Analysis of EEG Signals in a Patient with Spastic Cerebral Palsy Undergone Dolphin-Assisted Therapies

Oswaldo Morales Matamoros, Erika Yolanda Aguilar del Villar, Abril Pérez Sánchez, Jesús Jaime Moreno Escobar, Ricardo Tejeida Padilla

Research output: Contribution to journalArticlepeer-review

Abstract

Cerebral palsy is a group of developmental disorders that affects a certain percentage of population motivating the development of several types of therapies ranging from conventional where physical therapies are included to some alternative therapies such as the dolphin-assisted therapies (DAT), in order to improve the quality of life of patients suffering these disorders. To find scientific evidence of the DAT effectiveness, in this work is developed a four-stage first-order cybernetic model: i) Signal Acquisition, ii) EEG Processing, iii) EEG Exploring and iv) Healthcare Informatics System (HIS-DAT), in order to explore the electroencephalographic signals behavior from a patient with Infantile Spastic Cerebral Palsy undergone DAT, as well as bioacoustic signals emitted by a female bottlenose dolphin via specialized transducers or passive sensors for aquatic environments, by using nonlinear mathematical tools. We found that the Power Spectrum of signals from EEG and Hydrophone yield similar densities along all DAT and the child’s brain activity increases 3-fold higher-frequency when the therapist-dolphin pair interacts with the patient. These findings are supported by the Self-Affine Analysis outcomes, pointing out the emergence of negative correlations from the patient’s brain activity during the whole session of DAT but the greatest changes occurred During DAT.

Original languageEnglish
Pages (from-to)918-929
Number of pages12
JournalInternational Journal of Advanced Computer Science and Applications
Volume13
Issue number12
DOIs
StatePublished - 2022

Keywords

  • Analysis of eeg signals
  • Assisted therapies
  • Brain–computer interfaces
  • Healthcare system
  • Infantile spastic cerebral palsy
  • Nonlinear dynamics
  • Power spectrum
  • Self-affine analysis

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