue within the patient. A transmitter transmits data in a wireless manner. A power supply powers the device. A method locating disordered tissue in a patient is also disclosed.

A tissue disorder monitoring system includes at least two electrodes constructed and arranged to obtain analog electrical signals from a patient. An amplifier amplifies the analog electrical signals. Filter structure filters the amplified analog electrical signal. An A/D converter converts the amplified and filtered analog electrical signals to digitized electrical signals. A microprocessor circuit is constructed and arranged to execute an application that analyzes the digitized electrical signals to identify and to determine treatment data including a specific location and/or propagation of disordered tissue within the patient. A transmitter transmits data in a wireless manner. A power supply powers the device. A method locating disordered tissue in a patient is also disclosed.