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Effective heart rate measuring system capable of resisting natural motion of head

A kind of heart rate, natural technology, applied in the field of effective heart rate measurement system, can solve the problem of not requiring face, inactivity, measurement accuracy impact, etc.

Active Publication Date: 2019-05-03
YANGO UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0002] In recent years, the use of computer vision technology to measure physiological signals such as heart rate has attracted widespread attention because it is cheap and suitable for long-term monitoring. This method uses an ordinary cheap camera to obtain vital signs from the face to measure heart rate. Generally speaking, this The method is to obtain a region of interest (Region of Interest; ROI) from the face, and then use the Fast Fourier Transform (Fast Fourier Transform) to obtain the frequency spectrum to calculate the heart rate. However, this method usually needs to be manually defined on the face A fixed ROI, and the subject's face is required to be still; if the face moves, the measurement accuracy will be seriously affected. This method is not suitable for real application situations, because even if the person is still, There will still be natural movement of the head, especially if you want to monitor and measure heart rate for a long time, you can't ask the person's face to face the camera without moving

Method used

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  • Effective heart rate measuring system capable of resisting natural motion of head
  • Effective heart rate measuring system capable of resisting natural motion of head
  • Effective heart rate measuring system capable of resisting natural motion of head

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Experimental program
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Effect test

Embodiment 1

[0031] see image 3 , an efficient heart rate measurement system that resists natural head movements, comprising the following steps:

[0032] Step 1: Detect and track the face and facial feature points. The face detection is obtained by using the HOG (Histogram of Oriented Gradient) feature and the classifier SVM (Support Vector Machine), and then use the shape predictor to estimate Measure 68 feature points of the face. Face tracking uses the golden ratio of the standard human face to design a search box and narrow the search range to improve the tracking speed. The 68 feature points are distributed on the eyes, mouth, nose and face contour of the face, and the golden ratio map of the face ( image 3 ) must know that the width of a human face is about 5 eye widths W EYE , and the height is about 3 bridge lengths W N , the width of the right eye W RE =d(36,39), left eye width W LE =d(42,45),W EYE =0.5(W RE +W LE ); the height of the bridge of the nose W N =d(33,E), ...

Embodiment 2

[0049] The experiment was carried out on 15 test subjects respectively, and each test subject carried out 20 measurements, a total of 300 measurement results. The test subjects were all yellow people with different skin tones. The video uses a normal webcam with a resolution of 640x480. There are many variations and difficulties in these videos, including changes in camera angles and shooting distances, and the environment of the testees is disturbed by different degrees of light.

[0050] The heart rate C measured by the system i Heart rate G measured with a reference device i , Find the mean and standard deviation of all test records, and calculate C i with G i The correlation coefficient (correlation) and absolute error are as follows

[0051] Correlation coefficient:

[0052] Absolute error:

[0053] The optimal position is automatically selected from three ROI positions: the forehead and the left and right cheeks. In order to test this adaptive ROI technology, t...

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Abstract

The invention discloses an effective heart rate measuring system capable of resisting natural motion of the head. The effective heart rate measuring system comprises two processing units, wherein a first unit is used for obtaining stable ROIs, a photographic lens is opened, real-time images are converged, the system can automatically detect and trace human faces and face feature points, and afterthe human faces are detected, a search frame is narrowed according to a human face golden ratio so as to increase the tracing speed; and the positions of regions of interest ROIs are respectively designed on foreheads, right cheeks and left cheeks, the pose (pose) of head motion is judged through the face feature points, accordingly the appropriate ROI is automatically selected, and through motionwave filtering, stable ROI signals are obtained. The second unit is used for processing heart rate signals, the ROI signals are firstly preprocessed, green channels are taken out from the ROIs to besubjected to pixel averaging, the average value of each time point is in series connection to form a time sequence signal, then through standardization processing, the influence of ray changes on thequality of the signals is eliminated, main signals are highlighted, and through quick Fourier transformation and bandpass filtering processing, heartbeat data can be calculated.

Description

technical field [0001] The present invention relates to a heart rate measurement system, in particular to an effective heart rate measurement system which can resist the natural movement of the head. Background technique [0002] In recent years, the use of computer vision technology to measure physiological signals such as heart rate has attracted widespread attention because it is cheap and suitable for long-term monitoring. This method uses an ordinary cheap camera to obtain vital signs from the face to measure heart rate. Generally speaking, this The method is to obtain a region of interest (Region of Interest; ROI) from the face, and then use the Fast Fourier Transform (Fast Fourier Transform) to obtain the frequency spectrum to calculate the heart rate. However, this method usually needs to be manually defined on the face A fixed ROI, and the subject's face is required to be still; if the face moves, the measurement accuracy will be seriously affected. This method is n...

Claims

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Application Information

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IPC IPC(8): A61B5/024
Inventor 张容娟谢朝和王琨刘大茂
Owner YANGO UNIV
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