Brain Wave Ranking Device for Objective Product Preference Analysis
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Solution Overview
Problem
Conventional brain wave analysis methods face challenges in accurately estimating emotional intensity and predicting purchase actions due to subjective bias and variations in brain wave patterns, failing to objectively rank research objects like products or brands effectively.
Innovation Solution
A device and method that analyze event-related electrical potentials to quantify brain responses to research objects, using pattern classification and discriminant analysis to rank their responsiveness, eliminating subjective influence by presenting stimuli multiple times and measuring brain waves immediately after each presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If questionnaire research is used to measure emotional intensity, then subjective bias is introduced, but the reliability and accuracy of research results deteriorate
Solution Approach 1:
The patent replaces the mechanical/questionnaire-based measurement system with an electrophysiological measurement system. Instead of relying on self-reported questionnaire data that is susceptible to subjective bias, the invention uses EEG (electroencephalography) to directly measure brain wave patterns and event-related potentials, thereby eliminating the harmful factor of subjective bias while maintaining measurement precision.
Solution Approach 2:
The patent introduces brain wave patterns and event-related potentials as intermediary indicators to indirectly measure emotional intensity. Rather than directly asking subjects about their emotions (which introduces bias), the invention uses brain wave characteristics as a mediator that objectively reflects emotional states, thereby improving measurement accuracy without subjective contamination.
2Measurement precision
If brain wave data is analyzed using general correlation methods, then processing time increases, but measurement precision remains insufficient due to individual variations
Solution Approach 1:
The patent segments the brain wave data analysis into distinct components, specifically isolating event-related potentials (such as P300, N200, P100 components) from general brain wave patterns. By focusing on these specific time-locked potentials that occur at predetermined time points after stimulus presentation, the invention achieves both high measurement precision for individual emotion estimation and efficient processing time through targeted analysis rather than comprehensive data processing.
Solution Approach 2:
The patent performs preliminary action by pre-defining the time windows and characteristics of event-related potentials before actual data analysis. The analysis protocol specifies predetermined time points (e.g., 100-300ms for P300) and filtering criteria in advance, allowing for rapid processing during actual measurement without time-consuming exploratory analysis, thereby maintaining both precision and efficiency.
3Object-affected harmful factors
If brain information map visualization is generated without questionnaire research, then subjective bias is eliminated, but the ability to predict future purchase actions remains insufficient
Solution Approach 1:
The patent introduces dynamic analysis by measuring event-related potentials that change over time in response to different stimulus types and presentation conditions. Rather than using static brain wave patterns or fixed questionnaire responses, the invention captures dynamic brain responses that evolve during the decision-making process, thereby improving the reliability of predicting future purchase actions while maintaining elimination of subjective bias through objective physiological measurement.
Solution Approach 2:
The patent implements feedback mechanisms by analyzing event-related potentials that provide real-time information about a subject's cognitive and emotional processing during stimulus evaluation. The measured brain wave patterns serve as feedback about the subject's internal state, which can then be used to predict future behaviors and purchase actions with higher reliability, while the objective measurement method continues to eliminate subjective bias.
Data Source
AI summary
A device, a system, a method, and a program are realized which are capable of predicting the order of the feeling and the preference of a subject to products which are the research objects, for marketing research and others. The images of a plurality of research objects are presented a plurality of times as visual stimuli in order to measure the brain wave. A brain wave data of an event related electrical potential for the research objects which the subject has selected as a target immediately after the stimulus presentation, is processed by a linear discriminant analysis to quantitatively represent with a single index, in order to rank the research objects.