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Radar-based heart rate analysis method and equipment

An analysis method and heart rate technology, applied in the computer field, can solve problems such as interference, insufficient sensitivity, and strong interference, and achieve the effects of improving equipment practicability, simplifying circuit design, and strong anti-interference

Pending Publication Date: 2022-02-18
珠海脉动时代健康科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] (1) The sensitivity is not enough. The millimeter-wave radar can detect the movement of a few tenths of a millimeter, while the movement caused by the heartbeat is 0.1 to 0.5mm (chest), 0.01 to 0.2mm (back);
[0006] (2) There is a lot of interference and strong interference. For the detection of breathing and heart rate, the movement of the trunk and limbs of the human body is a strong interference, speaking and blinking are also strong interference, as well as intestinal peristalsis, muscle shaking, etc.;
[0007] (3) Non-contact measurement has disadvantages. Non-contact measurement is originally the advantage of millimeter-wave radar, but non-contact measurement itself has disadvantages. The radar wave is emitted from the transmitting antenna and passes through a space to reach the object to be measured. After reflection, it passes through a space to reach the receiving antenna. The whole propagation process introduces various interferences, as well as the influence of reflectivity and reflection area;
[0008] (4) Software and hardware technology is not yet mature

Method used

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  • Radar-based heart rate analysis method and equipment

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Embodiment approach

[0050] The present invention provides the following embodiments, including:

[0051] The design of the fully convolutional neural network uses the deep learning framework tensorflow, the code is as follows:

[0052] input_layer = keras.layers.Input(input_shape)

[0053] / / convolutional layer

[0054] conv1=keras.layers.Conv1D(filters=128, kernel_size=8, padding='same')(input_layer)

[0055] / / batch normalization layer

[0056] conv1 = keras.layers.BatchNormalization()(conv1)

[0057] / / non-linear activation layer

[0058] conv1 = keras.layers.Activation(activation='relu')(conv1)

[0059] conv2=keras.layers.Conv1D(filters=256, kernel_size=5, padding='same')(conv1)

[0060] conv2 = keras.layers.BatchNormalization()(conv2)

[0061] conv2 = keras.layers.Activation('relu')(conv2)

[0062] conv3=keras.layers.Conv1D(128, kernel_size=3, padding='same')(conv2)

[0063] conv3 = keras.layers.BatchNormalization()(conv3)

[0064] conv3 = keras.layers.Activation('relu')(conv3)

...

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Abstract

The invention relates to a technical scheme of a radar-based heart rate analysis method and equipment, and the method comprises the steps of: acquiring heart rate data of a plurality of different positions collected by a millimeter wave radar device, and carrying out de-noising processing on the heart rate data to obtain de-noised waveform data; creating a full convolutional neural network, and training the full convolutional neural network to obtain a heart rate detection model; calculating a sample entropy for the de-noised waveform data; adjusting the millimeter wave radar device to obtain the de-noised waveform data of multiple different positions to calculate the sample entropy, and selecting the position with the minimum sample entropy for continuous heart rate monitoring. The method and the equipment provided by the invention have the advantages that: the practicability of the equipment for monitoring the heart rate through the millimeter wave radar is greatly improved, and the accuracy of heart rate detection is improved.

Description

technical field [0001] The invention relates to the field of computers, in particular to a radar-based heart rate analysis method and equipment. Background technique [0002] Millimeter wave (mmWave) is a special radar technology that uses short-wavelength electromagnetic waves. Millimeter wave radar can emit signals with wavelengths on the order of millimeters. In the electromagnetic spectrum, such wavelengths are considered short wavelengths and are one of the advantages of the technology. Admittedly, the size of the system components (such as antennas) required to process mmWave signals is indeed small. Another advantage of short wavelengths is high accuracy. Millimeter-wave systems operating at frequencies of 76–81 GHz (corresponding to a wavelength of about 4 mm) will be able to detect movements as small as a few tenths of a millimeter. [0003] The breathing and heartbeat of the human body are a kind of mechanical movement in a macroscopic view. The breathing moveme...

Claims

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Application Information

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IPC IPC(8): A61B5/024A61B5/00
CPCA61B5/7264A61B5/7267A61B5/7203A61B5/726A61B5/7257A61B5/024A61B5/02438A61B5/725Y02A90/10
Inventor 金瑞军符文剑刘庆才段明勇
Owner 珠海脉动时代健康科技有限公司
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