A computer vision-based respiratory rate monitoring and alarm system
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This study proposed a breathing rate monitoring strategy using a mono camera to track and detect sleep apnea phenomena. Breathing rates were first tracked among consecutive image frames. The human body area was then isolated and magnified using a deep neural network (DNN) model before applying the optical flow algorithm to extract and monitor the up and down changes caused by respiration.
Nội dung trích xuất từ tài liệu:
A computer vision-based respiratory rate monitoring and alarm system
Nội dung trích xuất từ tài liệu:
A computer vision-based respiratory rate monitoring and alarm system
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Computer vision-based Breathing rate detection Sleep apnea Optical flow Principal component analysisGợi ý tài liệu liên quan:
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