GluCINDa (Glucose: Coherent Import. Neat Data.): An Open-Source Tool for the Consolidation of Continuous Glucose Monitoring Data for Research.
Project description
GluCINDa — Glucose: Coherent Import. Neat Data.
⚠ RESEARCH AND EDUCATION USE ONLY This software does not seek or have market approval and is intended exclusively for research and educational purposes. It is not intended for use in safety-critical systems or in any environment in which a software error could lead to damage or injury (e.g., for therapy or clinical decision-making purposes). This software is experimental and may contain errors. It is provided without any warranty (other than copyright as stated in Article 6 of the EUPL) and use of the software is entirely at your own risk. There is no obligation to provide updates, maintenance, or support.
Overview
GluCINDa is a manufacturer-agnostic continuous glucose monitoring (CGM) data ingestion layer designed for research applications. It provides automated parsing, normalization, and structured export of raw CGM data exports across heterogeneous device manufacturers and file formats. GluCINDa does not perform glucose analysis; it produces clean, and traceable output suitable for downstream processing and statistical analysis.
Key design principles:
- Manufacturer-agnostic: no hardcoded dependencies on any single CGM device or export structure
- Full traceability: all transformations are documented; silent data loss is not permitted
- Reproducible and deterministic: identical inputs produce identical outputs
- Stable output schema: downstream analysis pipelines are not broken by upstream format changes
- Optimized for real-world data: handles heterogeneous CGM exports from multiple manufacturers and download platforms (Validated: Abbott/LibreView, Dexcom/Clarity, Medtronic/CareLink, iCan, Glooko. Provisional: Sibionics, Tandem)
Contributors
Software created and written by:
- Petra M. Baumann (MUG)
- Alexander Grebien (MUG)
Acknowledgments:
- Christian Taucher (MUG)
- Florian Posch (MUG)
- Lia Bally (INS)
- Julia Mader (MUG)
MUG: Medical University of Graz, Austria
INS: Inselspital Bern, Switzerland
Installation
Download the latest .whl file from GitHub Releases and install with:
pip install glucinda-1.0.0-py3-none-any.whl
Then launch with
glucinda
Usage
After launching the GUI, you are in Simple Mode. Select the directory containing the input files, accept the suggested or provide an empty output directory and press "Run". Switching to Advanced Mode allows for some customization of the documenation and outputs.
Output Schema
GluCINDa produces a semicolon-delimited CSV containing all extracted CGM data with the following columns:
| Column | Description |
|---|---|
sid |
Subject identifier, derived from the input file name. |
date |
Date of measurement (YYYY/mm/dd). |
time |
Time of measurement (HH:MM:SS). |
value_num |
Numeric CGM value. Empty if the source value is non-numeric. |
unit |
Unit of measurement as it appears in the source column header (e.g. mg/dl, mmol/l); undefined if absent. |
value_str |
Non-numeric CGM value (e.g. High, Low). Empty if the source value is numeric. |
record_type |
CGM record type code distinguishing measurement subtypes (LibreView only). |
record_type_source_column |
Source column for record_type (LibreView only). |
manufacturer_assumed |
CGM device manufacturer inferred from the input file structure. |
device_id |
Sensor or transmitter identifier from the input file (LibreView, Clarity, Glooko). |
device_id_source_column |
Source column for device_id (LibreView, Clarity, Glooko). |
sequence |
Row-level sequence number as provided by the manufacturer (Clarity, CareLink, iCan). |
sequence_source_column |
Source column for sequence (Clarity, CareLink, iCan). |
download_source_assumed |
Download platform inferred from the input file structure. |
source_column |
Column name in the input file from which value_num or value_str was extracted. |
source_file |
Input file name (and sheet name for XLS/X files). |
notice |
Parsing-related warnings. Empty if no issues were detected. |
further_raw_data_json |
Verbatim source values stored as JSON for full transparency. |
For full details including data types, controlled vocabularies, and transformation notes, see DATA_DICTIONARY.md.
Citation
A manuscript describing GluCINDa is currently under review. In the meantime, please cite the software using the "Cite this repository" button on the GluCINDa release repository.
License
GluCINDa is licensed under the terms of the European Union Public Licence v. 1.2 (EUPL-1.2).
You should have received a copy of the EUPL in a separate LICENSE file along with
GluCINDa. If not, see https://eupl.eu/1.2/en/.
The EUPL is internationally recognized and written in legally neutral terms, ensuring broad applicability beyond the European Union. It is compatible with many widely used open-source licenses, facilitating integration of GluCINDa into international projects.
Copyright © 2025 Medical University of Graz. All rights reserved.
Third-Party Libraries
A list of third-party tools, modules, and libraries used in connection with GluCINDa,
together with their respective licenses, is provided in the NOTICE file.
Export Control
The software (including all related documentation) shall be used and communicated in compliance with all applicable export control laws. Use by or communication to persons or countries restricted by regulatory authorities (according to applicable classification and intended use) is strictly prohibited.
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