Artificial pancreas and glycemic control

Meal detection, carbohydrate estimation and personalized insulin delivery.

My earlier research focused on glycemic control for patients with Type 1 Diabetes Mellitus: meal detection algorithms, carbohydrate estimation, and artificial pancreas design.

This work combined feedback control schemes with biomedical signal processing to produce personalized insulin delivery strategies, addressing circadian variability in insulin sensitivity and patient-specific parameter tuning.

Related publications: (Godoy et al., 2021; Sereno et al., 2017)

References

2021

BSPC

Meal detection and carbohydrate estimation based on a feedback scheme with application to the artificial pancreas

J. L. Godoy, Juan E. Sereno, and Pablo S. Rivadeneira

Biomedical Signal Processing and Control, 2021

DOI Bib

@article{godoy2021meal,
  title = {Meal detection and carbohydrate estimation based on a feedback scheme with application to the artificial pancreas},
  author = {Godoy, J. L. and Sereno, Juan E. and Rivadeneira, Pablo S.},
  journal = {Biomedical Signal Processing and Control},
  volume = {68},
  pages = {102715},
  year = {2021},
  doi = {10.1016/j.bspc.2021.102715}
}

2017

CCAC

A performance comparison between standard and impulsive ZMPC on type 1 diabetic patients

Juan E. Sereno, Alejandro H. González, and Pablo S. Rivadeneira

In 2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC), 2017

DOI Bib

@inproceedings{sereno2017performance,
  title = {A performance comparison between standard and impulsive {ZMPC} on type 1 diabetic patients},
  author = {Sereno, Juan E. and González, Alejandro H. and Rivadeneira, Pablo S.},
  booktitle = {2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC)},
  pages = {1--6},
  publisher = {IEEE},
  year = {2017},
  doi = {10.1109/CCAC.2017.8276464}
}