The present invention relates to the field of biomedical signal processing, specifically, a device and method of implementation for enhancing the accuracy of fetal heart rate acceleration data recognition. The present invention comprises: collecting fetal heart rate data in a pre-configured period so as to obtain a fetal heart rate data sequence, H(n); performing baseline identification on the fetal heart rate sequence, H(n), to obtain a fetal heart rate baseline data sequence, B(n); pre-processing the fetal heart rate data sequence, H(n), to obtain a pre-processed fetal heart rate data sequence, C(n); performing acceleration recognition on the pre-processed fetal heart rate data sequence, C(n), according to pre-configured acceleration determination criteria and the fetal heart rate baseline data sequence, B(n), to obtain acceleration data segments; calculating an acceleration attribute value for each of the acceleration data segments, and outputting each acceleration data segment and the acceleration attribute value calculation result thereof. The technical solution provided by the present invention effectively distinguishes the variations between the accelerations and the baseline, accurately recognizes each acceleration in continuous accelerations, and avoids the situations of the detected number of fetal heart rate data accelerations being lower than the actual number or being mistaken due to current methods, thereby enhancing the accuracy in recognizing fetal heart rate curve accelerations.

Certain examples provide systems and methods to enhance slow wave sleep. An example method includes identifying a sleep stage for slow wave sleep in a subject being monitored. The example method also includes generating, following identification of slow wave sleep and using a processor including a phase locked loop, an output signal based on a phase of a reference input signal, the output signal phase locked according to the reference input signal. The example method includes delivering, during slow wave sleep for the subject, a stimulus to the subject based on the phase locked output signal. The delivering includes providing the stimulus in a series of signal pulses for a first period of time; and providing a refractory period without pulses in a second period of time. The method further includes measuring feedback from the stimulus.

An oximeter probe includes a probe unit or a base unit and a probe tip where the probe tip has a number of sources and detectors that can be accessed individually or in differing combinations for measuring tissue oxygen saturation at different tissue depth in tissue. A processor of the oximeter probe controls a multiplexer that is coupled to the detectors for selectively collecting measurement information from the detectors via the multiplexer. The oximeter probe is user programmable via one or more input devices on the oximeter probe for selecting the particular sources and detectors to collect measurement information from by the processor.

A method for noninvasive analysis of subcutaneous tissue includes irradiating a surface of the tissue with short wave infrared (SWIR) radiation in a first spectral band that is strongly absorbed by water, and with SWIR radiation in a second spectral band such that an interaction of the radiation in both spectral bands with a component of the tissue other than water is substantially identical. An intensity of the radiation in each of the spectral bands that emerges from the tissue is measured. A relative absorption by the tissue of radiation in one of spectral bands relative to absorption by the tissue of radiation in the other of the spectral bands is calculated. A state of the tissue is determined in accordance with the calculated relative absorption.

Systems, devices and methods for noninvasive analysis of tissue, by irradiating a surface of the tissue with infrared radiation such that an interaction of the radiation with a component of the tissue other than water in two spectral bands is substantially identical, measuring an intensity of the radiation that emerges from the tissue in each of the spectral bands, determining change in at least one of shape and intensity of signals received by the at least one radiation detector, calculating a relative absorption by the tissue of radiation in one of the first and second spectral bands relative to absorption by the tissue of radiation in the other of the first and second spectral bands, and determining concentration of a predetermined substance, in accordance with the calculated relative absorption and in accordance with determined change in the received signal.

An apparatus for estimating biometric information is provided. According to one exemplary embodiment, the apparatus may include a sensor comprising an electrocardiogram (ECG) sensor configured to measure an ECG signal of a user and a pulse wave sensor configured to measure two or more pulse wave signals at two or more measurement sites of the user; and a processor configured to obtain biometric information based on the ECG signal and the two or more pulse wave signals measured by the sensor.

The methods and apparatuses presented herein determine and/or improve the quality of one or more physiological assessment parameters, e.g., response-recovery rate, based on biometric signal(s) and/or motion signal(s) respectively output by one or more biometric and/or motion sensors. The disclosed methods and apparatuses also estimate a user's stride length based on a motion signal and a determined type of user motion, e.g., walking or running. The speed of the user may then be estimated based on the estimated stride length.

Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.

According to an aspect there is provided a method of obtaining a measurement of the blood pressure of a subject using a non-invasive blood pressure, NIBP, monitor and including using a pulse rate sensor and a cuff that is to be placed around a limb of the subject, the method comprising using the pulse rate sensor to obtain information on the pulse rate of the subject; adapting a pressure signal filter according to the obtained information on the pulse rate of the subject; starting inflation of the cuff; obtaining a pressure signal representing the pressure in the cuff as the cuff is inflated; filtering the pressure signal using the adapted pressure signal filter during inflation of the cuff; and processing the filtered pressure signal to obtain a blood pressure measurement for the subject during inflation of the cuff.

A computer-implemented method of heart rate estimation includes receiving heart beat data, detecting sequential beats within the heart beat data, identifying a beat interval of each sequential beat, and generating a beat array containing the beat intervals of sequential beats within an array window. The beat array is then sorted based on the beat intervals of the sequential beats so as to generate a sorted beat array. A weight array is calculated by applying a weight control parameter to each beat interval in the sorted beat array, wherein the weight array includes a weight value for each beat interval that is proportional to a corresponding beat interval value in the sorted beat array. A weighted median is calculated based on the weight array, and a heart rate estimation for the array window is determined based on the weighted median of the weight array and the sorted beat array.