Peer-Reviewed Journal Articles
1) C. Zhou, F. Zhang, E.J.C. Nacpil, Z. Wang, and F.X. Xu, “Driver Steering Intention Prediction for Human-Machine Shared Systems of Intelligent Vehicles Based on CNN-GRU Network,” Sensors, vol. 25, no. 10, 2025.
2) C. Liu, B. Chen, Y. Guo, X. Chen, E.J.C. Nacpil, W. Hou, and R. Zheng, “Evaluation of a user-accessible countermeasure: Effect of manual dexterity gymnastics on passive driver fatigue,” Transportation Research Part F: Traffic Psychology and Behaviour, vol. 101, 2024.
3) F.X. Xu, E.J.C. Nacpil, Z. Wang, and C. Zhou, “Modeling lateral control behavior of driver for manual takeover of automated vehicles during pedestrian collision avoidance”, IEEE Transactions on Vehicular Technology, vol. 73, no. 6, 2024.
4) Y. Choi, E.J.C. Nacpil., J. Han, I. Kim, and I. Jeon, “Recent Advances in Dispersant Technology for Carbon Nanotubes toward Energy Device Applications,” Advanced Energy and Sustainability Research, vol. 5, no. 4, 2024.
5) C. Liu, E.J.C. Nacpil, W. Hou, Y. Qin, and R. Zheng, “Evaluation of Visual Risk Perception of Automated Driving Tasks by Analyzing Gaze Pattern Dispersion,” IEEE Transactions on Intelligent Vehicles, vol. 9, no. 1, 2024.
6) E.J.C. Nacpil, J. Han, and I. Jeon, “Artificial Intelligence-Assisted Robustness of Optoelectronics for Automated Driving: A Review,” IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 1, 2024.
7) F.X. Xu, S.Y. Feng, E.J.C. Nacpil, Z. Wang, G.Q. Wang, and C. Zhou, “Modeling Lateral Control Behaviors of Distracted Drivers for Haptic-Shared Steering System,” IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 12, 2023.
8) E.J.C. Nacpil, Z. Wang, M. Guan, K. Nakano, and I. Jeon, “EEG-based Emergency Braking Prediction Using Data Ablation and SVM Classification,” IEEE Sensors Journal, vol. 23, no. 14, 2023.
9) E. Jokar, L. Cai, J. Han, E.J.C. Nacpil, and I. Jeon, “Emerging Opportunities in Lead-Free and Lead–Tin Perovskites for Environmentally Viable Photodetector Applications,” Chemistry of Materials, vol. 35, no. 9, 2023.
10) S. Yoon, J.H. Jeon, S. Cho, E.J.C. Nacpil, I. Jeon, J. Choi, H. Kim, “Extreme gradient boosting to predict atomic layer deposition for platinum nano-film coating,” Langmuir, vol. 39, no. 14, 2023.
11) C. Liu, Z. Wang, E.J.C. Nacpil, W. Hou, R. Zheng, “Analysis of Visual Risk Perception Model for Braking Control Behaviour of Human Drivers: A Literature Review,” IET Intelligent Transport Systems, 2022.
12) Z. Wang, R. Zheng, E.J.C. Nacpil, K. Nakano, “Modeling and analysis of driver behavior under shared control through weighted visual and haptic guidance,” IET Intelligent Transport Systems, 2022.
13) Z. Wang, S. Suga, E.J.C. Nacpil, B. Yang, K. Nakano, “Effect of Fixed and sEMG-Based Adaptive Shared Steering Control on Distracted Driver Behavior,” Sensors, vol. 21, no. 7691, 2021.
14) E.J.C. Nacpil, Z. Wang, K. Nakano, “Application of physiological sensors for personalization in semi-autonomous driving: A review,” IEEE Sensors Journal, vol. 21, no. 18, 2021.
15) E.J.C. Nacpil, S. Nacey, G. Youssef, “Feasibility assessment of transfer functions describing biomechanics of the human lower limb during the gait cycle,” Biosignal Processing and Control, vol. 69, 2021.
16) E.J.C. Nacpil, Z. Wang, Z. Yan, T. Kaizuka, K. Nakano, “Surface Electromyography-controlled Pedestrian Collision Avoidance: A Driving Simulator Study,” IEEE Sensors Journal, vol. 21, no. 12, 2021.
17) Z. Wang, S. Suga, E.J.C. Nacpil, Z. Yan, K. Nakano, “Adaptive driver-automation shared steering control via forearm surface electromyography measurement,” IEEE Sensors Journal, vol. 21, no. 4, 2021.
18) E.J.C. Nacpil, T. Kaizuka, R. Zheng, and K. Nakano, “Surface Electromyography-Controlled Automobile Steering Assistance,” Sensors, vol. 20, no. 3, 2020.
19) E.J.C. Nacpil, Z. Wang, R. Zheng, T. Kaizuka, and K. Nakano, “Design and Evaluation of a Surface Electromyography-Controlled Steering Assistance Interface,” Sensors, vol. 19, no. 6, 2019.
20) E.J.C. Nacpil, R. Zheng, T. Kaizuka, and K. Nakano, “A surface electromyography controlled steering assistance interface,” Journal of Intelligent and Connected Vehicles, Apr. 2019.
Peer-Reviewed Conference Papers
1) E.J. Nacpil, K. Nakano, “Driving Simulator Validation of Machine Learning Classification for a Surface Electromyography-Based Steering Assistance Interface,” In AHFE 2020 International Conference on Human Factors and Simulation, 2020. pp. 143–149.
2) E.J. Nacpil, T. Kaizuka, and K. Nakano, “Driving simulator validation of surface electromyography controlled driving assistance for bilateral transhumeral amputees,” In AHFE 2019 International Conference on Human Factors and Simulation, 2019. pp. 166–175.
3) R. Yamashina, Y. Tanda, A. Taniguchi, E.J.C. Nacpil, H. Shimura, A. Kawaguchi, “不整地用履帯型移動体(RM17-0035)を用いた自律移動技術検証に関する報告 (Autonomous Mobile Robots using Tracked Vehicle for Rough Terrain),” In 2018 JSME Conference on Robotics and Mechatronics, 2018. (In Japanese)
4) E.J. Nacpil, R. Zheng, T. Kaizuka, and K. Nakano, “Implementation of a sEMG-machine interface for steering a virtual car in a driving simulator,” In AHFE 2017 International Conference on Human Factors in Simulation and Modeling, 2018, pp. 274–282.