9 results about "Pulse Wave Analysis" patented technology

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.

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.

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 a disease prediction method and system based on left and right radial artery pulse wave analysis, and the method comprises the steps: arranging sensors at corresponding positions of different arms, and collecting left and right radial artery pulse waves according to a preset rule, so as to obtain signal data; carrying out denoising processing on the signal data, wherein the denoising processing comprises synchronous wavelet decomposition, common-mode noise component calculation and phase subtraction denoising; carrying out feature extraction according to the denoised signal data, wherein the features comprise a time domain feature, a frequency domain feature and a nonlinear feature; and carrying out classification according to the extracted features by adopting a framework of integrated learning and model training, and outputting risk rating. The system comprises a signal acquisition unit, a signal preprocessing unit, a feature extraction unit and a classification unit. According to the method, disease risk prediction is carried out by utilizing the characteristics of the left and right radial artery pulse waves, and the prediction accuracy can be improved. The method can be widely applied to the fields of medical instruments and data analysis.

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