An Intelligent Model for Bispectral Index (BIS) in Patients Undergoing General Anesthesia

  1. José Luis Casteleiro-Roca 1
  2. Juan Albino Méndez Pérez 2
  3. José Antonio Reboso-Morales 2
  4. Cos Juez, Francisco Javier de 3
  5. Francisco Javier Pérez-Castelo 1
  6. José Luis Calvo-Rolle 1
  1. 1 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

  2. 2 Universidad de La Laguna
    info

    Universidad de La Laguna

    San Cristobal de La Laguna, España

    ROR https://ror.org/01r9z8p25

  3. 3 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

Erakutsi afiliazioak +
Liburua:
International Joint Conference SOCO’16-CISIS’16-ICEUTE’16: San Sebastián, Spain, October 19th-21st, 2016 Proceedings
  1. Manuel Graña (coord.)
  2. José Manuel López-Guede (coord.)
  3. Oier Etxaniz (coord.)
  4. Álvaro Herrero (coord.)
  5. Héctor Quintián (coord.)
  6. Emilio Corchado (coord.)

Argitaletxea: Springer Suiza

ISBN: 978-3-319-47364-2,  3-319-47364-6,  978-3-319-47363-5,  3-319-47363-8

Argitalpen urtea: 2017

Orrialdeak: 290-300

Biltzarra: International Conference on Computational Intelligence in Security for Information Systems (9. 2016. San Sebastián)

Mota: Biltzar ekarpena

DIALNET GOOGLE SCHOLAR

Laburpena

Nowadays, the engineering tools play an important role inmedicine, regardless of the area. The present research is focused in anesthesiology, specifically on the behavior of sedated patients. The work shows the Bispectral Index Signal (BIS) modeling of patients undergoing general anesthesia during surgery. With the aim of predicting the patient BIS signal, a model that allows to know its performance from the Electromyogram (EMG) and the propofol infusion rate has been created. The proposal has been achieved by using clustering combined with regression techniques and using a real dataset obtained from patients undergoing general anesthesia. Finally, the created model has been tested also with data from real patients, and the results obtained attested the accuracy of the model.

Datuen iturria: Dialnet