Application for evaluation machine
Utilization of brain waves in the succession of skilled skills ~ Next-generation interface that directly reads thoughts and emotions from the brain ~
Introduction
In recent years, artificial intelligence and machine learning technologies are advancing in all fields. In addition, the advent of deep learning has dramatically improved recognition performance, and it is now being used in various ways such as autonomous driving, personal authentication, and time-series data prediction.
In this paper, from the perspective of passing on skilled skills, in addition to image analysis and natural language analysis, which are widely applied in the field of deep learning, we focus on electroencephalography (EEG), which is a method of reading information in the brain from brain activity signals, which has been actively studied in recent years. I would like to introduce the possibilities and benefits of AI while touching on it.
What is EEG
In this paper, I will explain the merits of the electroencephalogram method compared to various approaches in skill transfer, but first I will explain what an electroencephalogram is.
Brain waves are wave-like signals caused by the activity of more than 100 billion brain cells in the human brain. The frequency is mainly from 0.5Hz to 30Hz, and these are usually analyzed quantitatively using a method called frequency analysis.
In addition, by measuring evoked potentials called event-related potentials that respond to external visual stimuli, it becomes possible to decipher higher brain functions such as selection and judgment.
Image classification by EEG
We provide a system that performs high-speed classification/annotation of target images (= meaning of images) based on brain waves called event-related potentials mentioned above.
In the case of an airport case, it is used as a system that instantly extracts images when a skilled inspector recognizes dangerous goods from X-ray images of baggage that are projected one after another. By using this system, it is possible to constantly create the latest AI model while picking up abnormal data that is difficult to explain in words at high speed and in real time.
Significance of EEG utilization in skill inheritance
In recent years, many methods have been released as services that help with the succession of skilled skills and process automation. For example, image analysis AI can detect small flaws and differences in shape that the human eye misses.
Recently, failure prediction services that predict anomalies based on various data, such as sound and vibration, have increased in addition to automatic image anomaly detection. However, not all appearance inspections can be easily automated. It is possible to quantify the clear differences between good and defective products, such as scratches and dents, and build a system, but qualitative differences such as color unevenness and impressions are subjective judgments by inspectors. It is very difficult to set a baseline for this because
High-quality training data is necessary to create a highly accurate AI model, but for busy skilled workers, the annotation work to give meaning to each data is an extremely heavy burden.
This work is often outsourced, but judgments by outsiders who do not fully understand the company's business and products may create a gap with the level of requirements on the site side.
As a countermeasure to these issues, by implementing annotation work using brain waves, it is not necessary to express the judgments of skilled technicians in words, and it is possible to create training data at high speed while ensuring the quality of judgments. I can. We also obtain the degree of certainty at the time of judgment from the electroencephalogram, and change the weight during learning (the degree of influence on the machine learning process) according to the degree of certainty. You can create an AI model that is close to judgment.
Points unique to electroencephalogram analysis
Electroencephalogram (EEG) analysis has a unique feature that conventional image analysis and natural language analysis do not have. It is extremely useful in that it can process human reactions to various types of information such as auditory, gustatory, olfactory, and tactile information in addition to visual information. A unique method.
Many of the tasks that experts usually do by feeling are difficult to verbalize, but in the case of the electroencephalogram approach, it is possible to directly measure reactions in the brain without verbalizing it, so it is attracting attention in the skill inheritance of experts. We are here. In recent years, its use in neuromarketing applications has also increased.
In methods such as questionnaire surveys aimed at design evaluation, cognitive biases such as "sympathy bias" are applied, making it impossible to make independent decisions and unconsciously agree with the opinions of the majority of people around you. However, it is possible to make a more quantitative evaluation by directly obtaining feedback from the EEG before such subjective bias is applied.
free demonstration
Guidance of the demonstration
Would you like to actually measure brain waves?
What is the "skill transfer of experts" based on brain waves? What is AI that learns human consciousness and judgment?
I think there are a lot of unknown things, so why not try measuring your brain waves first and experience what it's like?
After the actual measurement, we will provide support from proposals to implementation and operation so that we can use AI using EEG at the customer's site while including examples of AI utilization in our activities so far. increase.
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