| Texto completo | |
| Autor(es): |
Mano, Leandro Y.
[1, 2]
;
Barros, Vinicius A.
[1, 3]
;
Nunes, Luiz H.
[4]
;
Sawada, Luana O.
[5]
;
Estrella, Julio C.
[1]
;
Ueyama, Jo
[1]
Número total de Autores: 6
|
| Afiliação do(s) autor(es): | [1] Univ Sao Paulo, Inst Math & Comp Sci, Sao Paulo - Brazil
[2] Univ Groningen, Johann Bernoulli Inst Math & Comp Sci, Groningen - Netherlands
[3] Inst Pesquisas Eldorado, Campinas - Brazil
[4] Fed Inst Sao Paulo, Sao Paulo - Brazil
[5] Florida Int Univ, Sch Comp & Informat Sci, Miami, FL 33199 - USA
Número total de Afiliações: 5
|
| Tipo de documento: | Artigo Científico |
| Fonte: | MOBILE INFORMATION SYSTEMS; v. 2019, JUL 10 2019. |
| Citações Web of Science: | 1 |
| Resumo | |
Owing to the increase in the number of people with disabilities, as a result of either accidents or old age, there has been an increase in research studies in the area of ubiquitous computing and the Internet of Things. They are aimed at monitoring health, in an efficient and easily accessible way, as a means of managing and improving the quality of life of this section of the public. It also involves adopting a Health Homes policy based on the Internet of Things and applied in smart home environments. This is aimed at providing connectivity between the patients and their surroundings and includes mechanisms for helping the diagnosis and prevention of accidents and/or diseases. Monitoring gives rise to an opportunity to exploit the way computational systems can help to determine the real-time emotional state of patients. This is necessary because there are some limitations to traditional methods of health monitoring, for example, establishing the behavior of the user's routine and issuing alerts and warnings to family members and/or medical staff about any abnormal event or signs of the onset of depression. This article discusses how a layer-based architecture can be used to detect emotional factors to assist in healthcare and the prevention of accidents within the context of Smart Home Health. The results show that this process-based architecture allows a load distribution with a better service that takes into account the complexity of each algorithm and the processing power of each layer of the architecture to provide a prompt response when there is a need for some intervention in the emotional state of the user. (AU) | |
| Processo FAPESP: | 17/21054-2 - Combinando Inteligência Artificial e Multimodal para Emoção Classificação |
| Beneficiário: | Leandro Yukio Mano Alves |
| Modalidade de apoio: | Bolsas no Exterior - Estágio de Pesquisa - Doutorado |
| Processo FAPESP: | 16/14267-7 - Explorando Internet das Coisas e Inteligência Artificial no contexto de Saúde em Casas Inteligentes: uma abordagem física e emocional |
| Beneficiário: | Leandro Yukio Mano Alves |
| Modalidade de apoio: | Bolsas no Brasil - Doutorado |