Casteleiro-Roca, José-LuisJove, EstebanGonzález-Cava, José M.Méndez Pérez, Juan AlbinoCalvo-Rolle, José LuisBlanco Álvarez, Francisco2025-06-102025-06-102020-03Casteleiro-Roca, JL., Jove, E., Gonzalez-Cava, J.M. et al. Hybrid model for the ANI index prediction using Remifentanil drug and EMG signal. Neural Comput & Applic 32, 1249–1258 (2020). https://doi.org/10.1007/s00521-018-3605-z1433-3058http://hdl.handle.net/2183/42263[Abstract] With the aim to control and reduce the pain of patients during a surgery with general anesthesia, one of the main challenges is the proposal of safe an optimal and efficient methods of drugs administering. First step to achieve this goal is the proposal and development of right indexes that correlate satisfactory with analgesia. One of this index gives the most hopeful results is the Analgesia Nociception Index (ANI). The present research work deals the ANI response of patients during surgeries with general anesthesia with intravenous drug infusion. The main aim is to predict the ANI signal behavior regarding of the analgesic infusion rate. To do that, a hybrid intelligent model is developed, using clustering and regression techniques based on artificial neural networks and support vector regression. The proposal was validated with a dataset of surgeries real cases of patients undergoing general anesthesia. The achieved results attest for the potential of the proposed technique.engThis version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00521-018-3605-zElectroMyoGram signal (EMG)Analgesia Nociception Index (ANI)Multi-layer perceptron (MLP)Support vector regression (SVRjournal articleopen accesshttps://doi.org/10.1007/s00521-018-3605-z