CGM-Freq: A Python']Python Library for Frequency Domain Analysis of Continuous Glucose Monitoring Data

被引：0

作者：

Healey, Elizabeth ^{[1
]}

Kohane, Isaac ^{[2
]}

机构：

[1] Harvard MIT Program Hlth Sci & Technol, Cambridge, MA 02139 USA

[2] Harvard Med Sch, Dept Biomed Informat, Boston, MA USA

来源：

2024 IEEE EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS, BHI | 2024年

基金：

美国国家科学基金会;

关键词：

signal processing; continuous glucose monitoring;

D O I：

10.1109/BHI62660.2024.10913828

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In recent years, the number of patients using continuous glucose monitoring (CGM) has increased. In addition to helping patients manage their disease, CGM produces time series data that can be used for integration in control algorithms, predictive models, and for retrospective analyses. Through feature extraction, many digital biomarkers can be derived from CGM. In this work, we provide a tool to extract features derived from the frequency domain. We first introduce a novel open-source Python library, CGM-Freq, for the analysis of CGM data in the frequency domain. We then test the library on real data. This work provides an open-source tool to further investigate the frequency domain of CGM signals.

引用

页数：6

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