Expertise: Machine Learning / Data Analytics / Deep Learning / AI
SAM3 Expertise Areas: Machine Learning / Data Analytics / Deep Learning / Artificial Intelligence
SAM3 researchers have expertise in many advanced analytics methods that allow for the processing of large data sets or complex sensor data. Through these methods, vast arrays of sensor and other data are analyzed to determine knowledge and information that can be communicated to the older adult leading to action.
Analytics Expertise Areas
- Applications to: Video analysis, Audio and acoustic analysis, Smart home sensor fusion, Driving Assessment
- Methods: Machine Learning, Deep Learning, Artificial Intelligence including supervised and unsupervised learning
- Big data analysis including datasets >1TB
- Processing models including cluster and GPU assisted methods
K. Van Benthem, B. Wallace, L. McCauley, J. Keillor, S. Marshall, F. Knoefel, T. Friedman, and C. Herdman, “Profiles of Mature Drivers and Their Trust in Telematics‑Based Safety Technologies”, ISG 2026
B. Chimehi, J. Larivière-Chartier, B. Wallace, L. Ault, F. Knoefel, J. Kaye, Z. Beattie, J. Steele, L. Anderson, N.Thomas, “Digital Signatures of Caregiver Burden: Machine Learning Classification Using Multimodal In-Home Sensor Data”, ISG 2026
S. Shafiyan, K. Fraser, F. Knoefel, N. Thomas, M. Kunz, B. Wallace, R. Goubran, A.a Zumbansen, “Revisiting the Cookie Theft Picture for Cognitive Impairment: Assessing Its Relevance for Discourse Analysis After Four Decades”, accepted at Alzheimer’s Association International Conference (AAIC), 2025.
McCauley, L., Benthem, K. V., Herdman, C., Wallace, B., Keillor, J., Goubran, R., Knoefel, F., & Marshall, SM, “Communicating increased driving risk: A study of mature driver expectations”, accepted at Alzheimer’s Association International Conference (AAIC), 2025.
Nasr, M. S. E., Masson, P., Wallace, B., A., Benthem, K. V., Herdman, C., Keillor, J., Goubran, R., Knoefel, F., & Marshall, SM. “Identifying Mature Driver Risk from Naturalistic Driving”, accepted at Alzheimer’s Association International Conference (AAIC), 2025.
W. Sloan, B. Wallace, R. Goubran, H. Sveistrup, “Improved Activity Recognition Through Fusion of Earable Pairs” accepted at IEEE Medical Measurement and Applications Symposium (MeMeA 2025), 2025
M. Kunz, K. Fraser, B. Wallace, F. Knoefel, R. Goubran, S. Shafiyan, N. Thomas “Addressing Age Bias in the Application of Appearance-Based Gaze-Tracking for Older Adults”, IEEE/CVF Winter Conference on Applications of Computer Vision, 2025.
(Best Paper Award)
W. Sloan, B. Wallace, R. Goubran, H. Sveistrup, “Cross-Body Transfer Learning for Human Activity Recognition” accepted at 2025 IEEE International Instrumentation Measurement Technology Conference (I2MTC), 2025
Pioneering Voice AI with Carleton University
Story by partner company Edge Signal about the work we have done with them within a SAM3 SME Support for Aging in Place Technology project. …
A. Laghai, B. Wallace, B. Laska, R. Goubran, “Ray Tracing Modelling Using LiDAR 3D Scans for Rapid Acoustical Measurement and Simulation” accepted at 2025 IEEE International Instrumentation Measurement Technology Conference (I2MTC), 2025
Stewart, Matthew, Caitlin Higginson, Julien Lariviere-Chartier, Elliott Lee, James Green, Rafik Goubran, Frank Knoefel, and Rebecca Robillard. “Classification of Central and Obstructive Sleep Apnea Using Respiratory Inductance Plethysmography and Convolutional Neural Networks.” In 2024 IEEE Sensors Applications Symposium (SAS), pp. 1-6. IEEE, 2024.
Link to Paper
Bahareh Chimehi, Julien Larivière-Chartier, Bruce Wallace, Zachary Beattie, Laura Ault, Lyndsey Miller, Joel Steele, Neil Thomas, Sensor Assessment of Time in Bed on Caregiver Burden for Person Living with Cognitive Impairment, IEEE International Symposium on Medical Measurements (MeMeA) 2024, 2024
Link to Paper