Identificação da Doença de Alzheimer Através da Fala Utilizando Reconhecimento de Emoções

Autores

  • Guilherme Bernieri Military Institute of Engineering – IME
  • Julio Cesar Duarte Military Institute of Engineering – IME

DOI:

https://doi.org/10.59681/2175-4411.v15.iEspecial.2023.1093

Palavras-chave:

Alzheimer Disease, Automatic Speech Analysis, Machine Learning

Resumo

Alzheimer's disease is the most common neurodegenerative dementia in elderly people in the world and its diagnosis requires a wide medical evaluation, supported by cognitive tests, clinical and imaging exams. Identifying the disease through speech can reduce the cost and time of medical diagnosis. Emotional states are important performance indicators of cognitive processes. Intelligent and non-invasive computational techniques can become relevant support tools for an early medical diagnosis. Therefore, this article addresses the use of emotion recognition through voice as a biomarker to identify the presence of Alzheimer's disease. The proposed method is based on the extraction of emotional features from speech and pattern recognition using neural networks. The results of the experiments reached an accuracy of 72.61%, a precision of 72.90% and a recall of 72.50% through cross-validation of the data.

Biografias Autor

Guilherme Bernieri, Military Institute of Engineering – IME

Master's Student, Military Institute of Engineering – IME, Rio de Janeiro (RJ), Brazil.

Julio Cesar Duarte, Military Institute of Engineering – IME

Professor, Military Institute of Engineering – IME, Rio de Janeiro (RJ), Brazil.

Referências

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Publicado

2023-07-20

Como Citar

Bernieri, G., & Duarte, J. C. (2023). Identificação da Doença de Alzheimer Através da Fala Utilizando Reconhecimento de Emoções. Journal of Health Informatics, 15(Especial). https://doi.org/10.59681/2175-4411.v15.iEspecial.2023.1093

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