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Near-infrared brain function signal extracting method based on least square support vector machine

A technology of support vector machine and least squares, applied in diagnostic recording/measurement, medical science, sensors, etc., can solve the problems of low detection accuracy of near-infrared brain function activity signal, error interference of brain function activity signal, etc.

Inactive Publication Date: 2016-09-28
HARBIN INST OF TECH
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Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of error interference in the brain function activity signal obtained by adopting the adaptive filtering technology based on the multi-distance measurement method when the physiological interference and the brain function signal frequency band are seriously overlapped, resulting in low detection accuracy of the near-infrared brain function activity signal problem, and proposed a near-infrared brain function signal extraction method based on recursive least squares adaptive filtering and least squares support vector machine

Method used

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  • Near-infrared brain function signal extracting method based on least square support vector machine
  • Near-infrared brain function signal extracting method based on least square support vector machine
  • Near-infrared brain function signal extracting method based on least square support vector machine

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specific Embodiment approach 1

[0064] Specific implementation mode one: combine figure 1 and figure 2 To illustrate this embodiment, the method for extracting near-infrared brain function signals based on the least squares support vector machine of this embodiment is specifically prepared according to the following steps:

[0065] Step 1: Place a dual-wavelength light source S and detector D on the surface of the scalp of the brain tissue to be tested 1 and detector D 2 A near-infrared probe composed of a dual-wavelength light source S and a detector D 1 The straight-line distance between 1 , dual-wavelength light source S and detector D 2 The straight-line distance between 2 , the dual-wavelength light source S emits two kinds of near-infrared light with wavelengths λ 1 and lambda 2 , detector D 1 and detector D 2 It is used to obtain the diffuse reflection light intensity in the quiet state of the brain and the diffuse reflection light intensity in the brain-induced excitation state, so as to ob...

specific Embodiment approach 2

[0135] Specific embodiment two: the difference between this embodiment and specific embodiment one is: 5mm1 2 <40mm;

[0136] Among them, R 1 For the dual-wavelength light source S and detector D 1 The straight-line distance between; R 2 For the dual-wavelength light source S and detector D 2 the distance between.

[0137] Other steps and parameters are the same as those in Embodiment 1.

specific Embodiment approach 3

[0138] Specific embodiment three: the difference between this embodiment and specific embodiment one or two is: the R 1 10mm, R 2 is 40mm. Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.

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Abstract

A method for extracting near-infrared brain function signals based on a least squares support vector machine, the invention relates to a method for extracting near-infrared brain function signals. The purpose of the present invention is to solve the problem of low detection accuracy of near-infrared brain function activity signals. The specific process is called: 1: Obtain the time signal of the optical density change of two near-infrared lights of different wavelengths at different distances; 2: Obtain the time signal of the concentration change of oxygenated hemoglobin and the time signal of the concentration change of reduced hemoglobin; 3: Obtain the time signal of the change in the concentration of oxygenated hemoglobin Brain function activity signal; four: get W of W(t) * (t); Five: Get the brain function activity signal E(t): Six: Get the brain function activity signal after eliminating the error interference; Seven: Construct the Lagrangian function to get the linear equation system; Eight: Solve the linear equation system to get La The numerical solution of the Grangian multiplier vector α and the offset b, at this time, the brain function activity signal processed by the least squares support vector machine regression function is expressed as E * (t). The invention is used for brain function signal extraction.

Description

technical field [0001] The invention relates to a method for extracting near-infrared brain function signals. Background technique [0002] Near-infrared spectroscopy can provide information on blood oxygen metabolism in the cerebral cortex during brain functional activities by detecting changes in the concentration of oxyhemoglobin and reduced hemoglobin in the cerebral cortex, so as to detect the state of brain functional activity. Compared with other brain function detection methods such as functional magnetic resonance imaging, positron emission tomography, and electroencephalography, near-infrared spectroscopy has the advantages of being economical, safe, non-invasive, convenient to use, and easy to implement. However, when using near-infrared spectroscopy to detect brain function activities, physiological activities such as human heartbeat, breathing, human low-frequency oscillations, and human ultra-low-frequency oscillations will interfere with the measurement signal...

Claims

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Application Information

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IPC IPC(8): A61B5/1455A61B5/00
CPCA61B5/14553A61B5/0075A61B5/4064A61B5/7203A61B5/7221A61B5/7225A61B5/7235A61B5/7271
Inventor 刘昕张岩刘丹王启松孙金玮
Owner HARBIN INST OF TECH
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