Article Versions Notes

Romine WL, Schroeder NL, Graft J, Yang F, Sadeghi R, Zabihimayvan M, Kadariya D, Banerjee T. Using Machine Learning to Train a Wearable Device for Measuring Students’ Cognitive Load during Problem-Solving Activities Based on Electrodermal Activity, Body Temperature, and Heart Rate: Development of a Cognitive Load Tracker for Both Personal and Classroom Use. Sensors. 2020; 20(17):4833. https://doi.org/10.3390/s20174833

Romine, William L., Noah L. Schroeder, Josephine Graft, Fan Yang, Reza Sadeghi, Mahdieh Zabihimayvan, Dipesh Kadariya, and Tanvi Banerjee. 2020. "Using Machine Learning to Train a Wearable Device for Measuring Students’ Cognitive Load during Problem-Solving Activities Based on Electrodermal Activity, Body Temperature, and Heart Rate: Development of a Cognitive Load Tracker for Both Personal and Classroom Use" Sensors 20, no. 17: 4833. https://doi.org/10.3390/s20174833

Romine, W. L., Schroeder, N. L., Graft, J., Yang, F., Sadeghi, R., Zabihimayvan, M., Kadariya, D., & Banerjee, T. (2020). Using Machine Learning to Train a Wearable Device for Measuring Students’ Cognitive Load during Problem-Solving Activities Based on Electrodermal Activity, Body Temperature, and Heart Rate: Development of a Cognitive Load Tracker for Both Personal and Classroom Use. Sensors, 20(17), 4833. https://doi.org/10.3390/s20174833