Comparison of end-to-end neural network architectures and data augmentation methods for automatic infant motility assessment using wearable sensors

HIGHLIGHTS

• who: Manu Airaksinen and colleagues from the BABA Center, Pediatric Research Center, Children`s Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland have published the research: Comparison of End-to-End Neural Network Architectures and Data Augmentation Methods for Automatic Infant Motility Assessment Using Wearable Sensors, in the Journal: Sensors 2023, 23, 3773. of /2023/
• what: This study investigates the use of different end-to-end neural network for processing infant motility from wearable sensors. The authors focus on the performance and computational burden of alternative sensor encoder and time series modeling modules . . .
  

   

  

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