Apparatus and method for analyzing information relating to physical and mental condition
First Claim
1. An apparatus for analyzing a physiological fluctuation signal of a subject to determine at least one psychological condition of the subject, the apparatus comprising a neural network receiving the physiological fluctuation signal as an input for estimating physiological conditions using frequency variations, wherein said neural network is an hourglass type neural network, training of the hourglass type neural network carried out by supplying the physiological fluctuation signal to both an input and an output of the hourglass type neural network, output values of an intermediate layer of the hourglass type neural network representing at least one psychological condition.
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Abstract
An apparatus and method are provided for analyzing information relating to the physiological and psychological conditions of a driver. Psychological conditions such as comfortableness or degree of alertness are estimated on the basis of physical data such as fluctuation in brain waves. This apparatus comprises a first neural network having a pre-processed 1/f fluctuation signal for brain waves as an input and for estimating a degree of alertness of the driver, and a second neural network receiving the estimated degree of alertness and the pre-processed 1/f fluctuation signal, for estimating and outputting driving comfortableness. By employing a neural network, which has a mapping ability as well as flexible adaptability even for non-linear data, based on the learning function, more accurate estimation of mental conditions can be achieved in comparison with conventional statistical analysis.
43 Citations
16 Claims
- 1. An apparatus for analyzing a physiological fluctuation signal of a subject to determine at least one psychological condition of the subject, the apparatus comprising a neural network receiving the physiological fluctuation signal as an input for estimating physiological conditions using frequency variations, wherein said neural network is an hourglass type neural network, training of the hourglass type neural network carried out by supplying the physiological fluctuation signal to both an input and an output of the hourglass type neural network, output values of an intermediate layer of the hourglass type neural network representing at least one psychological condition.
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7. An apparatus for analyzing information relating to physiological and psychological conditions comprising a neural network receiving a preprocessed EEG fluctuation signal of a subject as an input for estimating physiological conditions of the subject, wherein said neural network comprises:
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a first neural network receiving the pre-processed EEG fluctuation signal as an input for estimating a degree of alertness; and a second neural network receiving the degree of alertness estimated by the first neural network and the pre-processed EEG fluctuation signal as inputs for estimating comfortableness, to estimate both alertness and comfortableness as psychological conditions. - View Dependent Claims (8)
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10. A method for analyzing information relating physiological and psychological conditions, comprising:
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applying a physiological fluctuation signal to a neural network; and estimating psychological conditions using frequency variations; wherein said neural network is an hourglass type neural network, training of the hourglass type neural network carried out by supplying the physiological fluctuation signal to both an input and an output of the hourglass type neural network, output values of an intermediate layer of the hourglass type neural network representing the psychological conditions. - View Dependent Claims (11, 12, 13)
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15. A method for analyzing information relating physiological and psychological conditions, comprising:
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applying a physiological fluctuation signal of a subject to a neural network, the physiological fluctuation signal including a pre-processed EEG fluctuation signal of the subject; applying the pre-processed EEG fluctuation signal to an alertness estimation portion of the neural network to estimate alertness; and applying the estimated alertness and the pre-processed EEG fluctuation signal to a comfortableness estimation portion of the neural network to estimate both alertness and comfortableness as the psychological conditions. - View Dependent Claims (16)
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Specification