175 results about "Fetal Heart Rate Variability" patented technology

Method and apparatus for determining the state of entrainment between biological systems which exhibit oscillatory behavior such as heart rhythms, respiration, blood pressure waves and low frequency brain waves based on a determination of heart rate variability (HRV) and an evaluation of the power spectrum thereof. Entrainment reflects a harmonious balance between the two branches of the autonomic nervous system within the body. This internal state of heightened physiological efficiency enhances health and promotes optimal performance. According to one embodiment a method is used to determine the entrainment level based on an entrainment parameter related to HRV. The method first determines the power distribution spectrum (PSD) and then calculates an entrainment parameter (EP), which is a measure of the power distribution in the HRV spectrum. High EP values occur when this power is concentrated within a relatively narrow range of frequencies, and lower values when the power is distributed over a broader range of frequencies. In one embodiment, an apparatus is provided for monitoring the heart beat and presenting this information via a personal computer, handheld device, or other processing means.

The present invention describes a method of tracking minute ventilation from R-R intervals that are based on the acquisition of ECG signal. Sub-methods (RDF1), which are mainly based on heart rate variability, are used, wherein the respiratory frequency is determined from a pattern of rhythmic changes in heart beat data. The sub-methods (RDF1-n) are combined using an expert function, wherein each sub-method (RDF1-n) determines an estimate of the respiratory frequency.

Described herein are fetal and / or maternal monitoring devices, systems and methods using UWB medical radar. These devices and systems may include a UWB sensor providing high-resolution and reliable simultaneous monitoring of multiple indicators of fetal and / or maternal health, such as fetal heart rate, fetal heart rate variability, fetal respiration, fetal gross body movement, maternal contractions, maternal heart rate, maternal respiration, and other derivative parameters during virtually all stages of pregnancy and during delivery. The sensor allows novel collection of physiological data using a single sensor or multiple sensors to develop individual and aggregate normal motion indices for use in determining when departure from normal motion index is indicative of fetal or maternal distress.

A method of operating a baroreflex therapy system includes providing an implantable baroreflex activation device, providing a sensing arrangement, and providing a controller in operable communication with the baroreflex activation device and the sensing arrangement. The sensing arrangement is used to measure a physical parameter of a patient to generate physical parameter data. The physical parameter data is communicated to the controller, wherein the controller performs heart rate variability analysis based on the physical parameter data. An indication of results of the heart rate variability analysis are provided, upon which a determination may be made to adjust a baroreflex therapy to be delivered by the implantable baroreflex activation device.

An improved sensor (102) for hydration monitoring in mobile devices, wearables, security, illumination, photography, and other devices and systems uses an optional phosphor-coated broadband white LED (103) to produce broadband light (114), which is then transmitted along with any ambient light to target (125) such as the ear, face, or wrist of a living subject. Some of the scattered light returning from the target to detector (141) is passed through a narrowband spectral filter set (155) to produce multiple detector regions, each sensitive to a different waveband wavelength range, and the detected light is spectrally analyzed to determine a measure of hydration, such as fluid losses, fluid ingested, fluid balance, or rate of fluid loss, in part based on a noninvasive measure of components of the bloodstream. In one example, variations in components of the bloodstream over time such as hemoglobin and water are determined based on the detected light, and the measure of hydration is then determined based on the in components of the bloodstream over time. In the absence of the LED light, ambient light may be sufficient illumination for analysis. The same sensor can provide identifying features of type or status of a tissue target, such as heart rate or heart rate variability, respiratory status, or even confirmation that the tissue is alive. Hydration monitoring systems incorporating the sensor, as well as methods, are also disclosed.

Provided is a method for detection of a preselected condition such as subclinical stress or pain in a subject animal using heart rate variability. The method comprises the steps of determining a heart rate and / or inter-beat interval for the subject animal over a preselected period of time to determine the subject animal's heart rate data. The method further comprises analyzing the heart rate or inter-beat data from the subject animal to identify a set of heart rate variability data for the subject animal for a selected heart rate variability parameter such as a frequency domain or time domain parameter such as LF / HF ratio. The heart rate variability data from the selected animal can be compared to substantially normal values established for the selected animal species or compared to the subject animal's own previously identified substantially normal values or HRV pattern over a period of time and thereby determine whether the preselected condition exists.

A device is configured to monitor a cardiovascular property of a subject. The device obtains measurement data from a primary pressure wave sensor arranged to detect pressure waves in an extracorporeal fluid circuit in fluid communication with the cardiovascular system of the subject. The device has a signal processor configured to generate a time-dependent monitoring signal based on the measurement data, such that the monitoring signal comprises a sequence of heart pulses, wherein each heart pulse represents a pressure wave originating from a heart beat in the subject; determine beat classification data for each heart pulse in the monitoring signal; and calculate, based at least partly on the beat classification data, a parameter value indicative of the cardiovascular property. The beat classification data may distinguish between heart pulses originating from normal heart beats and heart pulses originating from ectopic heart beats. The cardiovascular property may be an arterial status of the cardiovascular system, a degree of calcification in the cardiovascular system, a status of a blood vessel access used for connecting the extracorporeal fluid circuit to the cardiovascular system, a heart rate variability, a heart rate, a heart rate turbulence, an ectopic beat count, or an origin of ectopic beats. The device may be attached to or part of a dialysis machine.

The invention discloses a heat comfort detection method based on physiological parameters of the human body. The method comprises the following steps: acquiring the physiological parameters of the human body, including skin temperature, an electrocardiosignal, fingertip pulse, breath and skin impedance; performing peak value identification on the electrocardiosignal to obtain a heart rate variability signal and a heart rate; performing correlation analysis on the skin temperature, the heart rate variability signal, the heart rate, the fingertip pulse, the breath and the skin impedance to acquire the correlation degree of the physiological parameters and heat comfort so as to select optimal physiological parameters; performing regression analysis on the optimal physiological parameters, and building a function relationship between the physiological parameters and the comfort degree; inputting the function relationship of the physiological parameters and the comfort degree to a BP (Back-Propagation) neural network and performing automatic heat comfort degree judgment. The method can be used for intelligently regulating the temperature of an air conditioner by detecting the physiological parameters of the human body in real time and inputting the physiological parameters into an air conditioning system, and individual variation is fully considered, so that the regulated indoor thermal environment is more similar to the expected thermal environment of the human body.

This invention relates to a system and a kit for stress and relaxation management. A cardiac activity sensor (101) is used for measuring the heart rate variability (HRV) signal of the user and a respiration sensor (102) for measuring the respiratory signal of the user. The system contains a user interaction device (103) having an input unit (104) for receiving user specific data and an output unit for providing information output to the user. A processor (106) is used to assess the stress level of the user by determining a user related stress index. The processor is also used to monitor the user during a relaxation exercise by means of determining a relaxation index based on the measured HRV and respiratory signals, the relaxation index being continuously adapted to the incoming measured signals and based thereon the processor instructs the output unit to provide the user with biofeedback and support messages. Finally, the processor uses the user specific data as an input in generating a first set of rules defining an improvement plan for self-management of stress and relaxation. The first set of rules is adapted to trigger commands instructing the output unit to provide the user with motivation related messages. Also, at least a portion of said user specific data is further used to define a second set of rules indicating the user's personal goals.

The invention discloses a heart rate variability analyzing method based on an amplitude spectrum and instruments. The method comprises the following steps that a human body autonomic nervous function monitor is installed, after amplification, filtering and analog-digital conversion are carried out on electrocardio signals collected by an electrocardio electrode slice, an RR interval time sequence is built, the QRS waveform of the electrocardio signals has the features of large amplitude, short time limit, steep waveform and easy recognition, the key for obtaining HRV signals is that the R wave of an electrocardiogram is accurately calibrated, and according to the morphological characteristic of an R wave picture, the wave crest of the R wave is the maximum positive value in a single signal period; the instruments included in the method comprise a preamplifier module used for amplifying the electrocardio signals, a filter module, an A / D conversion module, an R crest positioning module, a signal pseudo crest pseudo differential eliminating module, an RR sequence forming module, an interpolation module and a display module which are sequentially connected, the preamplifier module is connected with the electrocardio electrode slice through a guide line, and the electrode slice is arranged on the surface of the human body skin and used for collecting the electrocardio signals of the human body.

Methods, devices, and systems for monitoring heart rate variability (HRV). The HRV monitoring systems and devices are adapted to give immediate feedback to the subject concerning their current condition and any pertinent changes in their condition. The HRV monitoring systems and devices detect, analyze, and assess HRV against a pre-determined application or user need. They also have the ability to provide real time notifications based on the system's assessment of a user's heart HRV and changes in the HRV.

The present invention describes a method of tracking minute ventilation from R-R intervals that are based on the acquisition of ECG signal. Sub-methods (RDF1), which are mainly based on heart rate variability, are used, wherein the respiratory frequency is determined from a pattern of rhythmic changes in heart beat data. The sub-methods (RDF1-n) are combined using an expert function, wherein each sub-method (RDF1-n) determines an estimate of the respiratory frequency.

The present invention provides a method and apparatus for monitoring the fetal condition in an objective, quantitative, and non-invasive manner by enabling continuous and highly specific data collection during pre-natal development and the intra-partum period. In an embodiment, monitoring the fetal condition comprises monitoring a fetal heart rate, a fetal heart rate variability, and / or the fetal heart vector orientation of a fetus in a pregnant mother. Automated signal processing techniques are applied to a multiplicity of transducers to select an optimum signal vector to monitor at least one of a fetal heart rate, a fetal heart rate variability, and / or the fetal heart vector orientation of a fetus in a pregnant mother.

The invention provides a biological feedback control method and system based on HRV heart rate variability training. The biological feedback control method comprises the steps that S1, mode options of any one or more combinations including a breathing guiding mode, a breathing training mode and a state evaluating mode are provided for a user to select; and S2, a corresponding mode interface is entered according to the selecting operation of the user, and heart rate variability analyzing is conducted on the current user when the user selects the breathing training mode or the state evaluating mode. The biological feedback control method has the advantages that the biological feedback control method is not limited to simple evaluation any longer, by conducting pointed breathing trainings with different rhythms on the user, impaired parasympathetic nerves (or sympathetic nerves) can recover to be balanced, and the purpose of effective preventing or relieving some diseases is achieved.

The embodiment of the invention discloses a method and device for acquiring a heart rate variation characteristic parameter. The method comprises the following steps of: calculating and obtaining a heart rate variation signal in a time domain according to a human physiological signal; carrying out time-frequency conversion on the heart rate variation signal in the time domain, and selecting a power spectrum subsequence reflecting heart rate variation from a converted power spectrum sequence according to a frequency characteristic of the heart rate variation; accumulating power values at frequency points upwards from a lowest frequency point of the power spectrum subsequence, and accumulating power values at frequency points downwards from a highest frequency point to obtain a first frequency point when the ratio of the accumulated power value to the total power value is more than a low frequency search ratio and a second frequency point when the ratio of the accumulated power value to the total power value is more than a high frequency search ratio; and obtaining the difference between the second frequency point and the first frequency point to obtain the frequency band width of the power spectrum subsequence, and the frequency band width is the characteristic parameter. According to the embodiment of the invention, the characteristic parameter can reflect periodic variation of the heart rate variation and also can reflect a position relationship between a main peak value and a secondary peak value.

The invention provides a sleep staging method based on a BCG (ballistocardiogram) signal. The method comprises the steps as follows: extracting a heart rate signal, a pulse signal and a respiration signal from the BCG signal acquired in advance, and calculating heart rate variability (HRV) and cardiopulmonary coupling (CPC) power spectrum according to the heart rate signal, the pulse signal and the respiration signal; acquiring change trend signals of frequency domain characteristics of the HRV and the CPC power spectrum, converting the change trend signals of the frequency domain characteristics of the HRV and the CPC power spectrum into multichannel image characteristics, performing characteristic extraction of the HRV and the CPC power spectrum, and extracting characteristic vectors according to time domain signals of the extracted HRV and CPC power spectrum; and training sleep staging results corresponding to HRV and CPC power spectrum density signals according to the multichannelimage characteristics and characteristic vectors. The sleep staging method combines the HRV and the CPC power spectrum to distinguish sleep stages and has higher adaptability and accuracy.

A wearable cardioverter defibrillator (WCD) system includes a support structure that the patient may wear, and one or more sensors that may acquire patient physiological signals, such as ECG and others. A processor of the WCD system may determine diagnostics from the patient physiological signals. These diagnostics include a six-second ECG portion, heart rates as histograms, heart rates against QRS width, heart rate trends, clinical event counters, diagnostics relating to heart rate variability and about the atrial arrhythmia burden of the patient. In some embodiments, the WCD system includes a user interface with a screen that displays these diagnostics. In some embodiments, the WCD system exports these diagnostics for viewing by a different screen. When viewed, these diagnostics permit more detailed analysis of the state of the patient.

The invention provides a heart rate measuring method and a heart rate measuring device based on the bioelectrical impedance technology. According to the heart rate measuring method, the bioelectrical impedance technology is adopted, specifically, an electrical impedance signal of the radial artery of the arm of a tested person is collected, then analog-digital conversion is carried out on the signal, thus an electrical impedance digital signal is obtained, and then the heart rate and heart rate variability characters are extracted from the electrical impedance digital signal. The heart rate measuring method has the characteristics of being simple and feasible, and being low in price and easy and convenient to operate, the heart rate data can be rapidly and accurately collected and analyzed, and the measurement for the tested person is realized.

A method for predicting ventricular arrhythmia includes a step of receiving at least one of an electrocardiogram signal and a respiration signal of a ventricular arrhythmia patient; a step of acquiring at least one of parameter values for heart rate variability and respiratory variability of the ventricular arrhythmia patient by analyzing at least one of the electrocardiogram signal and the respiration signal of the ventricular arrhythmia patient; a step of generating a ventricular arrhythmia estimation algorithm for predicting whether or not ventricular arrhythmia occurs by using the acquired parameter values; a step of predicting whether or not ventricular arrhythmia of a user occurs by applying at least one of the parameter values for the heart rate variability and the respiratory variability of the user to the ventricular arrhythmia estimation algorithm; and a step of outputting prediction results as to whether or not the ventricular arrhythmia occurs.

A system and method for assessing treatment effects on obstructive sleep apnea are provided. The apparatus includes a bio-signal measurement unit, a combined index calculation unit, and a treatment response assessment unit. The bio-signal measurement unit measures each of the electrocardiogram and respiratory rhythm of a patient. The combined index calculation unit calculates a combined cardiac and respiratory index by combining the heart rate variability and respiratory rhythm signals measured by the bio-signal measurement unit. The treatment response assessment unit assesses a response of the patient to the treatment of obstructive sleep apnea.

A synchronization cardiograph information detecting and analyzing method comprises, transforming cardiograph analog signals into digital signals, arranging 14 separate amplification channels for synchronously magnifying 14 lead electrocardiosignals, calculating the remained four leads, collecting the cardiograph data, and automatically analyzing high-frequency electrocardiogram, conventional electrocardiogram, atrium cordis late electric potential, frequency spectrum electrocardiogram, vectorcardiogram, heart rate variability, autonomic nerve information.

The invention relates to a method and system for detecting atrial arrhythmia, especially atrial fibrillations. Based on at least one electrical signal indicative of a heart's activity, a plurality of short-term HRV data sets are generated, one short-term HRV data set indicating the heart's rate variability within a time period of a given length, and two consecutive short-term HRV data sets having a given time difference. A frequency analysis of each short-term HRV data set is then performed and a power level corresponding to at least one selected frequency component in each short-term HRV data set is defined. The occurrence of the heart's atrial arrhythmia episodes are then estimated on the basis of the power levels defined.

A decision support tool is provided for predicting the neonatal vitality scores of a fetus during delivery, the scores being an indicator of future health for the infant anticipated to be born within a future time interval, measured as time to birth. The predicted neonatal vitality score is determined from measurements of physiological variables monitored during labor, such as uterine activity and fetal heart rate. Fetal heart rate variability and patterns may be detected and computed using the monitored physiological variables, and neonatal vitality scores may be predicted based, at least in part, on the variability metrics and fetal heart rate patterns. Scores may be predicted for different delivery methods, such as vaginal delivery or cesarean delivery, for different time-to-birth intervals. In this way, these scores may be used for decision support for care plans during labor, such as increased monitoring and / or modifying the delivery type.

The present invention discloses neuro-stimulation systems and methods for affecting cardiovascular function, particularly for improving heart rate variability and treating arrhythmia.

A scientific method and system for determining a customized essential oil blend through accessing a physiolocial data from a user are disclosed in the present invention. The physiological data is heart rate vairiability (HRV), which is associated with cardiac diseases and the autonomic nervous system.

Described herein are fetal and / or maternal monitoring devices, systems and methods using UWB medical radar. These devices and systems may include a UWB sensor providing high-resolution and reliable simultaneous monitoring of multiple indicators of fetal and / or maternal health, such as fetal heart rate, fetal heart rate variability, fetal respiration, fetal gross body movement, maternal contractions, maternal heart rate, maternal respiration, and other derivative parameters during virtually all stages of pregnancy and during delivery. The sensor allows novel collection of physiological data using a single sensor or multiple sensors to develop individual and aggregate normal motion indices for use in determining when departure from normal motion index is indicative of fetal or maternal distress.

The invention discloses a sleep staging method based on BCG and blood oxygen saturation rate. The sleep staging method comprises the following steps of collecting BCG data and blood oxygen saturationdata of the whole night; extracting a JJ interval from BCG signals to obtain a heart rate signal and heart rate variability; processing the BCG signal to obtain a respiratory rate signal, and calculating a cardiopulmonary coupling power spectrum; and establishing a state set S = {S1, S2, S3, S4} of the sleep process. According to the sleep staging method based on the BCG and the blood oxygen saturation rate, the accuracy degree of sleep staging of non-contact information collection can be improved, the characteristics of a sober state are extracted in a cardiopulmonary coupling power spectrummode, sleep staging training is optimized by a machine learning clustering analysis method, the accuracy degree of sleep staging is improved, and a user can be helped to obtain an accurate examinationresult of the sleep state in a non-inductive environment.