15 results about "Pulse Wave Analysis" patented technology

An electronic device according to an embodiment may include communication circuitry and at least one processor. The at least one processor may be configured to receive a first PPG signal obtained by a first wearable device from the first wearable device via the communication circuitry and receive a second PPG signal from a second wearable device. The first wearable device may be worn on a first position of a user and the second wearable device may be worn on a second position of the user. The at least one processor may be configured to obtain a pulse transit time (PTT) taken for a pulse wave to be transferred from the first position to the second position, based on the first PPG signal and the second PPG signal. The at least one processor may be configured to obtain a distance between the first wearable device and the second wearable device. The at least one processor may be configured to obtain a pulse wave velocity (PWV) at which the pulse wave is transferred, based on the distance and the PTT. The at least one processor may be configured to obtain a first blood pressure by using a pulse wave analysis (PWA) method, based on the first PPG signal and / or the second PPG signal. The at least one processor may be configured to obtain a vascular characteristic value related to a characteristic of a blood vessel, based on the PWV and the first blood pressure. The at least one processor may be configured to obtain a blood pressure correction value for correcting a second blood pressure to be obtained, based on the vascular characteristic value.

The present application relates to the technical field of medical monitoring, in particular to a vascular hemodynamic abnormality monitoring system and a pulse wave analysis method thereof, the core of the present application lies in that a flexible piezoelectric sensor array is used to capture human vascular pulse wave signals, the signals are transmitted to a wearable monitoring device for preliminary preprocessing, and then transmitted to a data processing host through a wireless manner, a pulse wave analysis module in the host adopts a multi-level analysis method, including multi-scale signal decomposition and reconstruction, nonlinear feature extraction and pattern recognition, multi-parameter adaptive judgment standard, deep learning feature automatic extraction and multi-site information fusion decision, ensuring the accuracy and comprehensiveness of the analysis, finally, the processing result is transmitted to an application platform to generate a vascular health report, realizing non-invasive continuous monitoring, this innovation effectively fills the gap of the prior art in continuous monitoring, and has important significance for real-time monitoring of vascular health status and prevention of vascular diseases.

A self-calibration method of a pulse wave analysis blood pressure measuring device mainly comprises the following steps that the pressure of an air bag is regulated and controlled, and blood pressure measurement is completed through oscillography; the pressure of the air bag is adjusted to the pressure needed by blood pressure measurement through the pulse wave analysis method, the pressure is kept, and data used for blood pressure measurement through the pulse wave analysis method are collected; and binding the acquired pulse wave data with a blood pressure value calculated by an oscillography to finish calibration. According to the method, calibration can be automatically completed without additional equipment, and the use convenience of the pulse wave analysis blood pressure measuring device can be effectively improved.

Multi-use blood pressure sensor systems are capable of earning out multiple methods of blood pressure measurements, including full-length finger oscillometric curve method (FL-FOCM), short-length finger oscillometric curve method (SL-FOCM) and pulse wave analysis based on oscillometric curve (PWA-BOC) method. The short-length finger oscillometric curve (SL- FOCM) and pulse wave analysis based on oscillometric curve (PWA-BOC) methods rely on oscillometric curves previously obtained from the full-length finger oscillometric curve method (FL-FOCM) and stored in a library of curves and / or converted into a predictive curve model.

According to the pulse wave analysis method based on ultrasonic imaging, the pulse wave analysis equipment and the ultrasonic imaging system, ultrasonic data stored in a real-time scanning state can be read in a non-real-time scanning state, and the pulse wave analysis equipment is used for analyzing the pulse wave based on the ultrasonic image. Performing pulse wave analysis again according to the read ultrasonic data to obtain and output a pulse wave analysis result after reanalysis; besides, in the function of performing pulse wave analysis again in a non-real-time scanning state to obtain a pulse wave analysis node after reanalysis, one or more links such as redetermination of an interested area, reidentification of a blood vessel wall and reidentification of the early / late period of the heart can be extended; the flexibility of the pulse wave analysis function, the utilization rate of case data and the efficiency of clinical diagnosis can be greatly improved.

A sleepiness level estimator comprises a Doppler sensor configured to detect a user's pulse wave and an analysis unit configured to analyze the pulse wave detected by the Doppler sensor. The analysis unit is configured to generate an index value by digitizing the pulse wave based on chaos analysis, where a pulse waveform change (a time-series change in the pulse waveform) serves as the analysis source. The unit then estimates the user's sleepiness level based on this index value and outputs sleepiness level information.

This invention discloses a continuous non-invasive blood pressure monitoring system based on fingertip photoplethysmography (PPG). The system includes: an intelligent finger cot terminal for acquiring fingertip PPG signals and adjusting the fingertip contact pressure in real time using a closed-loop control formula to maintain a constant pressure state on the finger blood vessels; a mobile computing terminal for receiving fingertip PPG signals and performing preprocessing operations on the fingertip PPG signals; and a cloud service platform for calculating the preprocessed fingertip PPG signals based on a preset blood pressure calculation model to obtain a continuous blood pressure waveform and estimate hemodynamic parameters based on the continuous blood pressure waveform. The preset blood pressure calculation model is specifically a pulse wave analysis model, a pulse wave propagation time model, or a deep learning mapping model. The hemodynamic parameters are specifically stroke volume and cardiac output. Through the mobile computing terminal and the cloud service platform, continuous arterial pressure waveform reconstruction and physiological parameter calculation are realized, and long-term monitoring accuracy can be maintained through a periodic calibration mechanism.

An adaptive processing of the pulsatility signal can improve the pulse wave analysis (PWA) leading to a better blood pressure estimation. The technique is based on transforming the pulsatility signal so that the fiducial points required for the PWA are well-defined.

An electronic device according to one embodiment may comprise a communication module and at least one processor. The at least one processor may be configured to receive a first PPG signal obtained by a first wearable device from the first wearable device and receive a second PPG signal from a second wearable device through a communication circuit. The first wearable device may be worn at a first location on a user and the second wearable device may be worn at a second location on the user. The at least one processor may be configured to obtain a pulse transit time (PTT) for which pulse waves are transmitted from the first location to the second location, on the basis of the first PPG signal and the second PPG signal. . The at least one processor may be configured to obtain the distance between the first wearable device and the second wearable device. The at least one processor may be configured to obtain a pulse wave velocity (PWV) at which pulse waves are transmitted, on the basis of the distance and the PTT. The at least one processor may be configured to obtain a first blood pressure by using a pulse wave analysis (PWA) method on the basis of the first PPG signal and / or the second PPG signal. The at least one processor may be configured to obtain a blood vessel characteristic value related to the characteristics of blood vessels, on the basis of the PWV and the first blood pressure. The at least one processor may be configured to obtain a blood pressure correction value for correction of a second blood pressure that is to be obtained, on the basis of the blood vessel characteristic value.

A blood pressure measuring device air bag pressure self-adaptive adjusting method based on pulse wave analysis belongs to the technical field of blood pressure measurement, and can adjust the pressure value of an air bag in a self-adaptive manner according to the current wearing and measuring environment of a blood pressure measuring device and the pulse wave signal quality. A proper pressure is maintained between a wearing device of the blood pressure measuring device and a measuring part, so that the amplitude and the quality of the pulse wave signal can still be relatively consistent when different users wear the blood pressure measuring device with different degrees of tightness.

The invention relates to the technical field of medical monitoring, in particular to a vascular hemodynamics anomaly monitoring system and a pulse wave analysis method thereof.The core of the vascular hemodynamics anomaly monitoring system is that a flexible piezoelectric sensor array is used for capturing human body vascular pulse wave signals, the signals are transmitted to a wearable monitoring device for preliminary preprocessing, and the human body vascular pulse wave signals are obtained; a pulse wave analysis module in the host adopts a multi-level analysis method, and the multi-level analysis method comprises the steps of multi-scale signal decomposition and reconstruction, nonlinear feature extraction and mode recognition, multi-parameter self-adaptive judgment standard, deep learning feature automatic extraction and multi-part information fusion decision making; according to the method, the analysis accuracy and comprehensiveness are ensured, finally, a processing result is transmitted to an application platform, a blood vessel health report is generated, non-intrusive continuous monitoring is achieved, the innovation effectively fills the blank of continuous monitoring in the prior art, and the method has great significance in monitoring the blood vessel health condition in real time and preventing blood vessel diseases.

The present application belongs to the field of medical devices and physiological signal detection technology, and relates to a pulse wave analysis method and system based on piezoelectric dynamics characteristics. The present application compensates for the attenuation of the subcutaneous tissue on the pulse wave through active acoustic detection, emits high-frequency mechanical vibration waves at the end of diastole using multi-frequency voltage pulses, and receives reflected echoes to construct an equivalent acoustic impedance transfer function and an acoustic inverse compensation filter. The present application restores the true arterial vessel wall dynamics by performing frequency domain deconvolution operation on the original pulse wave signal, locates key physiological event points, estimates the local pulse wave propagation speed using a single-point piezoelectric sensor without the need for multi-point measurement. In combination with the fluid mechanics equation, the present application separates the forward incident wave and the backward reflected wave, calculates the absolute amplitude ratio to evaluate the vascular compliance, effectively eliminates the interference of subcutaneous fat and muscle tissue, improves the accuracy and reliability of the evaluation, and provides a new tool for cardiovascular function evaluation.

The invention discloses an atrial fibrillation detection system, an atrial fibrillation detection method and a processor. In the scheme, a signal acquisition module acquires a pulse wave signal of a target object within a preset duration and generates a corresponding pulse oscillogram; the first data processing module performs time domain feature analysis on the pulse oscillogram to obtain a first time domain feature value and a second time domain feature value, and determines a multi-dimensional feature joint value based on the first time domain feature value and the second time domain feature value; a second data processing module performs data distribution feature analysis on the pulse oscillogram to obtain a target feature value when determining that the target object has an arrhythmia condition based on the multi-dimensional feature joint value; and the recognition module recognizes the arrhythmia type of the target object according to the target feature value to obtain a recognition result. By optimizing the pulse wave analysis algorithm of the atrial fibrillation, accurate recognition of the atrial fibrillation can be completed through single pulse wave signal measurement, and the auxiliary value of the recognition result on medication and treatment of medical workers is effectively improved.

To provide a blood pressure pulse wave measuring device and a blood pressure pulse wave measuring method capable of suppressing deterioration in reliability of an arteriosclerosis examination due to tension or the like felt by a subject.SOLUTION: A blood pressure pulse wave measuring device includes: a blood pressure pulse wave measuring part for measuring the blood pressure pulse wave of a subject; a heartbeat analysis part for detecting a rest state of the subject by analyzing a heartbeat trend of the subject; an extraction part for extracting the blood pressure pulse wave when the rest state of the subject is detected by the heartbeat analysis part, of the blood pressure pulse wave measured by the blood pressure pulse wave measuring part; and a degree-of-arteriosclerosis calculation part for calculating an index of the arteriosclerosis of the subject using the blood pressure pulse wave extracted by the extraction part.SELECTED DRAWING: Figure 2