A wearable device is provided. The wearable device includes a first sensor having a light-emitting part and a light-receiving part, a second sensor having at least one electrode, and at least one processor electrically connected to the first sensor and the second sensor, wherein the at least one processor acquires PPG signal data by using the first sensor for a first time while the wearable device is worn on a user's body, acquires ECG signal data by using the second sensor for the first time for which the PPG signal is acquired, determines an inter-beat interval calculation model, based on the result of a comparison between the PPG signal data and the ECG signal data, and acquires, based on the determined inter-beat interval calculation model, an inter-beat interval of the user from PPG signal data measured for a second time after the first time.

In some examples, a method includes receiving a signal indicative of a blood pressure of a patient and identifying at least one first portion of the signal comprising a first characteristic of the signal exceeding a first threshold. The method also includes identifying at least one first portion of the signal comprising a second characteristic of the signal exceeding a second threshold, the first characteristic being different than the second characteristic. The method further includes determining a filtered signal indicative of the blood pressure of the patient by excluding the at least one first portion and the at least one second portion from the signal. The method includes determining a set of mean arterial pressure values based on the filtered signal and determining an autoregulation status of the patient based on the set of mean arterial pressure values.

Various embodiment disclosed herein include a method for monitoring serum potassium in a patient. The method can include gathering cardiac electrogram data from the patient using two or more electrodes, separating the cardiac electrogram data into discrete subunits including a T-wave, aligning T-waves to create aligned discrete subunits, averaging the aligned discrete subunits to generate an average T-wave for the cardiac electrogram data, and determining a serum potassium value using the average T-wave for the cardiac electrogram data and a predetermined model relating T-wave values with serum potassium magnitudes.

The present invention relates to systems and methods to measure, compute, and predict blood pressure. More specifically, the invention generally relates to systems, methods, and process for predicting blood pressure from respiratory, circulatory, acoustic, hemodynamic, movement and blood flow characteristics and metrics.

Disclosed herein is a device for continuous physiological monitoring as well as systems and methods for interpreting data from such a device. The systems and methods may include automatically detecting, assessing, and analyzing exercise activity, physical recovery states, sleep states, and the like. The acquisition of continuous physiological data may facilitate automated recommendations concerning changes to sleep, recovery time, exercise routines, and the like.

An OCT apparatus and method for characterization of a fluid adjacent to a tympanic membrane has a low coherence source which is coupled to a splitter which has a measurement path and a reference path. The reference path is temporally modulated for length, and the combined signals from the reference path and the measurement path are applied to a detector. The detector examines the width of the response and the time variation when an optional excitation source is applied to the tympanic membrane, the width of the response and the time variation forming a metric indicating the viscosity of a fluid adjacent to the tympanic membrane being measured.

A non-invasive method and system is provided for determining an internal component of respiratory effort of a subject in a respiratory study. Both a thoracic signal (T) and an abdomen signal (A) are obtained, which are indicators of a thoracic component and an abdominal component of the respiratory effort, respectively. A first parameter of a respiratory model is determined from the obtained thoracic signal (T) and the abdomen signal (A). The first parameter is an estimated parameter of the respiratory model that is not directly measured during the study. The internal component of the respiratory effort is determined based at least on the determined first parameter of the respiratory model. The first model parameter is determined based on the thorax signal (T) and the obtained abdomen signal (A) without an invasive measurement.

A process and signal processing unit (5) determine a cardiogenic signal (Sig.sub.kar,est) or a respiratory signal (Sig.sub.res,est) from a sum signal (Sig.sub.Sum), resulting from a superimposition of cardiac activity and breathing of a patient (P). A signal estimating unit (6), which yields a shape parameter as a value of a transmission channel parameter (LF), is generated during a training phase. A sample with a sample element per heartbeat is used. During a use phase, the transmission channel parameter is measured for each heartbeat, a shape parameter value is calculated by the application of the signal estimating unit and is used to calculate an estimated cardiogenic signal segment (Sig.sub.Hz,kar.LF) or an estimated respiratory signal segment. The cardiogenic signal segments are combined into the cardiogenic signal or the respiratory signal segments are combined into the respiratory signal or the cardiogenic signal segments are subtracted from the sum signal.

Embodiments of devices and methods for evaluating tissue are disclosed. In one embodiment, a method for measuring a characteristic of a tissue may include passing a current through the tissue, measuring a signal corresponding to the voltage resulting from passing the current through the tissue, analyzing current passed through the tissue and resulting voltage to determine the electrical characteristics of the tissue; and analyzing the electrical characteristics of the tissue to determine a status of the tissue. Methods for achieving relatively constant sensor application pressure are disclosed.

In part, the disclosure relates to computer-based methods, devices, and systems suitable for performing intravascular data analysis and measurement of various types of data such as pressure and flow data. The disclosure relates to probes and methods suitable for determining an event in a cardiac cycle such as flow threshold such as a peak flow, a fraction thereof, other intravascular parameters or a point in time during which peak flow or a change in one of the perimeters occurs. An exemplary probe includes one or more of a pressure sensor, a resistor, a flow sensor and can be used to generate diagnostic data based upon measured intravascular and other parameters. In part, the disclosure relates to methods and systems suitable for determining a coronary flow reserve value in response to one or more of intravascular pressure and flow data or data otherwise correlated therewith.