Emotion Anlayzer is a simple solution for analyzing emotions (Interest, Like, Stress, Concentration, Calmness, Negative, Comfortable, Refresh β, Appetite β) from brainwaves.
With only one headgear and one iPad, the user can perform measurments and visualize results anywhere. Data can also be exported in CSV format.
Results can be used for product development, benefit creation, evidence making, and PR.
It can be used for various purposes in accordance with your business, including research, demonstration experiments, sales promotions, and PR.
Emotion Analyzer is an unique and cutting-edge solution, which allows mobile, realtime use and at low-cost. It is based on the original algorithm developed by intensive research.
Its potential usage varies greatly from conventional brainwave devices.
"This algorithm is designed based on a biometric database amassed by professor Mitsukura over 15 years, and allows you to estimate emotions.
The device can simply classify emotions into 'interest,' 'like,' 'stress,' 'concentration,' 'calmness,' 'negative,' 'comfortable,' 'refresh β,' and 'appetite β.'"
"One of the features of electroencephalograms (EEG) is that it shows and visualizes changes in emotions by an excellent time resolution.
Noise arising from body motion and myoelectric factors is removed by a noise filter implemented in the application."
Previously, neural marketing research incurred huge costs in general, due to the need for special and expensive equipments.
It was also common to spend vast amounts of time, even under the joint research.
Licensing to use the Emotion Analyzer is time-based, meaning you may use it as much as you like during the license period.
"The saved emotion data is time-stamped by the second, and can be exported as csv files.
By using simultaneous video recording, emotion data can be synchronized with video to check which particular actions generated stimulii.
Furthermore, comments may be added, which simplify post-experiment checking."
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The service is limited only for the company capitalized more than 10 million YEN.
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