ROBOT-BASED AUTISM DIAGNOSIS DEVICE USING ELECTROENCEPHALOGRAM AND METHOD THEREFOR
    1.
    发明申请
    ROBOT-BASED AUTISM DIAGNOSIS DEVICE USING ELECTROENCEPHALOGRAM AND METHOD THEREFOR 审中-公开
    基于机器人的电动诊断装置使用电化学及其方法

    公开(公告)号:US20140323901A1

    公开(公告)日:2014-10-30

    申请号:US14360743

    申请日:2012-10-22

    CPC classification number: A61B5/04842 A61B5/0484 A61B5/04845 A61B5/04847

    Abstract: The present invention relates to a robot-based autism diagnosis device using an electroencephalogram and to a method therefor. The invention comprises: an electroencephalogram signal detector which is worn on or attached to the head of a child showing signs of autism and detects an electroencephalogram signal generated following an event which is provided; and a robot for diagnosing the degree of autism on receiving the electroencephalogram signal detected by the electroencephalogram signal detector. In the invention, a relatively accurate judgment is made as to whether autism is present, and autism diagnosis is achieved at an early stage such that autistic children can receive treatment for the signs of autism at an early stage.

    Abstract translation: 本发明涉及使用脑电图的基于机器人的自闭症诊断装置及其方法。 本发明包括:脑电波信号检测器,其佩戴在或附着到显示自闭症迹象的儿童的头部,并检测在提供的事件之后产生的脑波信号; 以及用于在接收由脑波信号检测器检测到的脑波信号时诊断自闭症程度的机器人。 在本发明中,对自闭症是否存在进行了比较准确的判断,并且早期实现了自闭症诊断,以便自闭症儿童能够早期接受自闭症的治疗。

    Semantic map production system and method

    公开(公告)号:US11557137B2

    公开(公告)日:2023-01-17

    申请号:US17410824

    申请日:2021-08-24

    Abstract: The system includes a metric map creation unit configured to create a metric map using first image data received from a 3D sensor, an image processing unit configured to recognize an object by creating and classifying a point cloud using second image data received from an RGB camera; a probability-based map production unit configured to create an object location map and a spatial semantic map in a probabilistic expression method using a processing result of the image processing unit, a question creation unit configured to extract a portion of high uncertainty about an object class from a produced map on the basis of entropy and ask a user about the portion, and a map update unit configured to receive a response from the user and update a probability distribution for spatial information according to a change in probability distribution for classification of the object.

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