Prof. Yingying Chen and her team has received the Best Testbed Award from the 10th ACM/IEEE Symposium on Edge Computing (SEC) 2025. The testbed is entitled as “mmWave Testbed for Data Collection and Model Sharing in Contactless Concentration Monitoring System”, and the award was received in December 2025 at Washington, D.C. The testbed was a collaborative work among Rutgers University, George Mason University, Temple University, and New York Institute of Technology. 

Maintaining concentration is essential for productivity, learning, and safety, yet it remains difficult to assess objectively in everyday settings. Traditional methods such as self-reporting and observational studies are subjective and labor-intensive. Wearable sensors can provide physiological data but require constant contact with the user, while camera-based systems raise privacy concerns and are sensitive to illumination and occlusion. Our team developed a mmWave-based testbed that integrates signal preprocessing, beamforming-based spatial decomposition, frequency-domain analysis, and deep learning with domain adaptation. The approach achieves accurate classification using a single Commercial-Off-The-Shelf (COTS) radar, offering a low-cost solution for contactless concentration monitoring in classrooms, offices,
and healthcare environments.