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公开(公告)号:US20180192923A1
公开(公告)日:2018-07-12
申请号:US15866972
申请日:2018-01-10
发明人: Yongji Fu , Ibne Soreefan , Alexander Sheung Lai Wong , Mohammad Javad Shafiee , Brendan James Chwyl , Audrey Gina Chung
IPC分类号: A61B5/11
CPC分类号: A61B5/1128 , A61B5/1115 , A61B5/743 , G08B21/22
摘要: A method for monitoring a patient in a bed may involve capturing images of the patient with multiple cameras in a vicinity of the bed, wirelessly transmitting the images of the patient from the multiple cameras to a processor including a memory device, processing the images to provide processed image data pertaining to a position of the patient relative to the bed to a user, and analyzing the processed image data to determine whether the patient is exiting the bed. The method may also optionally involve providing an alarm indicating that the patient is exiting the bed.
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公开(公告)号:US10321856B2
公开(公告)日:2019-06-18
申请号:US15866972
申请日:2018-01-10
发明人: Yongji Fu , Ibne Soreefan , Alexander Sheung Lai Wong , Mohammad Javad Shafiee , Brendan James Chwyl , Audrey Gina Chung
摘要: A method for monitoring a patient in a bed may involve capturing images of the patient with multiple cameras in a vicinity of the bed, wirelessly transmitting the images of the patient from the multiple cameras to a processor including a memory device, processing the images to provide processed image data pertaining to a position of the patient relative to the bed to a user, and analyzing the processed image data to determine whether the patient is exiting the bed. The method may also optionally involve providing an alarm indicating that the patient is exiting the bed.
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公开(公告)号:US11074802B2
公开(公告)日:2021-07-27
申请号:US15883754
申请日:2018-01-30
发明人: Alexander Sheung Lai Wong , Yongji Fu , Brendan James Chwyl , Audrey Gina Chung , Mohammad Javad Shafiee
摘要: A method and apparatus for predicting hospital bed exit events from video camera systems is disclosed. The system processes video data with a deep convolutional neural network consisting of five main layers: a 1×1 3D convolutional layer used for generating feature maps from raw video data, a context-aware pooling layer used for rectifying data from different camera angles, two fully connected layers used for applying pre-trained deep features, and an output layer used to provide a likelihood of a bed exit event.
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