Method for classifying sensory substances based on olfactory brain waves and GS-SVM

A GS-SVM and brain wave technology, applied in sensors, medical science, diagnostic recording/measurement, etc., can solve the problems of doping with subjective factors, poor repeatability, and inability to fully reflect the real feeling of the human body, and achieve a simple and simple sensory evaluation process. more normative effect

Inactive Publication Date: 2018-08-17
NORTHEAST DIANLI UNIVERSITY
View PDF5 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

With the development of science and technology, more and more precision instruments for analyzing flavor substances have emerged as the times require, but relying on instrumental analysis alone cannot fully reflect the real feeling of the human body, so the sensory evaluation of the human body still occupies an important position
In the process of sensory evaluation, personnel are required to personally participate in the use of sensory organs such as vision, smell, and taste. They are easily disturbed by daily habits and eating conditions. The sensory evaluation results given are mixed with personal Subjective factors, so it has a certain degree of subjectivity and poor repeatability

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for classifying sensory substances based on olfactory brain waves and GS-SVM
  • Method for classifying sensory substances based on olfactory brain waves and GS-SVM
  • Method for classifying sensory substances based on olfactory brain waves and GS-SVM

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0022] Materials and methods: 3 different brands of beer (Tsingtao, Cordon Bleu, Harbin) were selected, and their alcohol concentrations and raw materials are shown in Table 1 below:

[0023] Table 1 Samples of 3 different brands of beer

[0024]

[0025] In terms of olfactory EEG signal analysis, the EEG signals used are self-collected data in the laboratory. After the original EEG signals are collected, EEG preprocessing is performed first (including deleting bad areas, filtering out 50Hz power frequency interference, and superimposing data. average, wavelet transform, etc.); then perform linear analysis and nonlinear analysis on it, and use the peak value, mean value, standard deviation, center value, center frequency, power sum, and LZC complexity obtained by sub-frequency bands as eigenvalues; considering the acquisition The electrodes contain different regions, so the electrode screening is carried out; finally, the selected feature values ​​are sent to the correspond...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a method for classifying sensory substances based on olfactory brain waves and GS-SVM, which comprises the following steps of: S1, utilizing brain-computer interface system, i.e., the brain electric instrument, to acquire the electroencephalogram spectrum information of the subject; S2, preprocessing the acquired EEG spectrum data; S3, performing feature extraction on thepreprocessed atlas data based on the linear characteristic and the nonlinear characteristic analysis, 76-dimensional data including peak, mean, standard deviation, center value, center frequency, power sum and LZC complexity of alpha, beta, theta frequency bands are used as brain electrical characteristics in the study of brain electrical signals; S4, adopting a network format search support vector machine (GS-SVM) for pattern recognition. According to the method for classifying sensory substances based on olfactory brain waves and GS-SVM, the physiological morphology of the human brain information processing process in the product evaluation process is truly restored, which has extremely important significance in the fields of clinical medicine and cognitive science and can be widely usedin the sensory evaluation of substances, making the sensory evaluation process more concise, more standardized, precise and scientific.

Description

technical field [0001] The invention relates to the technical field of sensory substance classification, in particular to a method for sensory substance classification based on olfactory brain waves and GS-SVM. Background technique [0002] Sensory evaluation is an interdisciplinary subject that is gradually developed and matured by modern physiology, psychology, statistics and other disciplines. In the entire evaluation system, sensory professionals are involved in the development of new products, basic research, adjustment of ingredients and processes, It plays a decisive role in the evaluation of cost reduction, quality assurance and product optimization. With the development of science and technology, more and more precision instruments for analyzing flavor substances have emerged as the times require. However, only relying on instrumental analysis cannot fully reflect the real feeling of the human body, so the sensory evaluation of the human body still occupies an impor...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0484A61B5/048A61B5/374
CPCA61B5/7253A61B5/374A61B5/381
Inventor 门洪焦雅楠石岩巩芙榕刘晶晶房海瑞韩晓菊姜文娟
Owner NORTHEAST DIANLI UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products