Therapies customization by emotion recognition in biosignals

Authors

  • Maíra Araújo de Santana Universidade de Pernambuco
  • Wellington Pinheiro dos Santos Universidade Federal de Pernambuco

DOI:

https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1315

Keywords:

Emotion-Focused Therapy, Music Therapy, Artificial Intelligence

Abstract

Goal: This study aimed to develop a hybrid artificial neural network architecture to recognize mood states in biosignals from elderly individuals, including those with mild to moderate dementia, to support the personalization of therapies. Method: The study employed Wavelet Transform to convert signals into images, used as input for a hybrid architecture comprising a pre-trained convolutional neural network of LeNet type for feature extraction, and a Random Forest algorithm with 450 trees for classification. The performance of the proposed algorithm was evaluated on publicly available databases of electroencephalography and voice signals, and subsequently validated on an in-house database of elderly individuals with and without dementia. Results: The achieved accuracy ranged from 71% to 73%. Conclusion: This technology can be integrated into human-machine interfaces to personalize various therapies, such as music therapy.

Author Biographies

Maíra Araújo de Santana, Universidade de Pernambuco

Doutora em Engenharia da Computação, Universidade de Pernambuco, Recife (PE), Brasil.

Wellington Pinheiro dos Santos, Universidade Federal de Pernambuco

Professor do departamento de Engenharia Biomédica, Universidade Federal de Pernambuco, Recife (PE), Brasil.

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Published

2024-11-19

How to Cite

de Santana, M. A., & dos Santos, W. P. (2024). Therapies customization by emotion recognition in biosignals. Journal of Health Informatics, 16(Especial). https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1315

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