Area of research
Biomedical Engineering · Pulmonary and Respiratory Medicine
Research interest
Research interests include Computer science, Wearable computer, Firefighting, Characterization (materials science), 3d printed, and Wearable technology.
Respiratory Rate Monitoring During Wildland Firefighting Operations: A Comparison of Face-Mounted and Chest-Mounted Wearable Sensors
Field Testing Multi-Parametric Wearable Technologies for Wildfire Firefighting Applications
Design, Development and Characterization of a Single-Layer 3D-Printed Strain CB-TPU Sensor
Flexible Dual-Material 3D-Printed Capacitive Force Sensors: Design, Fabrication, and Metrological Characterization
Breath-by-Breath Measurement of Respiratory Frequency and Tidal Volume with a Multiple-Camera Motion Capture System During Cycling Incremental Exercise
Preliminary Assessment of a Low-Sampling-Rate Wearable Head-Mounted Inertial Sensor System for Human Activity Recognition
Design and Performance Evaluation of a Smart Helmet System for Human Activity Recognition in Worker Safety Applications
Towards Non-Invasive Hemodynamic Monitoring: A Feasibility Analysis of Left Ventricular Ejection Time (LVET) Measurement with Wearable Inertial Sensors in Aortic Stenosis Patients
Influence of Sampling Frequency on the Symmetric Projection Attractor Reconstruction
Live Demonstration: “Intelligent, 3D-Printed Respiratory Add-On for FFP3 Masks: Enhancing HSE Through Open and Scalable Design”
Standard-Compliant Validation of a Smart Modular Add-on for Respiratory Protective Equipment: Design, Integration, and Functional Impact Assessment
Towards the Instrumentation of Facemasks Used as Personal Protective Equipment for Unobtrusive Breathing Monitoring of Workers
A Wearable Platform as a First Step towards Enabling Collective Intelligence in Alzheimer's Disease Management: Feasibility Assessment on Healthy Volunteers
A Technological Platform for Quantifying Alzheimer’s Patient-Caregiver Interactions in the Walk and Talk Program
Wearable Systems for Unveiling Collective Intelligence in Clinical Settings