SYSTEM AND METHOD FOR BLOOD PRESSURE MEASUREMENT, COMPUTER PROGRAM PRODUCT USING THE METHOD, AND COMPUTER-READABLE RECORDING MEDIUM THEREOF

• US 20170071485A1
• Filed: 07/07/2016
• Published: 03/16/2017
• Est. Priority Date: 09/16/2015
• Status: Abandoned Application

• Current Assignee: Amengine Corporation
• Original Assignee: National Chiao Tung University (Government of The Republic of China)
• Inventors: Huang, Sheng-Chieh, Kao, Yung Hua, Tu, Tse-Yi, Chiang, Pei-Yu, Chao, Paul C.-P.
• Application Number:
  US15/204,392
• Publication Number:
  US 20170071485A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/02108 from analysis of pulse wave characteristics
• CPC Class Codes: A61B 5/02125 of pulse wave propagation time
• CPC Class Codes: A61B 5/02133 by using induced vibration of the blood vessel
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 3/086 using evolutionary algorithms, e.g. genetic algorithms or genetic programming
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16Y 20/40 relating to personal data, e.g. biometric data, records or preferences
• CPC Class Codes: G16Y 40/10 Detection; Monitoring
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Abstract

The present invention provides a system and method for blood pressure measurement, a computer program product using the method, and a computer-readable recording medium thereof. The present invention uses a sensor to measure an electrophysiological signal and establishes a personalized cardiovascular model through a numerical method, and re-establishes the personalized cardiovascular model through an optimization algorithm. Thus, a human physiological parameter generated from the re-established personal cardiovascular model matches the electrophysiological signal. Therefore, the present invention can provide accurate measurement results with the advantage of a small size, and can be applied to telemedicine field.

Claims

1. A method for blood pressure measurement, comprising:

measuring an electrophysiological signal and obtaining basic personal information;

establishing a personalized cardiovascular model based on the electrophysiological signal and the basic personal information through a numerical method, wherein the personalized cardiovascular model includes default model parameters and is configured to create a human physiological parameter; and

calibrating the default model parameters through an optimization algorithm to re-establish the personalized cardiovascular model, such that the human physiological parameter created by the re-established personalized cardiovascular model matches the measured electrophysiological signal.

2. The method for blood pressure measurement of claim 1, wherein the electrophysiological signal is a pulse signal obtained by a sensor.

3. The method for blood pressure measurement of claim 2, wherein the sensor is a vibrating pulse sensor or an optical sensor.

4. The method for blood pressure measurement of claim 1, wherein the numerical method is a finite element method.

5. The method for blood pressure measurement of claim 1, wherein the optimization algorithm is a genetic algorithm, a neural network algorithm, or an intelligent algorithm.

6. The method for blood pressure measurement of claim 1, wherein the basic personal information includes age, height, weight, gender, body fat ratio, or information contained in cloud electronic medical records.

7. The method for blood pressure measurement of claim 1, wherein the default model parameters include vascular wall thickness, vessel diameter, vessel density, blood vessel elasticity, blood concentration, blood density, blood viscosity coefficient, blood flow, blood flow field pressure, muscle elasticity and density, elasticity and density of the bones, skin elasticity, or elasticity and density of all the tissues from the wrist continuously extending to the heart.

8. The method for blood pressure measurement of claim 1, wherein the human physiological parameter is systolic blood pressure, diastolic blood pressure, or heart rate.

9. A computer program product for executing the method for blood pressure measurement of claim 1 after being loaded into a machine.

10. A computer-readable recording media, within which a computer program is stored, the computer program, after being loaded into a machine, executing the method for blood pressure measurement of claim 1.

11. A system for blood pressure measurement, comprising:

a measuring unit for measuring an electrophysiological signal and including a user interface for basic personal information to be input thereon; and

a computing unit connected with the measuring unit via a network for receiving the electrophysiological signal and the basic personal information, the computing unit including;

a modeling module for establishing a personalized cardiovascular model based on the electrophysiological signal and the basic personal information through a numerical method, wherein the personalized cardiovascular model includes default model parameters and is configured to create a human physiological parameter; and

an optimization module for calibrating the default model parameters through an optimization algorithm to re-establish the personalized cardiovascular model, such that the human physiological parameter created by the re-established personalized cardiovascular model matches the measured electrophysiological signal.

12. The system for blood pressure measurement of claim 11, wherein the measuring unit is a vibrating pulse sensor or an optical sensor.

13. The system for blood pressure measurement of claim 11, wherein the network is a wireless LAN, an infrared or Bluetooth wireless network, or a wired network.

14. The system for blood pressure measurement of claim 11, wherein the numerical method is a finite element method.

15. The system for blood pressure measurement of claim 11, wherein the optimization algorithm is a genetic algorithm, a neural network algorithm, or an intelligent algorithm.

16. The system for blood pressure measurement of claim 11, wherein the computing unit further includes a database module for storing the electrophysiological signal, the basic personal information and the personalized cardiovascular model.

17. The system for blood pressure measurement of claim 11, wherein the computing unit is a personal computer or a cloud server.

18. The system for blood pressure measurement of claim 11, wherein the basic personal information includes age, height, weight, gender, body fat ratio, or information contained in cloud electronic medical records.

19. The system for blood pressure measurement of claim 11, wherein the default model parameters include the vascular wall thickness, vessel diameter, vessel density, blood vessel elasticity, blood concentration, blood density, blood viscosity coefficient, blood flow, blood flow field pressure, muscle elasticity and density, elasticity and density of the bones, skin elasticity, or elasticity and density of all the tissues from the wrist continuously extended to the heart.

20. The system for blood pressure measurement of claim 11, wherein the human physiological parameter is systolic blood pressure, diastolic blood pressure, or heart rate.