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A method and system for detecting methamphetamine addicts based on multi-channel fnirs signal

A detection method and multi-channel technology, applied in pattern recognition in signals, instruments, complex mathematical operations, etc., can solve the problems that ice addicts are difficult to detect and cannot detect drug abuse, so as to improve detection accuracy and reduce detection the effect of time

Active Publication Date: 2021-11-05
SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional urine and blood testing methods mainly judge whether a person is taking drugs by detecting the components in human urine or blood. However, after a period of time, the components in urine and blood return to normal after the normal metabolism of the human body. whether it takes drugs
Therefore, traditional methods can only detect people who have recently used methamphetamine, but it is difficult to accurately detect people who have not been exposed to methamphetamine for a long time

Method used

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  • A method and system for detecting methamphetamine addicts based on multi-channel fnirs signal
  • A method and system for detecting methamphetamine addicts based on multi-channel fnirs signal
  • A method and system for detecting methamphetamine addicts based on multi-channel fnirs signal

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Embodiment 1

[0068] The embodiment of the present invention discloses a method for detecting methamphetamine based on the mutual information value of multi-channel fNIRS signals, including calculating the mutual information value between the fNIRS signals of each channel of two types of subjects; The mutual information value of the tester is used as a classification feature, which is sent to the machine learning algorithm, and the machine learning model is trained. The tester's fNIRS signal is extracted in real time through the multi-channel fNIRS channel, and the tester's multi-channel fNIRS signal is obtained and saved. After performing various preprocessing operations on the fNIRS signals of each channel, the mutual information value between the fNIRS signals of each channel of the tester is calculated, and sent to the trained classifier as an input to obtain the detection result. Based on brain nerve signals, this scheme overcomes the shortcomings of traditional methamphetamine detectio...

Embodiment 2

[0095] The difference between this embodiment and Embodiment 1 is that in this embodiment, the skewness of the multi-channel signal is calculated, and then the skewness indexes of the channels with significant differences are constructed into feature vectors, which are sent to the machine learning algorithm to implement classification.

[0096] Specifically, in this embodiment, 8, 9, 31, 35, 37, and 42 are selected, such as Figure 5 As shown, the six channels are located in the frontal, central, and parietal lobes, respectively.

[0097] When performing feature extraction, the skewness of each derivative fNIRS data in the data set of the S2 stimulus response of the two groups of people after the preprocessing is calculated respectively. In this embodiment, after the calculation of the skewness of each derivative fNIRS data is completed, the The respective skewness matrices (144 × 6) of the two types of subjects of addiction and health, that is, each skewness matrix contains d...

Embodiment 3

[0107] The difference between this embodiment and Embodiment 1 is that: this embodiment calculates the phase-lock value between multi-channel signals, and then constructs a feature vector from the phase-lock value adjacency matrix of the channels with significant differences, and sends it to the machine learning algorithm. Implement classification.

[0108] Specifically, this embodiment selects 3, 9, 18, 27, 36, 37, 40, a total of 7 channels, such as Figure 5 As shown, the seven channels are located in the frontal and central regions, respectively. The frontal lobe is responsible for high-level cognitive activities such as judgment, planning, decision-making, thinking, and memory, and is closely related to intelligence and mental activities; the central area has a somatosensory cortex, which can sense somatic information.

[0109] During feature extraction, the phase-lock values ​​of the data sets of the S2 stimulus responses of the two groups of people after the above prepr...

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Abstract

The invention relates to a method and system for detecting methamphetamine addicts based on multi-channel fNIRS signals. The fNIRS signals of the testers are extracted in real time through the multi-channel fNIRS channels, and the multi-channel fNIRS signals of the testers are obtained and stored; After the signal is preprocessed, calculate the mutual information value, skewness value or phase-locked value of each channel fNIRS signal, and construct a mutual information adjacency matrix, a skewness matrix or a phase-locked value adjacency matrix; the mutual information adjacency matrix, Skewness matrix or phase-locked value adjacency matrix is ​​sent to the classifier as input to obtain the detection result. Based on brain nerve signals, this solution overcomes the shortcomings of traditional methamphetamine detection and proposes a new method for methamphetamine detection, which greatly increases the effective time of detection. Finally, after testing, the detection accuracy has also been greatly improved.

Description

technical field [0001] The invention relates to the technical field of feature detection, in particular to a method and system for detecting ice drug addicts based on multi-channel fNIRS signals. Background technique [0002] Crystal methamphetamine entered China in the 1990s. Due to the lack of awareness of methamphetamine and the lack of effective detection methods, it is very difficult to detect drug addicts. [0003] The main component of meth is methamphetamine, also known as methamphetamine. Because the higher purity meth is a transparent crystal, which is very similar to rock sugar, it is also called meth. Excessive use of methamphetamine will not only make people highly dependent, but also cause symptoms such as methamphetamine psychosis and schizophrenia. At present, the detection methods for methamphetamine (meth) are mostly urine and blood tests. Traditional urine and blood testing methods mainly judge whether a person is taking drugs by detecting the components...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06K9/00G06F17/16
CPCG06F17/16G06F2218/04G06F2218/08G06F2218/12G06F18/214
Inventor 高军峰张家琦宋健魏曙光黎峰韦思宏黄伟安曾宣威康倩若湛慧苗
Owner SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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