Computação afetiva no contexto da musicoterapia: uma revisão sistemática
DOI:
https://doi.org/10.33448/rsd-v10i15.22844Palavras-chave:
Computação afetiva; Reconhecimento de emoções; Estimulação acústica; Sistema de recomendação; Musicoterapia.Resumo
A musicoterapia é uma ferramenta eficaz para retardar o progresso da demência, uma vez que a interação com a música pode evocar emoções que estimulam as áreas do cérebro responsáveis pela memória. Essa terapia é mais bem-sucedida quando o terapeuta fornece estímulos adequados e personalizados para cada paciente. Essa personalização costuma ser difícil. Assim, métodos de Inteligência Artificial (IA) podem auxiliar nessa tarefa. Este artigo traz uma revisão sistemática da literatura da área de computação afetiva no contexto da musicoterapia. Em particular, pretendemos avaliar métodos de IA para realizar o reconhecimento automático de emoções aplicados a Interfaces Musicais Homem-Máquina (HMMI). Para realizar a revisão, realizamos uma busca automática em cinco das principais bases de dados científicas nas áreas de computação inteligente, engenharia e medicina. Procuramos todos os artigos publicados entre 2016 e 2020, cujos metadados, título ou resumo contenham os termos definidos na string de pesquisa. O protocolo de revisão sistemática resultou na inclusão de 144 trabalhos das 290 publicações retornadas da pesquisa. Através desta revisão do estado da arte, foi possível elencar os desafios atuais no reconhecimento automático de emoções. Também foi possível perceber o potencial do reconhecimento automático de emoções para construir soluções assistivas não invasivas baseadas em interfaces musicais homem-máquina, bem como as técnicas de inteligência artificial em uso no reconhecimento de emoções a partir de dados multimodais. Assim, o aprendizado de máquina para reconhecimento de emoções de diferentes fontes de dados pode ser uma abordagem importante para otimizar os objetivos clínicos a serem alcançados por meio da musicoterapia.
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