Resumen
This work presents a Database that contains Photoplethysmography signals, glucose levels, weight, height and age of 217 patients. The information of biologic activity was obtained using the handle Empatica E4 Wristband, the glucose level using laboratory blood chemistry analyzers (Cobas 6000), and the physical parameters using standardized instruments. The database comprises a forward training a total of 5576 samples and another segment of validation to a total of 2164 samples. The Database has been used to evaluate different prediction techniques based on Machine Learning (Random Forest, Artificial Neural Network, Support Vector Machine, Gradient Boosting Machine). The implementation of these algorithms provides up to 90% average accuracy, a correlation of 0.88 and a satisfactory evaluation in the Error Diagram of Clarke. According to the results obtained, the proposed database is appropriate for training and verification of existing correlation between photoplethysmography signals and blood glucose level.
Idioma original | Inglés |
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Título de la publicación alojada | Advances in Emerging Trends and Technologies - Volume 2 |
Editores | Miguel Botto-Tobar, Joffre León-Acurio, Angela Díaz Cadena, Práxedes Montiel Díaz |
Editorial | Springer Verlag |
Páginas | 44-53 |
Número de páginas | 10 |
ISBN (versión impresa) | 9783030320324 |
DOI | |
Estado | Publicada - 1 ene. 2020 |
Evento | 1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019 - quito, Ecuador Duración: 29 may. 2019 → 31 may. 2019 |
Serie de la publicación
Nombre | Advances in Intelligent Systems and Computing |
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Volumen | 1067 |
ISSN (versión impresa) | 2194-5357 |
ISSN (versión digital) | 2194-5365 |
Conferencia
Conferencia | 1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019 |
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País/Territorio | Ecuador |
Ciudad | quito |
Período | 29/05/19 → 31/05/19 |
Nota bibliográfica
Publisher Copyright:© 2020, Springer Nature Switzerland AG.