CGM-Freq: A Python Library for Frequency Domain Analysis of Continuous Glucose Monitoring Data
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.
Authors
- Elizabeth Healey (ORCID: https://orcid.org/0000-0002-7307-8429)
- Isaac S. Kohane (ORCID: https://orcid.org/0000-0003-2192-5160)
Institutions
- Harvard–MIT Division of Health Sciences and Technology (US)
Publication Details
- Published
- 2024-11-10
- DOI
- https://doi.org/10.1109/bhi62660.2024.10913828
- Primary Topic
- Diabetes Management and Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation