Project: Evaluation of a test system to measure safe force thresholds on delicate tissue
2018 – 2020
Project goal: The project aims at supporting aging in place by means of an intelligent AI-based system making use of wireless sensors and data analytics that monitors activities of daily living (ADL). The system will be able extract and learn subject specific patterns of ADL from WiFi data in order to detect abnormal activities and generate appropriate alerts.
This platform provides the following features and benefits:
- It is passive/unobtrusive,
- Adapts to user behavior, but also to various network setups and environment configurations
- Enables care staff to monitor health and wellbeing of residents from a remote location.
PI: Ana-Maria Cretu
Students: Itaf Joudeh
Other Funding: NSERC ENGAGE
- Joudeh, Itaf O., Ana-Maria Cretu, R. Bruce Wallace, Rafik A. Goubran, Abdulaziz Alkhalid, Michel Allegue-Martinez, and Frank Knoefel. “WiFi Channel State Information-Based Recognition of Sitting-Down and Standing-Up Activities.” In 2019 IEEE International Symposium on Medical Measurements and Applications (MeMeA), pp. 1-6. IEEE, 2019.
- Joudeh, Itaf O., “Exploiting Wi-Fi Channel State Information for Artificial Intelligence-Based Human Activity Recognition of Similar Dynamic Motions”, M.A.Sc. Thesis, Carleton University, 2020.
- I. Joudeh, A. Cretu, B. Wallace, R. Goubran, A. Allegue-Martinez, F. Knoefel, “Location Independence in Machine Learning Classification of Sitting-Down and Standing-Up Actions using Wi-Fi Sensors”, 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2021.