公开(公告)号：US20180181833A1

公开(公告)日：2018-06-28

申请号：US15506708

申请日：2015-08-25

Applicant: AGENCY FOR SCIENCE, TECHNOLOGY AND RESEARCH

Inventor： Fengshou YIN ,  Wing Kee Damon WONG ,  Jiang LIU ,  Beng Hai LEE ,  Zhuo ZHANG ,  Kavitha GOPALAKRISHNAN ,  Ying QUAN ,  Al Ping YOW

IPC: G06K9/46 ,  G06K9/00 ,  G06K9/03 ,  G06T7/00 ,  A61B3/00 ,  A61B3/12 ,  A61B3/14

CPC classification number: G06K9/4676 ,  A61B3/0025 ,  A61B3/12 ,  A61B3/14 ,  A61B2576/02 ,  G06K9/0061 ,  G06K9/036 ,  G06K9/6269 ,  G06K2009/00932 ,  G06K2209/05 ,  G06T7/0012 ,  G06T7/0014 ,  G06T2207/20081 ,  G06T2207/30041 ,  G06T2207/30168

Abstract: A method of assessing the quality of an retinal image (such as a fundus image) includes selecting at least one region of interest within a retinal image corresponding to a particular structure of the eye (e.g. the optic disc or the macula), and a quality score is calculated in respect of the, or each, region-of-interest. Each region of interest is typically one associated with pathology, as the optic disc and the macula are. Optionally, a quality score may be calculated also in respect of the eye as a whole (i.e. over the entire image, if the entire image corresponds to the retina).

公开(公告)号：US20220172023A1

公开(公告)日：2022-06-02

申请号：US17599148

申请日：2019-03-29

Applicant: AGENCY FOR SCIENCE, TECHNOLOGY AND RESEARCH

Inventor： Haihong ZHANG ,  Huijuan YANG ,  Zhuo ZHANG ,  Chuan Chu WANG ,  Dajiang HE ,  Kai Keng ANG

IPC: G06N3/04 ,  G06N3/12

Abstract: Disclosed is a system and method for measuring a non-stationary brain signal. Per the method, the system receives brain signals, extracts one or more features from the brain signals, determines, based on the Receive brain signals extracted one or more features, a super feature set describing dynamic behaviour of the brain signals, and forms a cluster-recurrent-neural-network (CRNN) from one or more samples taken from the super feature set, by formExtract one or more features ing at least one cluster of the one or more samples based on the one or more from the brain signals features, to estimate a brain state of interest in each cluster of brain signals; using a Monte Carlo approach to estimate an a posteriori probability density function of the brain state of interest by applying the CRNN to each cluster of the at least one cluster; and determining the brain state of interest from the estimated density function.

公开(公告)号：US20170360362A1

公开(公告)日：2017-12-21

申请号：US15533372

申请日：2015-12-07

Applicant: AGENCY FOR SCIENCE, TECHNOLOGY AND RESEARCH

Inventor： Zhuo ZHANG ,  Cuntai GUAN ,  Hai Hong ZHANG ,  Huijuan YANG

IPC: A61B5/00 ,  A61B5/0476 ,  A61B5/04

CPC classification number: A61B5/4812 ,  A61B5/04012 ,  A61B5/0476 ,  A61B5/7264 ,  A61B5/7267

Abstract: A method for profiling sleep of an individual is provided. The method includes defining a sleep feature space for the individual, measuring a brain wave for the individual during the individual's sleep, and mapping the sleep feature space in response to a comparison of the brain wave and a previous brain wave measurement used to define the sleep feature space. The brain wave may comprise a brain wave spectrum. The sleep feature space may comprise, or be composed of, spectral power and envelope measures. The method also includes modelling the mapped sleep feature space in response to recognized neural network patterns corresponding to each of a plurality of sleep stages derived from recognizing the neural network patterns from the sleep feature space and deriving a sleep profile for the individual from sleep stages determined in response to the modelled mapped sleep feature space and the brain wave of the individual.