Optimization of an artificial neural network for predicting stress in robot-assisted laparoscopic surgery based on EDA sensor data.

Journal: International journal of computer assisted radiology and surgery
Published Date: May 20, 2025

Abstract

PURPOSE: This study aims to optimize tunable hyperparameters of the multilayer perceptron (MLP) setup. The optimization procedure is aimed at more accurately predicting potential health risks to the surgeon during robotic-assisted surgery (RAS).

Authors

  • Daniel Caballero
    Bioengineering and Health Technologies Unit, Jesús Usón Minimally Invasive Surgery Center, Cáceres, Spain.
  • Manuel J Pérez-Salazar
    Bioengineering and Health Technologies Unit, Jesús Usón Minimally Invasive Surgery Center, Cáceres, Spain.
  • Juan A Sánchez-Margallo
    Bioengineering and Health Technologies Unit, Jesús Usón Minimally Invasive Surgery Center, Cáceres, Spain. jasanchez@ccmijesususon.com.
  • Francisco M Sánchez-Margallo
    Jesús Usón Minimally Invasive Surgery Centre, Ctra. N-521, km 41.8, 10071 Cáceres, Spain. Electronic address: msanchez@ccmijesususon.com.

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