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A Robust Estimation Method of Near Infrared Brain Function Signals Based on Multi-range Measurement Method and Least Square Criterion

A measurement method and robust estimation technology, applied in diagnostic recording/measurement, medical science, sensors, etc., can solve the problems of eliminating useful information loss, aliasing part gross error, etc.

Inactive Publication Date: 2016-05-11
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For data that is not an outlier, false elimination will also lose useful information
make the unavoidable aliasing part gross error in the measurement signal

Method used

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  • A Robust Estimation Method of Near Infrared Brain Function Signals Based on Multi-range Measurement Method and Least Square Criterion
  • A Robust Estimation Method of Near Infrared Brain Function Signals Based on Multi-range Measurement Method and Least Square Criterion
  • A Robust Estimation Method of Near Infrared Brain Function Signals Based on Multi-range Measurement Method and Least Square Criterion

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Experimental program
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specific Embodiment approach 1

[0019] Specific Embodiment 1: The method for robust estimation of near-infrared brain function signals based on the multi-distance measurement method and the least square criterion of this embodiment is specifically prepared according to the following steps:

[0020] Step 1. Use a near-infrared probe composed of a light source S and two detectors D1 and D2 to detect the position of the brain tissue to be measured;

[0021] Step 2: Detecting the diffuse reflection light intensity signal and transforming it through a photoelectric sensor to obtain an electrical signal reflecting light intensity information;

[0022] Step 3. The electrical signal obtains the time series △[HbO 2 ] N (k) and time series of changes in reduced hemoglobin concentration △[HHb] N (k), time series △[HbO 2 ] F (k) and time series of changes in reduced hemoglobin concentration △[HHb] F (k);

[0023] Step 4. Use x(k) to express △[HbO 2 ] N (k) or △[HHb] N (k);

[0024] Step 5. Use y(k) to express ...

specific Embodiment approach 2

[0030] Specific embodiment 2. The difference between this embodiment and specific embodiment 1 is that the light source S described in step 1 adopts an integrated dual-wavelength near-infrared light source, and the linear distance between the light source S and the near-end detector D1 is r 1 ; The linear distance between the light source S and the far-end detector D2 is r 2 .

[0031] Other steps and parameters are the same as those in Embodiment 1.

specific Embodiment approach 3

[0032] Embodiment 3: The difference between this embodiment and Embodiment 1 or 2 is that the two wavelengths emitted by the dual-wavelength near-infrared light source are λ 1 =760nm,λ 2 = 850nm.

[0033] Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.

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Abstract

The invention relates to a signal robust estimation method, in particular to a near-infrared brain function signal robust estimation method based on a multi-distance measurement method and a least absolute deviation criterion. The invention aims to solve the problem that the current gross error seriously impacts the accurate extraction of brain function signals. The method comprises the following steps of step 1, using a light source S and a near-infrared probe formed by a D1 and a D2 to detect; step 2, obtaining an electric signal respond to light intensity information; step 3, acquiring delta [HbO2] <N> (k) and delta [HHb] <N> (k) measured by the D1, and delta [HbO2] <F> (k) and delta [HHb] <F> (k) measured by the D2; step 4, expressing the delta [HbO2] <N> (k) or the delta [HHb] <N> (k) in terms of x(k); step 5, expressing the delta [HbO2] <F> (k) or the delta [HHb] <F> (k) in terms of y(k); step 6, expressing the brain function signal in a way that s (k) is equal to y(k) minus beta x(k); step 7, utilizing the least absolute deviation criterion to solve a weight coefficient beta which enables J(k) to be the smallest, obtaining an error performance function J(k), and expressing the J (k) as shown in the specification; step 8, obtaining the brain function signal s(k). The near-infrared brain function signal robust estimation method based on the multi-distance measurement method and the least absolute deviation criterion is applied in the signal processing field.

Description

technical field [0001] The invention relates to a signal robustness estimation method, in particular to a near-infrared brain function signal robustness estimation method based on a multi-distance measurement method and a least one multiplication criterion. Background technique [0002] Near-infrared spectroscopy can be used for changes in oxyhemoglobin concentration in the cerebral cortex Δ[HbO 2 ] and reduced hemoglobin concentration change Δ[HHb] signal measurement, to further expand the analysis of brain function activity signals. However, in the detection of brain function and activity by near-infrared spectroscopy, the light intensity signal is often affected by instrument noise, environmental interference, and experimental factors. For the processing of outliers, the elimination strategy is usually adopted. However, only obvious outliers can be detected. For data that is not an outlier, false elimination will also lose useful information. This makes the unavoidable...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/0476
Inventor 张岩刘丹杨春玲张国亮孙金玮
Owner HARBIN INST OF TECH
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