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cgmguru: Advanced Continuous Glucose Monitoring Analysis with High-Performance C++ Backend
Tools for advanced analysis of continuous glucose monitoring (CGM) time-series, implementing GRID (Glucose Rate Increase Detector) and GRID-based algorithms for postprandial peak detection, and detection of hypoglycemic and hyperglycemic episodes (Levels 1/2/Extended) aligned with international consensus CGM metrics. Core algorithms are implemented in optimized C++ using 'Rcpp' to provide accurate and fast analysis on large datasets.
Getting started
Package overview
cgmguru: Complete CGM Analysis Workflow
cgmguru: Examples Gallery
detect_all_events function : cgmguru vs iglu
detect_between_maxima function
detect_hyperglycemic_events function
detect_hypoglycemic_events function
excursion function
find_local_maxima function
find_max_after_hours function
find_max_before_hours function
find_min_after_hours function
find_min_before_hours function
find_new_maxima function
grid function
maxima_grid function
mod_grid function
orderfast function
start_finder function
transform_df function
Browse package contents
Package details |
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| Author | Sang Ho Park [aut, cre], Rosa Oh [aut, ctb], Sang-Man Jin [aut, ctb] |
| Maintainer | Sang Ho Park <shstat1729@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.1.0 |
| URL | https://github.com/shstat1729/cgmguru |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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