The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis

Hatice Kabaoğlu; Fecir Duran; Emine Uçar

doi:10.35377/saucis...1612668

EN

The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis

Abstract

This study focuses on developing a digital twin for baby incubators in neonatal intensive care units to enhance monitoring and care for premature infants. The digital twin employs a hybrid model integrating Long Short-Term Memory (LSTM) and Random Forest (RF) algorithms to predict potential errors and alarms. The LSTM algorithm was trained using sensor data provided by a health technology company to predict future measurements. Subsequently, the RF algorithm classifies these predictions into specific error conditions. The hybrid model demonstrates success with mean squared error and mean absolute error values of 1540533.6 and 160.8 for the LSTM model and an 86.44% accuracy rate for the RF model. The study's key findings emphasize the effectiveness of the hybrid model in predicting future sensor values and classifying errors, representing a significant step towards improving premature baby care. Integrating LSTM and RF algorithms offers an innovative approach to error prediction, minimizing risks and improving premature infant health outcomes. In summary, this study successfully develops a digital twin for baby incubators, offering a promising solution for advancing newborn healthcare services and providing a foundation for future research.

Keywords

References

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Details

Primary Language

English

Subjects

Software Engineering (Other)

Journal Section

Research Article

Authors

Hatice Kabaoğlu ^*
0000-0002-1077-0012
Türkiye

Fecir Duran
0000-0001-7256-5471
Türkiye

Emine Uçar
0000-0002-6838-3015
Türkiye

Early Pub Date

June 23, 2025

Publication Date

June 30, 2025

Submission Date

February 3, 2025

Acceptance Date

May 29, 2025

Published in Issue

Year 2025 Volume: 8 Number: 2

DOI

https://doi.org/10.35377/saucis...1612668

IZ

https://izlik.org/JA87PY77BT

Cite

RIS / Bibtex

APA

Kabaoğlu, H., Duran, F., & Uçar, E. (2025). The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis. Sakarya University Journal of Computer and Information Sciences, 8(2), 301-311. https://doi.org/10.35377/saucis...1612668

AMA

1.Kabaoğlu H, Duran F, Uçar E. The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis. SAUCIS. 2025;8(2):301-311. doi:10.35377/saucis.1612668

Chicago

Kabaoğlu, Hatice, Fecir Duran, and Emine Uçar. 2025. “The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis”. Sakarya University Journal of Computer and Information Sciences 8 (2): 301-11. https://doi.org/10.35377/saucis. 1612668.

EndNote

Kabaoğlu H, Duran F, Uçar E (June 1, 2025) The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis. Sakarya University Journal of Computer and Information Sciences 8 2 301–311.

IEEE

[1]H. Kabaoğlu, F. Duran, and E. Uçar, “The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis”, SAUCIS, vol. 8, no. 2, pp. 301–311, June 2025, doi: 10.35377/saucis...1612668.

ISNAD

Kabaoğlu, Hatice - Duran, Fecir - Uçar, Emine. “The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis”. Sakarya University Journal of Computer and Information Sciences 8/2 (June 1, 2025): 301-311. https://doi.org/10.35377/saucis. 1612668.

JAMA

1.Kabaoğlu H, Duran F, Uçar E. The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis. SAUCIS. 2025;8:301–311.

MLA

Kabaoğlu, Hatice, et al. “The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis”. Sakarya University Journal of Computer and Information Sciences, vol. 8, no. 2, June 2025, pp. 301-1, doi:10.35377/saucis. 1612668.

Vancouver

1.Hatice Kabaoğlu, Fecir Duran, Emine Uçar. The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis. SAUCIS. 2025 Jun. 1;8(2):301-1. doi:10.35377/saucis. 1612668