768 results about "RR interval" patented technology

The present invention relates to advanced signal processing methods including digital wavelet transformation to analyze heart-related electronic signals and extract features that can accurately identify various states of the cardiovascular system. The invention may be utilized to estimate the extent of blood volume loss, distinguish blood volume loss from physiological activities associated with exercise, and predict the presence and extent of cardiovascular disease in general.

A method and apparatus are disclosed for using photoplethysmography to obtain physiological parameter information related to respiration rate, heart rate, heart rate variability, blood volume variability and / or the autonomic nervous system. In one implementation, the process involves obtaining (2502) a pleth, filtering (2504) the pleth to remove unwanted components, identifying (2506) a signal component of interest, monitoring (2508) blood pressure changes, monitoring (2510) heart rate, and performing (2512) an analysis of the blood pressure signal to the heart rate signal to identify a relationship associated with the component of interest. Based on this relationship, the component of interest may be identified (2514) as relating to the respiration or Mayer Wave. If it is related to the respiration wave (2516), a respiratory parameter such as breathing rate may be determined (2520). Otherwise, a Mayer Wave analysis (2518) may be performed to obtain parameter information related to the autonomic nervous system.

This invention provides methods for non-invasively monitoring patients with congestive heart failure (CHF) and for reporting and / or warning of changes in the patients' status. The methods gather physiological data and combine the data into parameters by which the severity of CHF can be judged. Preferred parameters include periodic breathing and heart rate variability. This invention also provides systems for carrying out these methods which permit patients to engage in their normal daily activities. Preferably, physiological data analysis is performed by a portable electronic unit carried by the patients.

Devices and methods are disclosed that treat a medical condition, such as migraine headache, by electrically stimulating a nerve noninvasively, which may be a vagus nerve situated within a patient's neck. Preferred embodiments allow a patient to self-treat his or her condition. Disclosed methods assure that the device is being positioned correctly on the neck and that the amplitude and other parameters of the stimulation actually stimulate the vagus nerve with a therapeutic waveform. Those methods comprise measuring properties of the patient's larynx, pupil diameters, blood flow within an eye, electrodermal activity and / or heart rate variability.

Methods involving extraction of information from the inherent variability of physiometrics, including data on cardiovascular and pulmonary functions such as heart rate variability, characteristics of ECG traces, pulse, oxygenation of subcutaneous blood, respiration rate, temperature or CO2 content of exhaled air, heart sounds, and body resonance, can be used to identify individual subjects, particularly humans. Biometric data for use in the methods can be obtained either from contact sensors or at a distance. The methods can be performed alone or can be fused with previous identification algorithms.

A method and a system for detection of an arrhythmia, the method comprising determining a number of heart beat intervals; determining an instantaneous heart rate for each of the heart beat intervals; determining the variability of the instantaneous heart rates compared to a mean of the number of instantaneous heart rates; determining a non-linear value that represents the variability of the instantaneous heart rates; and detecting the arrhythmia by comparing the non-linear value with a predetermined threshold.

Apparatus is provided that includes an electrode device, adapted to be coupled to a vagus nerve of a subject, and a control unit, adapted to drive the electrode device to apply to the vagus nerve a current that reduces heart rate variability of the subject. Also provided is a method comprising applying to a vagus nerve of a subject a current that reduces heart rate variability of the subject.

There is provided a method of determining a diagnostic measure of sleep apnea including the following steps: acquiring an electrocardiogram signal, calculating a set of RR intervals and electrocardiogram-derived respiratory signal from said electrocardiogram, and hence calculating a set of spectral and time-domain measurements over time periods including power spectral density, mean, and standard deviation. These measurements are processed by a classifier model which has been trained on a pre-existing data base of electrocardiogram signals to provide a probability of a specific time period containing apneic episodes or otherwise. These probabilities can be combined to form an overall diagnostic measure. The system also provides a system and apparatus for providing a diagnostic measure of sleep apnea.

An apparatus and method for predicting potentially fatal arrhythmias up to twenty four hours in advance of the event by employing formulas indicating either too little or too much heart rate variability. A number of these formulas have both predetermined upper and lower limits, which if exceeded for a period of time are a predictor of a potentially fatal arrhythmia. When a patient's ALARM condition is predicted, whether the patient is indoors or outdoors, conscious or unconscious, a redundant protocol is utilized to relay that ALARM condition to a central monitoring station. The central monitoring station informs the patient's doctor, and then uses what ever means are available to transport the patient to the nearest emergency room for treatment. An apparatus and method for pacing the heart in a natural way, once a potentially fatal arrhythmia has been predicted is also disclosed.

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.

Disclosed herein are methods, systems, and apparatus for treating a medical condition of a patient, involving detecting a physiological cycle or cycles of the patient and applying an electrical signal to a portion of the patient's vagus nerve through an electrode at a selected point in the physiological cycle(s). The physiological cycle can be the cardiac and / or respiratory cycle. The selected point can be a point in the cardiac cycle correlated with increased afferent conduction on the vagus nerve, such as a point from about 10 msec to about 800 msec after an R-wave of the patient's ECG, optionally during inspiration by the patient. The selected point can be a point in the cardiac cycle when said applying increases heart rate variability, such as a point from about 10 msec to about 800 msec after an R-wave of the patient's ECG, optionally during expiration by the patient.

According to embodiments of the invention, there is provided a method of producing an artificial neural network capable of predicting the survivability of a patient, the method including: storing in an electronic database patient health data, the patient health data comprising a plurality of sets of data, each set having at least one of a first parameter relating to heart rate variability data and a second parameter relating to vital sign data, each set further having a third parameter relating to patient survivability; providing a network of nodes interconnected to form an artificial neural network, the nodes comprising a plurality of artificial neurons, each artificial neuron having at least one input with an associated weight; and training the artificial neural network using the patient health data such that the associated weight of the at least one input of each artificial neuron of the plurality of artificial neurons is adjusted in response to respective first, second and third parameters of different sets of data from the patient health data, such that the artificial neural network is trained to produce a prediction on the survivability of a patient.

A method and apparatus for method for discriminating heart rhythms includes computing a first predetermined number of RR intervals from received QRS intervals, and computing a median RR interval corresponding to a predetermined number of the first predetermined number of RR intervals. A predetermined beat-to-beat variation and a corresponding predetermined count are determined based on the computed median RR interval. Beat-to-beat variation differences between the first predetermined number of RR intervals are computed and a determination is made as to whether the computed beat-to-beat variation differences are greater than the predetermined beat-to-beat variation, and as to whether a number of the computed beat-to-beat variation differences that are greater than the predetermined beat-to-beat variation is greater than the predetermined count. The heart rhythm is identified as an irregular rhythm in response to the number being greater than or equal to the predetermined count.

A device and method in which spectral analysis of heart rate variability is performed in order to assess autonomic balance. When a threshold level is reached, a diagnostic mode is triggered in which the device performs computationally intensive data analysis to assess the probability of a pathological event such as an arrhythmia occurring.

An method for analyzing irreversible apneic coma (IAC) for determining the presence of irreversible apneic coma (IAC) by analyzing the heart rate variability of a brain traumatic patient, thereby providing a physician a reference index to determine whether brain death has occurred. This method includes, at first, recording an electrocardiogram (ECG) from a subject. Then, analyzing R-R interval in said electrocardiogram (ECG), and plotting said R-R interval into Poincaré plot, wherein the X coordinate in said Poincaré plot represents R-R interval(n), and n is a 1˜data number. Y coordinate in said Poincaré plot represents RR(n+1). And, finally, quantifying said Poincaré plot, and obtaining semi-major axis (SD1), semi-minor axis (SD2), and SD1 / SD2 of said Poincaré plot, as well as Poincaré plot area.

The invention relates to a method and apparatus for predicting a sudden heart abnormality for an individual patient. In order to provide a prediction mechanism that is suitable for acute care, three sub-indices are determined based on medical data obtained from the patient. The first sub-index indicates the level of deterministic chaos in the heart rate variability of the patient, the second sub-index indicates the energy level in the myocardium of the patient, and the third sub-index indicates the degree of ventricular arrhythmia of the patient. Based on the first, second, and third sub-indices, at least one overall risk index is then determined, the overall risk index indicating the risk level of a sudden heart abnormality for the patient.

A medical device system and method for monitoring cardiac signal activity in patients with nervous system disorders. In some embodiments, a brain signal and a cardiac signal are received by a processor, brain events are identified in the brain signal, and the brain events are used to identify portions of the cardiac signal. In some embodiments, Event portions of the cardiac signal are identified corresponding to brain event time periods, and Inter-event portions are identified corresponding to time periods between brain events. An Inter-event heart-rate variability (HRV) calculation is performed using Inter-event portions of the cardiac signal, and an output of the medical device system is modified based upon the calculated Inter-event HRV according to certain embodiments of the invention. An Event HRV may also be calculated according to certain embodiments, and an output modified based on comparisons of the Event HRV to the Inter-event HRV, for example.

A method for calculating a variability value that is indicative of AF by obtaining a signal sequence of a plurality of RR intervals by monitoring electrical activity of a patient's heart. Each RR interval is converted into an instantaneous heart rate value and sorted into ascending order. The difference between each successive heart rate is calculated, discarding the two largest differences. The variability value is calculated by adding the retained differences.

An implantable medical device and method are provided for assessing autonomic tone and risk factors associated with arrhythmias and, based on this assessment, an early recurrence of ventricular tachycardia or ventricular fibrillation is predicted. Specifically, changes in R—R interval, heart rate variability, patient activity, and myocardial ischemia are measured prior to and after a detected an arrhythmia episode. A recurrence score is calculated as a weighted sum of measured parameters and compared to a prediction criterion. The prediction criterion may be a preset threshold score or an individualized episode template based on previously calculated recurrence scores associated with recurring episodes. Stored parameters and episode-related data may be downloaded for offline analyses for optimizing prediction criteria and monitoring patient status.

A medical device system and method for monitoring cardiac signal activity in patients with nervous system disorders. In some embodiments, a brain signal and a cardiac signal are received by a processor, brain events are identified in the brain signal, and the brain events are used to identify portions of the cardiac signal. In some embodiments, Event portions of the cardiac signal are identified corresponding to brain event time periods, and Inter-event portions are identified corresponding to time periods between brain events. An Inter-event heart-rate variability (HRV) calculation is performed using Inter-event portions of the cardiac signal, and an output of the medical device system is modified based upon the calculated Inter-event HRV according to certain embodiments of the invention. An Event HRV may also be calculated according to certain embodiments, and an output modified based on comparisons of the Event HRV to the Inter-event HRV, for example.

The invention discloses a dynamic electrocardiogram and motion recording and analyzing system, which is used for automatic detection on user activities and electrocardiogram analysis under activity scenes. The system comprises an electrocardiogram and motion sensor unit, a data acquisition, storage and transmission unit and an analysis and software unit, wherein the electrode of a motion sensor and the electrode of an electrocardiogram sensor can be packaged together or used independently; the system records and automatically detects daily physical motions of a user, such as lying, sitting, walking, running, tumbling, sitting up, standing up, sitting down, lying down and the like, and gives corresponding activity intensity; the electrocardiogram is automatically analyzed; and a corresponding mark is given when an abnormal electrocardiogram or abnormal activity is detected, all corresponding original signals and analysis results are stored, and nursing staff are prompted. The system gives heart rate variability of the user under different activity intensities, and changes of the heart rate variability along with activity types, activity intensities and time. The systems gives a method of analyzing changes of heart rate and electrocardiogram forms along with activity intensity and duration, and can be used for aerobic exercise optimization and exercise safety in motion and exercising.

An approach for improving the chances of survival of an individual who has received a trauma including, for example, hemorrhage or blunt injury, by providing more relevant information regarding the individual to first responders including at least one of heart rate variability index value, a baroreflex sensitivity value, and a pulse pressure. This information being used in at least one implementation to provide medical treatment to injured individuals including dispatching assistance and / or prioritizing in a triage situation increasing the speed at which these decisions can be made. In one exemplary embodiment, the heart rate variability index value is determined based on the relative power of the high frequencies versus the relative power of the low frequencies. In one exemplary embodiment, the pulse pressure is determined based on the difference between systolic pressure and diastolic pressure.

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 relates to a measurement apparatus for heart rate variability, which comprises an earpiece, a measurement module for photoplethysmographic (PPG) signal measuring an ear and producing a first physiological signal of a person under test, a measurement module for electrocardiographic (ECG) signal measuring a second physiological signal of the person under test, and a control and processing unit transmitting a sound signal to the earpiece. By playing the sound signal from the earpiece, the attention of the person under test can be detracted from the measurement module for PPG signal or the measurement module for ECG signal. Thereby, nervousness and impatience of the person under test can be eliminated, and hence the real heart rate variability of the person under test can be measured.

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 relates to a system and method for determining sleep, sleep stage and / or sleep stage transition of a person, including heart rate detecting means configured for detecting a heart rate of the person, movement detecting means configured for detecting a movement of a part of the body of the person, where the detected movement is caused by a skeletal muscle of the body, recording means configured for recording the detected heart rate and the detected movement of the part of the body, heart rate classifying means configured for classifying the recorded heart rate of the person into at least one heart rate class at least one heart rate variability class, movement classifying means configured for classifying the recorded movement into at least one movement class, and determining means configured for determining sleep, a sleep stage, a sleep stage transition and / or a sleep event of the person based at least partially on the at least one heart rate class and the at least one movement class.

The present disclosure is directed towards apparatuses, systems and methods for providing improved sensor-based patient monitoring and tracking. In accordance with one aspect, a method is provided for adjusting a vital sign alarm threshold of a vital status sensor as a function of a patient's GPS data, which may comprise: altitude data, velocity data, and position data. In accordance with another aspect, a method is provided for adjusting one or more alarm detection parameters based in part on a patient's calculated heart rate variability (HRV) data. According to yet another aspect, an electronic triage tag is configured to include a colored card insertion region for inserting a colored card for preventing the device from being inadvertently activated, an LCD screen and a series of LEDs for displaying the triage status of a patient (red, yellow, green, black).

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.

What is disclosed is a video-based system and method for estimating heart rate variability from time-series signals generated from video images captured of a subject of interest being monitored for cardiac function. In a manner more fully disclosed herein, low frequency and high frequency components are extracted from a time-series signal obtained by processing a video of the subject being monitored. A ratio of the low and high frequency of the integrated power spectrum within these components is computed. Analysis of the dynamics of this ratio over time is used to estimate heart rate variability. The teachings hereof can be used in a continuous monitoring mode with a relatively high degree of measurement accuracy and find their uses in a variety of diverse applications such as, for instance, emergency rooms, cardiac intensive care units, neonatal intensive care units, and various telemedicine applications.