In some examples, a system includes processing circuitry configured to generate a laser speckle contrast signal based on a received signal indicative of detected light, wherein the detected light is scatted by tissue from a coherent light source. The processing circuitry may also determine, from the laser speckle contrast signal, a flow value and determine, from the laser speckle contrast signal, a waveform metric. Based on the flow value and the waveform metric, the processing circuitry may determine a blood flow metric for the tissue and output a representation of the blood flow metric.

Catheterization of the heart is carried out by inserting a probe having electrodes into a heart of a living subject, recording a bipolar electrogram and a unipolar electrogram from one of the electrodes at a location in the heart, and defining a window of interest wherein a rate of change in a potential of the bipolar electrogram exceeds a predetermined value. An annotation is established in the unipolar electrogram, wherein the annotation denotes a maximum rate of change in a potential of the unipolar electrogram within the window of interest. A quality value is assigned to the annotation, and a 3-dimensional map is generated of a portion of the heart that includes the annotation and the quality value thereof.

Systems, devices and methods for monitoring analyte levels using a self-powered analyte sensor and associated sensor electronics are provided.

A device is described for interrogating human skin using tight coupling between the transmitter and receiver of the millimeter waves (MMWs). Methods are provided to evaluate changes in the amplitude and/or phase of the transmitted MMWs in order to estimate the blood concentration of glucose. Using this device and the related methods, the blood glucose concentration or a change in the blood glucose concentration can be monitored for diagnosing diabetes mellitus and other metabolic disorders of carbohydrate metabolism characterized by either high blood glucose level (hyperglycemia) or low blood glucose level (hypoglycemia), as well as for monitoring (including self-monitoring) a metabolic disorder progression or an efficacy of treatment.

The present disclosure relates to a device, method and system for calculating, estimating, or monitoring the blood pressure of a subject. At least one processor, when executing instructions, may perform one or more of the following operations. A first signal representing heart activity of the subject may be received. A second signal representing time-varying information on at least one pulse wave of the subject may be received. A first feature in the first signal may be identified. A second feature in the second signal may be identified. A pulse transit time based on a difference between the first feature and the second feature may be computed. The blood pressure of the subject may be calculated according to a first model based on the computed pulse transit time and a first set of calibration values, the first set of calibration values relating to the subject.

A photoplethysmographic (PPG) signal communicated by a PPG sensor of a wearable device worn by a user may be received by a processor. The processor may detect a plurality of heartbeats of the user from the PPG-signal, determine a heart rate of the user based on at least the plurality of heartbeats, determine a heart rate variability (HRV) based on the plurality of heartbeats, determine a respiration rate of the user based on a low frequency component of the PPG signal, and determine whether the user is in a stressed state based on the heart rate, the HRV, and the respiration rate. The processor may cause the display of information related to the stress state of the user, and instructions and/or advice for reducing a stress level of the user.

A multi-polar cannula having a cannula tube with a distal end and a proximal end and with a first electrode and at least one second electrode wherein the cannula tube has a cannula tube body and a layer that electrically insulates the first and second electrodes from each other, wherein the distal end of the cannula tube has a distal tip, wherein the first electrode is formed by the cannula tube body, and wherein the first electrode and the second electrode are connectable to a bioimpedance meter.

Provided in the embodiments of the present disclosure are a control method and device based on brain signal, and a human-machine interaction device, which periodically acquire EEG signals and cerebral oxygen signals within a target period, generate an electroencephalogram (EEG) wave curve representing changes of the EEG signals and a cerebral oxygen wave curve representing changes of the cerebral oxygen signals respectively within the target period, determine whether the EEG wave curve and the cerebral oxygen wave curve satisfy a condition for controlling a controlled device to perform a target operation, and control the controlled device to perform the target operation when the EEG wave curve and the cerebral oxygen wave curve satisfy the condition.

A technical solution is described for implementing a computer-executed signal processing algorithm to search for time domain segments of a recorded electroencephalogram (EEG) that are highly correlated, either positively or negatively, to one or more, individual, synthetically generated, single-period single-frequency (SPSF) sinusoids. The SPSFs are motivated by the combined concepts of individual Striatal Beat Frequencies (SBF) used to model cortical neuron activity, Frequency Domain Reflectometry used to study Voltage Standing Wave Ratios (VSWR), Geophysics Seismograms, and ghosting effects of multipath passing through periodic sinusoids. This computationally intense approach is only recently realizable through the advent of high performance computing. The SPSF approach, since it is not constrained to the error-laden one-window-fits-all approach of the Time-Frequency Spectrogram, offer's a more detailed basis to assess, and truer visualization of, the health of brain's electrical activities. This approach is a push-back against the Uncertainty Principal.

A pulse wave signal is registered and an occurrence of human limb movements detected during sleep using a pulse wave sensor and an accelerometer. The values of RR intervals and respiratory rate are measured at preset time intervals Δt.sub.i based on pulse wave signal. Mean P.sub.1, minimal P.sub.2, and maximal P.sub.3 values of RR intervals, the standard deviation of RR intervals P.sub.4, average respiratory rate P.sub.5 and average number of limb movements P.sub.6 are determined based on the above measured values. Function value F(Δt.sub.i) is determined thereafter as:
F(Δt.sub.i)=−K.sub.1P.sub.1−K.sub.2P.sub.2−K.sub.3P.sub.3+K.sub.4P.sub.4+K.sub.5P.sub.5+K.sub.6P.sub.6,
where K.sub.1-K.sub.6 are weight coefficients characterizing the contribution of the corresponding parameter to function value F(Δt.sub.i); whereat the onset and termination of sleep phase favorable to awakening is determined by increments of function F(Δt.sub.i).