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Patent Searching and Data


Title:
SIGNAL PROCESSING DEVICE AND METHOD
Document Type and Number:
WIPO Patent Application WO/2023/286313
Kind Code:
A1
Abstract:
The present art relates to a signal processing device and method that can improve robustness against noise of emotion estimation. A signal processing device extracts, as a feature value on the basis of a measured biological signal, a physiological index contributing to an emotion, outputs, for time series data on the feature value, time series data on the prediction label of an emotion status according to an identification model constructed in advance, and outputs an emotion estimation result on the basis of the result of a weighted sum performed on the prediction label by using a prediction label reliability that is the reliability of the prediction label. The present art can be applied to emotion estimation systems.

Inventors:
HYODO YASUHIDE (JP)
Application Number:
PCT/JP2022/007140
Publication Date:
January 19, 2023
Filing Date:
February 22, 2022
Export Citation:
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Assignee:
SONY GROUP CORP (JP)
International Classes:
A61B5/16
Domestic Patent References:
WO2018218286A12018-12-06
WO2017199597A12017-11-23
Foreign References:
JP2020203051A2020-12-24
JP2020048622A2020-04-02
JP2021053261A2021-04-08
JP2019170967A2019-10-10
Other References:
VAL-CALVOMIKEL ET AL.: "Optimization of real-time EEG artifact removal and emotion estimation for human-robot interaction applications", FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, vol. 13, 2019, Retrieved from the Internet
AFTANAS, L. I., S. A. GOLOCHEIKINE: "Human anterior and frontal midline theta and lower alpha reflect emotionally positive state and internalized attention: high-resolution EEG investigation of meditation.", NEUROSCIENCE LETTERS, vol. 310, no. 1, 2001, pages 57 - 60
BENEDEK, M.KAERNBACH, C.: "A continuous measure of phasic electrodermal activity", JOURNAL OF NEUROSCIENCE METHODS, vol. 190, 2010, pages 80 - 91, XP027106841
SALAHUDDINLIZAWATI ET AL., ULTRA SHORT TERM ANALYSIS OF HEART RATE VARIABILITY FOR MONITORING MENTAL STRESS IN MOBILE SETTINGS, 2007
LAWHERNVERNONW. DAVID HAIRSTONKAY ROBBINS: "DETECT: A MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in the EEG signals", PLOS ONE, vol. 8.4, 2013, pages 62944
KHATWANIMOHIT ET AL.: "Energy efficient convolutional neural networks for eeg artifact detection", IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS, 2018
Attorney, Agent or Firm:
NISHIKAWA Takashi et al. (JP)
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