HUPA-UCM diabetes dataset

Autor: J. Ignacio Hidalgo, Jorge Alvarado, Marta Botella, Aranzazu Aramendi, J. Manuel Velasco, Oscar Garnica
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Data in Brief, Vol 55, Iss , Pp 110559- (2024)
Druh dokumentu: article
ISSN: 2352-3409
DOI: 10.1016/j.dib.2024.110559
Popis: This dataset provides a collection of Continuous Glucose Monitoring (CGM) data, insulin dose administration, meal ingestion counted in carbohydrate grams, steps, calories burned, heart rate, and sleep quality and quantity assessment ac- quired from 25 people with type 1 diabetes mellitus (T1DM). CGM data was acquired by FreeStyle Libre 2 CGMs, and Fitbit Ionic smartwatches were used to obtain steps, calories, heart rate, and sleep data for at least 14 days. This dataset could be utilized to obtain glucose prediction models, hypoglycemia and hyperglycemia prediction models, and research on the relationships among sleep, CGM values, and the rest of the mentioned variables. This dataset could be used directly from the preprocessed version or customized from raw data. The data set has been used previously with different machine learning algorithms to predict glucose values, hypo, and hyperglycemia and to analyze influences among the features and the quality and quantity of sleep in people with T1DM.
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