Evaluation of a Continuous Blood Glucose Monitor: A Novel and Non-Invasive Wearable Using Bioimpedance Technology
Authors' conclusion
This study demonstrated the reliability of the prototype NI-CGM at collecting bioimpedance data in a real-world scenario. These data were used to train a model that could successfully estimate BGL with a promising MARD and clinically relevant PEG result. These results will enable continued development of the prototype NI-CGM as a wearable ring.
Study context
- Population
- Adults with T2Dworn for 14 days
- Participants
- 14 adults
- Outcome
- Accuracy of model-estimated BGL from bioimpedance data (MARD; Parkes error grid)
Methodological detailsreal-world, prototype device, randomized 80-20 training-test split
- Real-world
- Prototype device
- Randomized 80-20 training-test split
Main finding
As reported in the abstract
Accuracy of model-estimated BGL from bioimpedance data (gradient boosted model, 80-20 training-test split)
Mean Absolute Relative Difference (MARD) of estimated blood glucose level (BGL)
17.9%
Parkes error grid (PEG) analysis: values in clinically acceptable zones A and B
99%
Observational data: associations, not effects.
Original publication
Evaluation of a Continuous Blood Glucose Monitor: A Novel and Non-Invasive Wearable Using Bioimpedance Technology. J Diabetes Sci Technol. Published 29 October 2021. doi:10.
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