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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Ribeiro, G., Monge, J., Postolache, O. & Pereira, J. M. D. (2024). A novel AI approach for assessing stress levels in patients with type 2 diabetes mellitus based on the acquisition of physiological parameters acquired during daily life. Sensors. 24 (13)
Exportar Referência (IEEE) 
G. T. Ribeiro et al.,  "A novel AI approach for assessing stress levels in patients with type 2 diabetes mellitus based on the acquisition of physiological parameters acquired during daily life", in Sensors, vol. 24, no. 13, 2024
Exportar BibTeX 
@article{ribeiro2024_1722097342291,
	author = "Ribeiro, G. and Monge, J. and Postolache, O. and Pereira, J. M. D.",
	title = "A novel AI approach for assessing stress levels in patients with type 2 diabetes mellitus based on the acquisition of physiological parameters acquired during daily life",
	journal = "Sensors",
	year = "2024",
	volume = "24",
	number = "13",
	doi = "10.3390/s24134175",
	url = "https://www.mdpi.com/journal/sensors"
}
Exportar RIS 
TY  - JOUR
TI  - A novel AI approach for assessing stress levels in patients with type 2 diabetes mellitus based on the acquisition of physiological parameters acquired during daily life
T2  - Sensors
VL  - 24
IS  - 13
AU  - Ribeiro, G.
AU  - Monge, J.
AU  - Postolache, O.
AU  - Pereira, J. M. D.
PY  - 2024
SN  - 1424-8220
DO  - 10.3390/s24134175
UR  - https://www.mdpi.com/journal/sensors
AB  - Stress is the inherent sensation of being unable to handle demands and occurrences. If not properly managed, stress can develop into a chronic condition, leading to the onset of additional chronic health issues, such as cardiovascular illnesses and diabetes. Various stress meters have been suggested in the past, along with diverse approaches for its estimation. However, in the case of more serious health issues, such as hypertension and diabetes, the results can be significantly improved. This study presents the design and implementation of a distributed wearable-sensor computing platform with multiple channels. The platform aims to estimate the stress levels in diabetes patients by utilizing a fuzzy logic algorithm that is based on the assessment of several physiological indicators. Additionally, a mobile application was created to monitor the users’ stress levels and integrate data on their blood pressure and blood glucose levels. To obtain better performance metrics, validation experiments were carried out using a medical database containing data from 128 patients with chronic diabetes, and the initial results are presented in this study.
ER  -