Mi-Ryong Park
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Mi-Ryong Park has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
Dongwon Kim
2 shared publications- Bong Kyu Kim
Digital Biomedical Research Division, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Republic of Korea
1 shared publication - Bu-Gi Kim
Division of Marine Mechatronics, Mokpo National Maritime University, Mokpo 58628, Republic of Korea
1 shared publication - Chul Huh
Digital Biomedical Research Division, Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea
1 shared publication - Hoyong Kang
Elect & Telecommun Res Inst, 218 Gajeong Ro, Daejeon 34129, South Korea
1 shared publication - Hyo Young Cho
Digital Biomedical Research Division, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Republic of Korea
1 shared publication
Latest Publications
- Open Access
- 24 June 2025
- Published by MDPI AG in Biosensors
- Vol. 15 (7) , 406
Noninvasive Continuous Glucose Monitoring Using Multimodal Near-Infrared, Temperature, and Pressure Signals on the Earlobe
This study investigates a noninvasive continuous glucose monitoring (NI-CGM) system optimized for earlobe application, leveraging the site’s anatomical advantages—absence of bone, muscle, and thick skin—for enhanced optical transmission. The system integrates multimodal sensing, combining near-infrared (NIR) diffuse transmission with temperature and pressure sensors. A novel Multi-Wavelength Slope Efficiency Near-Infrared Spectroscopy (MW-SE-NIRS) method is introduced, enhancing noise robustness through the slope efficiency-based parameterization of NIR signal dynamics. By employing three NIR wavelengths with distinct scattering and absorption properties, the method improves glucose detection reliability, addressing tissue heterogeneity and physiological noise in noninvasive monitoring. To validate the feasibility, a pilot clinical trial enrolled five participants with normal or pre-diabetic glucose profiles. Continuous glucose data capturing pre- and postprandial variations were analyzed using a 1D convolutional neural network (Conv1D). For three subjects under stable physiological conditions, the model achieved 97.0% Clarke error grid (CEG) A-Zone accuracy and a mean absolute relative difference (MARD) of 5.2%. Across all participants, results showed 90.9% CEG A-Zone accuracy and a MARD of 8.4%, with performance variations linked to individual factors such as earlobe thickness variability and physical activity. These outcomes demonstrate the potential of the MW-SE-NIRS system for noninvasive glucose monitoring and highlight the importance of future work on personalized modeling, sensor optimization, and larger-scale clinical validation.
- 24 June 2025
- Published by MDPI AG in Biosensors
- Vol. 15 (7) , 406
Open AccessNoninvasive Continuous Glucose Monitoring Using Multimodal Near-Infrared, Temperature, and Pressure Signals on the Earlobe
This study investigates a noninvasive continuous glucose monitoring (NI-CGM) system optimized for earlobe application, leveraging the site’s anatomical advantages—absence of bone, muscle, and thick skin—for enhanced optical transmission. The system integrates multimodal sensing, combining near-infrared (NIR) diffuse transmission with temperature and pressure sensors. A novel Multi-Wavelength Slope Efficiency Near-Infrared Spectroscopy (MW-SE-NIRS) method is introduced, enhancing noise robustness through the slope efficiency-based parameterization of NIR signal dynamics. By employing three NIR wavelengths with distinct scattering and absorption properties, the method improves glucose detection reliability, addressing tissue heterogeneity and physiological noise in noninvasive monitoring. To validate the feasibility, a pilot clinical trial enrolled five participants with normal or pre-diabetic glucose profiles. Continuous glucose data capturing pre- and postprandial variations were analyzed using a 1D convolutional neural network (Conv1D). For three subjects under stable physiological conditions, the model achieved 97.0% Clarke error grid (CEG) A-Zone accuracy and a mean absolute relative difference (MARD) of 5.2%. Across all participants, results showed 90.9% CEG A-Zone accuracy and a MARD of 8.4%, with performance variations linked to individual factors such as earlobe thickness variability and physical activity. These outcomes demonstrate the potential of the MW-SE-NIRS system for noninvasive glucose monitoring and highlight the importance of future work on personalized modeling, sensor optimization, and larger-scale clinical validation.
- Open Access
- 27 November 2023
- Published by MDPI AG in Journal of Marine Science and Engineering
- Vol. 11 (12) , 2243
Evaluation of a Multi-Hop Wireless Internet-of-Things Network on Large Ships
IoT networks on large ships are known to face challenges, such as severe signal attenuation due to the complex steel bulkhead structure inside the ship. However, reliable connectivity is still required to monitor critical facilities such as engine rooms. This study presents an evaluation study of an IoT network using the IEEE 802.15.4 DSME MAC protocol for reliable data collection within a ship. We investigate the impact of ship-specific characteristics on signal propagation and analyze the feasibility of utilizing the DSME MAC protocol. We also compare the viability of 2.4 GHz and sub-1 GHz communication within a ship. In addition, we strategically select router locations and evaluate the stability and time sensitivity of the constructed network. The experimental results demonstrate the feasibility and reliability of the proposed multi-hop wireless network for seamless data transmission onboard ships.
- 27 November 2023
- Published by MDPI AG in Journal of Marine Science and Engineering
- Vol. 11 (12) , 2243
Open AccessEvaluation of a Multi-Hop Wireless Internet-of-Things Network on Large Ships
IoT networks on large ships are known to face challenges, such as severe signal attenuation due to the complex steel bulkhead structure inside the ship. However, reliable connectivity is still required to monitor critical facilities such as engine rooms. This study presents an evaluation study of an IoT network using the IEEE 802.15.4 DSME MAC protocol for reliable data collection within a ship. We investigate the impact of ship-specific characteristics on signal propagation and analyze the feasibility of utilizing the DSME MAC protocol. We also compare the viability of 2.4 GHz and sub-1 GHz communication within a ship. In addition, we strategically select router locations and evaluate the stability and time sensitivity of the constructed network. The experimental results demonstrate the feasibility and reliability of the proposed multi-hop wireless network for seamless data transmission onboard ships.
- 30 December 2015
- Published by The Institute of Webcasting, Internet and Telecommunication in The Journal of The Institute of Internet, Broadcasting and Communication
- Vol. 15 (6) , 79-88
A Study on Application of Time-Triggered Ethernet for Vehicle Network
- 30 December 2015
- Published by The Institute of Webcasting, Internet and Telecommunication in The Journal of The Institute of Internet, Broadcasting and Communication
- Vol. 15 (6) , 79-88
A Study on Application of Time-Triggered Ethernet for Vehicle Network