Ryan Mattfeld

Biography

I earned a Bachelor of Science (2012), Master of Science (2014), and Doctorate of Philosophy (2018) in Electrical Engineering from Clemson University. I am currently an Assistant Professor of Computer Science at Elon University. My research areas are focused on developing smarter sensors and in improving student learning and engagement. In particular, I have experience with table embedded scales, accelerometers, gyroscopes, head mounted displays cameras, and depth sensors including infrared and LiDAR. I have used these sensors towards projects focused on moblile health (mHealth), virtual/mixed reality latency, computer vision, object detection and recognition, and human motion detection. I also have experience in developing and evaluating how alternative grading systems affect student motivation. 

Some example projects include an analysis of simulator sickness; sickness caused by latency in head mounted displays. In particular, the research focused on the presence of sinusoidal latency in virtual reality systems. I also collaborated with BMW to develop a visual inspection system, which detects defects in the assembly process and provides live feedback to inspectors. I have undertaken multiple projects in the field of mHealth, with prior focus on automatic measurement of consumption events using a table embedded scale in a cafeteria environment and evaluation and development of pedometer algorithms for daily life, including regular, semi-regular, and unstructured gaits. I am now working on projects involving depth sensing. In particular, my current goal is the development of an open source depth sensor to function similarly to the now discontinued Xbox Kinect but using LiDAR as the depth sensor with applications ranging from obstacle detection for people with visual impairments to autonomous fire detection using drones.

Publications (listed chronologically)

Ryan Stephen Mattfeld. 2023. Improving Student Motivation through an Alternative Grading System. Journal of Computing Sciences in Colleges, 39, 5 (November 2023), 86–95.

R. Mattfeld, E. Jesch, and A. Hoover, “Evaluating Pedometer Algorithms on Semi-Regular and Unstructured Gaits,” Sensors, vol. 21, no. 13, p. 4260, Jun. 2021.

M. Wilson, S. Beadle, A. Kinsella, R. Mattfeld, A. Hoover, and E. Muth, "Task performance in a head-mounted display: The impacts of varying latency", Displays, vol. 61, 2020.

R. Mattfeld, “Evaluation of Pedometer Performance Across Multiple Gait Types Using Video for Ground Truth,” PhD dissertation, Holcombe Department of Electrical and Computer Engineering, Clemson University, SC., 2018.

R. Mattfeld, E. Jesch and A. Hoover, "A new dataset for evaluating pedometer performance," 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, pp. 865-869, 2017.

R. Mattfeld, E. Muth, and A. Hoover, "A comparison of bite size and BMI in a cafeteria setting," in Physiology & Behavior, vol. 181, pp. 38-42, 2017.

R. Mattfeld, E. Muth and A. Hoover, "Measuring the consumption of individual solid and liquid bites using a table embedded scale during unrestricted eating," in IEEE Journal of Biomedical and Health Informatics, vol. 21, no. 6, pp. 1711-1718, 2017.

A. Kinsella, R. Mattfeld, E. Muth and A. Hoover, “Frequency, not amplitude, of latency affects subjective sickness in a Head-Mounted Display,” in Aerospace Medicine and Human Performance, vol. 87, no. 7, pp. 604-609, 2016.

AADI Book Chapter on bite detection

Master's Thesis

I. Walker, R. Mattfeld, A. Mutlu, A. Bartow, and N. Giri, "A novel approach to robotic climbing using contimuum appendages in in-situ exploration", in 2012 IEEE Aerospace Conference, March 2012.

Project Pages

Bite detection through wrist-worn accelerometer and gyroscope

Bite detection through use of a table-embedded scale

Pedometer evaluation and algorithm development for regular, semi-regular, and irregular gaits

BMW Visual Inspector