Provided is an apparatus configured to estimate bio-information, the apparatus including a pulse wave sensor including a plurality of channels disposed in an isotropic shape, a force sensor configured to measure a force applied by an object to the pulse wave sensor, and a processor configured to detect a center of gravity based on pressure, applied by the object, in a space formed by the plurality of channels based on pulse wave signals measured by each of the plurality of channels included in the pulse wave sensor, provide a user with guide information with respect to contact of the object to the pulse wave sensor based on the detected center of gravity, and estimate bio-information based on the pulse wave signals and the force which are measured based on the guide information.

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.

Disclosed herein is a physiological measurement system that can automatically adjust the number of wavelengths used based on the quality of a sensor signal that is reflective of an optical radiation detected at a sensor after tissue attenuation. The signal quality is examined to determine if it is sufficient to support the use of a full set of wavelengths. If it is determined to be insufficient to support the full set, a reduced number of wavelengths is used.

Methods, apparatus, and systems relating to a Wearable Cardioverter Defibrillator (WCD) system capable of logging event data and/or broadcasting state changes and/or system status information to external clients are described. In an embodiment, a processor stores data corresponding to one or more event markers in memory in response to occurrence of an event. Occurrence of the event is detected based at least in part on detection of one or more parameters by one or more sensors or a signal to be generated by one or more of electrodes of the WCD system. A communication device transmits at least a portion of the stored data to a remote device. A patient condition or a WCD system condition can then be detected based at least in part on analysis of the stored data and/or the transmitted portion of the stored data.

Methods and arrangements are described for developing a virtual channel matrix for mapping analysis channels to stimulation channels for a cochlear implant patient by selecting a stimulation channel and measuring the amplitude growth function for the selected stimulation channel in response to commands to the cochlear implant to apply electrical stimulation pulses for the stimulation channel, where each stimulation pulse comprises a negative and a positive phase separated in time by a first inter-phase-gap; and measuring the amplitude growth function for the selected stimulation channel in response to commands to the cochlear implant to apply electrical stimulation pulses for the stimulation channel, where each stimulation pulse comprises a negative and positive phase separated in time by a second inter-phase-gap and whereby the first and second inter-phase-gaps are different. Thereafter Determining the slopes of the measured amplitude growth functions for the stimulation channel measured with the first and second inter-phase-gaps, and calculating an indicator based at least in part on the difference of the slopes of the amplitude growth functions indicative of the local neural survival for that stimulation channel. Thereafter Repeating this process for each stimulation channel where an indicator shall be derived and selecting for the virtual channel matrix the stimulation channels with best local neural survival by optimizing a function based at least in part on the calculated indicators of the stimulation channels.

A method and an apparatus for establishing absence of pain in a human or other mammal have been disclosed. The method comprises the steps of providing a skin conductance signal measured at an area of the mammal's skin through a time interval; detecting peaks in the skin conductance signal through said time interval; determining a rate of the peaks through the time interval; comparing the determined rate of peaks with a predetermined reference value; and if the measured rate of peaks is lower than the predetermined reference value, providing an output signal as indicating the state of absence of pain in the mammal.

Described herein are methods, devices and system for determining whether an R-wave detection should be classified as a false R-wave detection due to T-wave oversensing (TWO) or P-wave oversensing (PWO). One such method includes comparing a specific morphological characteristic (e.g., peak amplitude) associated with the R-wave detection to the specific morphological characteristic associated with each R-wave detection in a first set of earlier detected R-wave detections to thereby determine whether first TWO or PWO morphological criteria are met, and in a second set of earlier detected R-wave detections to thereby determine whether second TWO or PWO morphological criteria are met, wherein the second set differs from the first set but may have some overlap with the first set. The method also includes determining whether to classify the R-wave detection as a false R-wave detection, based on whether one of the first or second TWO or PWO morphological criteria are met.

An electronic device is provided. The electronic device includes a display, a communication circuit, and at least one processor configured to recognize a user's initial posture based on at least one of motion sensor signals of a first external electronic device and a second external electronic device received through the communication circuit, control the first external electronic device to receive a first motion sensor signal, obtain the user's workout data based on the first motion sensor signal when the initial posture satisfies a designated condition, control the second external electronic device to receive a second motion sensor signal when the user's movement is not recognized based on the first motion sensor signal and obtain the user's workout data based on the second motion sensor signal, and provide the workout data through at least one of the display or the first external electronic device.

A medical device includes at least one electrode to sense an electrocardiogram (ECG) signal of a patient, and a controller coupled to the at least one electrode. The controller is configured to generate a first ECG template based on a first ECG signal of the patient received during a first baselining operation. The controller is configured to determine that the patient has been administered a therapeutic shock, and responsive to the determination that the patient has been administered the therapeutic shock, the controller is configured to initiate a second baselining operation and generate a second ECG template based on a second ECG signal of the patient received during the second baselining operation. The controller is configured to determine whether the patient is experiencing a cardiac event based on a comparison of the second ECG template to a real time ECG signal received during real time monitoring of the patient.

When evaluating the quality of photoplethysmography (PPG) signal (52) measured from a patient monitor (e.g., a finger sensor or the like), multiple features of the PPG signal are extracted and analyzed to facilitate assigning a score to the PPG signal or portions (e.g., heartbeats) thereof. Heartbeats in the PPG signal are segmented out using concurrently captured electrocardiograph (ECG) signal (50), and for each heartbeat, a plurality of extracted features are analyzed. If all extracted features satisfy one or more predetermined criteria for each feature, then the heartbeat waveform is compared to a predefined heartbeat template. If the waveform matches the template (e.g., within a predetermined match percentage or the like), then the heartbeat is classified as “clean.” If the heartbeat does not patch the template, or if one or more of the extracted features fails to satisfy its one or more pre-determined criteria, the heartbeat is classified as “noisy.”