Device and method for detecting attention focusing degree based on analysis of heart rate variability

Abstract

The invention discloses a device and a method for detecting attention focusing degree based on the analysis of heart rate variability, mainly solving the problems of large interference and inconvenient testing of reference signals for attention judgment in the prior art. The method comprises the following testing steps: acquiring original electrocardiographic digital signals according to a MV5 lead mode; filtering the interference in the original electrocardiographic digital signals, extracting the position of a R wave and calculating heart rate variability signals; integrating and segmentingthe heart rate variability signals; performing empirical mode decomposition on each segment of the heart rate variability signals; calculating the approximate entropy of the heart rate variability signals and intrinsic mode function component signals; training a neutral network by using the calculated approximate entropy as an input vector of a reverse transmit neural network algorithm, and determining the parameters of codes of a neutral network; and detecting the attention focusing degree of a subject by utilizing the trained neutral network and outputting the test result. The invention hasthe advantages of large reference signal strength, convenient test and high accuracy, and is used for testing the attention focusing degree of a human body.

Description

technical field [0001] The invention belongs to the technical field of information processing and relates to medical information processing, in particular to a method of extracting human heart rate variation HRV signals and performing signal processing and cluster analysis to finally complete the judgment of the degree of concentration. The invention can be used to quantitatively determine whether children or adults are concentrating, and also provides a basis for medical clinical diagnosis of ADD or quantitative evaluation of treatment effects. Background technique [0002] Concentration is an important prerequisite for normal study and work, but some people cannot effectively control their attention. ADD, the most common behavioral disorder in childhood, is a typical example. It is generally believed that ADD is a disease between the intersection of psychology and physiology, also known as a physical and mental disease, characterized by poor selectivity and stability of a...

AI Technical Summary

Problems solved by technology

These methods of extracting attention states based on EEG analysis have the following defects, which limit their wide application in clinic

[0004] (1) The EEG signal is weak, and the influence of various interferences on the signal is very significant. In addition, various factors such as mental state, neuropsychiatric disease, blood pressure and even eye closure will affect the waveform of the EEG, and the effective analysis of the EEG The methods are still being explored, and the accuracy of the attention measurement method based on EEG analysis has yet to be verified

[0005] (2) It is very inconvenient to place multiple electrodes on the human head during the test. In order to measure accurately, it is often required to shave part of the hair. The use of electrode conductive paste makes it necessary to wash the hair immediately after the test, which is very troublesome.

[0006] (3) EEG amplification devices are expensive, which makes attention measurement and feedback correction equipment based on EEG analysis relatively expensive, making it difficult for home users

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