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Shopping decision-making method based on brain-computer interaction

A decision-making method and brain-computer interaction technology, applied in the field of shopping decision-making based on brain-computer interaction, can solve the problems of difficult to choose goods, spend a lot of time, and it is difficult to determine one's favorite goods, etc., to achieve convenient browsing, accurate Evaluate and ensure the effectiveness of timeliness

Active Publication Date: 2018-12-04
NANJING UNIV OF POSTS & TELECOMM
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although online shopping has brought convenience to people, the large number of products also makes it more difficult for people to choose when choosing, and it may take a lot of time to determine their favorite products.

Method used

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  • Shopping decision-making method based on brain-computer interaction

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Embodiment 1

[0024] refer to figure 1 , in the embodiment of the present invention, a shopping decision-making method based on brain-computer interaction is provided. The method judges the user's preference for the product based on the EEG signal data of the user's selection of items on the e-commerce platform, and is applied to e-commerce The product recommendation function of the platform, the EEG signal data is collected by EEG equipment, and the method includes the steps of:

[0025] S1. Collect and store the EEG signal data of the user when browsing a product on the e-commerce platform through the EEG device;

[0026] Preferably, the present invention uses a non-invasive EEG device to collect the EEG signal data when the user browses the product when the user enters the desired purchase on the e-commerce platform. Compared with the invasive EEG device, this non-invasive EEG device , the user can directly wear it on the head to collect the EEG signals of the scalp, which is more non-i...

Embodiment 2

[0057] The shopping decision-making method based on brain-computer interaction of the present invention will be described below according to specific embodiments; first, the user logs in to the Taobao account and wears an EEG device, preferably an EEG device with electrodes developed by a neurotechnology company in San Francisco, California, USA. The special hat Emotiv Insight is taken as an example. Emotiv Insight is equipped with five electrodes AF3, AF4, T7, T8 and Pz; The original EEG data is transmitted through wireless Bluetooth, and the receiving end uses the official standard USB Dongle for data reception; the user enters the product he wants to buy; and assuming that the product entered by the user is pants, the user is collected through the EEG device Emotiv Insight The original EEG data of the five electrode channels AF3, AF4, T7, T8 and Pz, and record the EEG data set D of the user’s current browsing pants. Here, the styles of pants include Harem pants, cropped pant...

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Abstract

The invention discloses a shopping decision-making method based on brain-computer interaction. The method can determine the user's preference for a commodity on the basis of EEG signal data of the user selecting an item in the e-commerce platform, and is applied to a commodity recommendation function of the e-commerce platform. The method comprises the following steps: acquiring the EEG signal data of the user through an EEG device and recording and storing the EEG signal data; using a band pass filter and the independent component analysis method to preprocess the EEG signal data, and performing extracting to obtain the sample entropy; obtaining a feature vector based on the sample entropy, using the Naive Bayes method to identify different emotions, and setting the excitement level for each of different emotions; using the average energy ratio method to extract features, and performing normalization to obtain a concentration value; and finally obtaining the matching degree when the user browses a corresponding commodity according to the excitement level and the concentration value, setting a threshold Th, comparing the matching degree and the threshold Th, and recommending the corresponding commodity to the user according to the comparison result. The method improves the shopping experience and shopping efficiency of the user, and facilitates selection.

Description

technical field [0001] The invention belongs to the interdisciplinary field of EEG signal processing and e-commerce technology, and in particular relates to a shopping decision-making method based on brain-computer interaction. Background technique [0002] In today's era of rapid development of the mobile Internet, online shopping has become the first choice for many people to shop. Although online shopping has brought convenience to people, the vast amount of products also makes it more difficult for people to choose when choosing, and it may take a lot of time to determine their favorite products. The classification and recognition of human emotions through the physiological signals of the human body provides a new way to solve the above problems. [0003] A brain-computer interface is a pathway for transmitting information between the brain and external devices. The brain-computer interface recognizes people's thinking by collecting and extracting the EEG signals gener...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06Q30/06
CPCG06Q30/06G06F2218/02G06F2218/08G06F18/29
Inventor 黄海平刘永双刘茜萍张佳宁程琨杜安明胡振超李家东
Owner NANJING UNIV OF POSTS & TELECOMM
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