Method of measuring taste using two phase radial basis function neural networks, a taste sensor, and a taste measuring apparatus
US7899765B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 22, 2006 |
| Grant date | Mar 1, 2011 |
| Priority date | — |
| Expiry date | Dec 14, 2027 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01N33/14
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A method for measuring tastes, which can better simulate the human gustation than known methods, as well as a taste sensor, computer program and an apparatus for measuring tastes, is disclosed. In this method, data processing is carried out by a two-phase radial basis function neural network. That is, by sensors, each of which sensors can quantify at least one component representing, individually or cooperatively, the taste of saltiness, sourness, sweetness, umami or bitterness, to obtain a response value from each sensor, and each of the obtained response values is input to a first phase radial basis function neural network to calculate the concentration of each component from each response value. Then, the concentration of each component is fed into a second phase radial basis function neural network, which correlates the concentration of each component with the intensities of saltiness, sourness, sweetness, umami and bitterness sensed by humans, to calculate the intensities of saltiness, sourness, sweetness, umami and bitterness sensed by humans.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.