In this paper, a method of concurrent recording and regeneration of visual and olfactory information is presented using electronic nose technology. To accomplish this objective, the sensor response patterns of odors in the atmosphere were measured using QCM (quartz crystal microbalance) odor sensors with partially overlapping specificities. Then the odors were identified from the response patterns using LVQ (learning vector quantization), a pattern classification algorithm of neural networks with supervised learning. Visual information, presented as a movie, was captured using a digital video camera; concurrently, odors using odor sensor responses were paired to the video. The recorded visual and olfactory information was evaluated by sensory tests to investigate the effectiveness of the proposed system. As a result, it was found that the olfactory information recorded using the proposed method was appropriate for odor regeneration associated with the movie.

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