Robust ppg peak detection using dilated convolutional neural networks

HIGHLIGHTS

• who: Kianoosh Kazemi and collaborators from the Department of Computing, Faculty of Technology, University of Turku, Turku, Finland have published the article: Robust PPG Peak Detection Using Dilated Convolutional Neural Networks, in the Journal: Sensors 2022, 22, 6054. of /2022/
• what: The authors propose a CNN-based peak determination approach for PPG signals with different levels of motion artifacts. The authors develop a generator function to produce PPG signals with a wide range of noise, augmenting the training data and creating noisy signals similar to real-life PPG records. Study participation was entirely voluntary, and . . .
  

   

  

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