7 results about "Sinus rhythm" patented technology

Methods, apparatus, and systems are provided to control contraction of the heart. At least one sensing element receives signals indicating electrical activity of sinus rhythm of the heart. Based on the received signals, the progress of contraction of the heart is determined. Based on the progress of contraction, the chamber of the heart may then be stimulated at a plurality of locations. In another embodiment, a plurality of electrodes are implanted in the left ventricle to stimulate at multiple locations in the left ventricle for the purpose of improving hemodynamic performance and increasing cardiac output in a patient who is suffering from congestive heart failure.

The method is for treating an individual having atrial fibrillation (AF) with administration of oral magnesium supplementation for converting atrial fibrillation to sinus rhythm. The method includes monitoring cardiac rhythms frequently (e.g. daily), importance of remaining hydrated, adding potassium if needed, and administering a dose of oral magnesium supplements for at least four to six weeks, for example. The method includes titrating the dose of magnesium supplements until conversion of atrial fibrillation to sinus rhythm, and additional titrating of the dose of magnesium supplements based upon recurrence of atrial fibrillation, until conversion of atrial fibrillation to sinus rhythm. Monitoring ‘Heart Rate Variability” in certain circumstances may forecast the presence or recurrence of atrial fibrillation.

A method and an electronic device for detecting a heart rhythm are provided. The method comprises: acquiring a first PPG signal in a first preset time length; determining a plurality of heart rate values based on the first PPG signal; determining a difference value of each two adjacent heart rates based on the plurality of heart rate values, the difference value of each two adjacent heart rates being used to generate a heart rate difference value trajectory graph; acquiring parameters of a heart rate difference value trajectory based on the heart rate difference value trajectory graph, the parameters of the heart rate difference value trajectory comprising one or more of the following parameters: an angle, a number, an angle standard deviation, a distance standard deviation; determining a heart rhythm type of the first PPG signal according to the parameters of the heart rate difference value trajectory, the heart rhythm type comprising any one of the following: a premature beat, an atrial fibrillation, a sinus rhythm, a ventricular tachycardia, a bigeminy, a trigeminy; and displaying the heart rhythm type of the first PPG signal, which can improve the accuracy of identifying a premature beat or an atrial fibrillation, reduce the probability of identifying a premature beat as an atrial fibrillation, and improve user experience.

The application belongs to the technical field of biological medicine, and particularly relates to a biomarker and application thereof. The application finds that the expression level of a specific subtype of a nicotine acetylcholine receptor of an arrhythmia patient is significantly lower than that of a sinus rhythm population, and the expression of the nicotine acetylcholine receptor in ischemia / reperfusion injury myocardium of a rat and myocardium of a heart failure patient also shows a significant downward trend. Further research finds that the expression loss of the specific subtype of the nAChR significantly increases the risk of arrhythmia. In combination with animal experiment results and human clinical data, it can be seen that the expression defect of the endogenous cholinergic system is closely related to fatal arrhythmia.

The invention relates to the technical field of medical equipment, and discloses a nail oximeter for heart disease diagnosis and a using method thereof, the nail oximeter comprises a main body formed by pivoting an upper cover and a lower shell, and a U-shaped spring, a PCBA mainboard, a light-emitting tube and a photosensitive receiving unit are arranged in the main body. The method comprises the steps of collecting photoelectric volume pulse wave signals and segmenting the photoelectric volume pulse wave signals into cardiac cycle waveform sequences, calculating rhythm features and morphological distortion degree features for each waveform in combination with an average morphological template exclusive to a user, constructing multi-dimensional state vectors, mapping continuous vector sequences into geometric trajectories in a state space, and calculating the morphological distortion degree of each waveform according to the geometric trajectories. And finally, judging whether the heart rhythm state is sinus rhythm or abnormal rhythm by analyzing the macroscopic geometrical characteristics of the trajectory, and outputting a result. According to the method, the rhythm and form information of the heartbeat is fused for state space analysis, so that the accuracy and reliability of screening abnormal states such as arrhythmia in a household scene are effectively improved.

The application discloses a physiological characteristic monitoring data processing method and device and a computer readable storage medium, and the method comprises the following steps: acquiring radar in-phase and quadrature signals, positioning a target thoracic cavity distance unit, extracting phase information, and generating a micro-motion signal; performing signal separation on the micro-motion signal based on a preset frequency interval, extracting independent respiratory signals and heartbeat signals; extracting a heartbeat cycle sequence of the heartbeat signal to generate a heart rhythm state feature; calculating the timing correlation of the respiratory signal and the heartbeat cycle sequence to generate a respiratory-heartbeat correlation feature; inputting the heart rhythm state feature and the respiratory-heartbeat correlation feature into a preset classification network to perform feature fusion and inference operation, and outputting a sinus rhythm type. The application realizes high-fidelity decoupling of a non-contact heart-lung signal, can accurately identify respiratory and non-respiratory sinus arrhythmia, effectively avoids false health warnings, and breaks through the cognitive barriers of professional medical indicators.

The invention relates to the technical field of medical artificial intelligence, in particular to an atrial fibrillation intelligent detection method and system based on multi-scale electrocardiogram wavebands and space-time fusion features, and the detection method comprises the steps: extracting the local features of the multi-scale P / QRS wavebands of electrocardiosignals and the space-time features of the whole section of signals through a deep learning model, and carrying out the multi-operator fusion and classification. The core of the training method is that an innovative labeling strategy based on atrial fibrillation identity information of a patient is adopted, the sinus rhythm period of the patient is also used as a positive sample for training, and the early warning ability of the model is improved. The system integrates the models trained according to the method. According to the method, the accuracy rate and the early recognition capability of automatic detection of the atrial fibrillation are effectively improved, and a complete solution is formed.