Collaborator · IoT4Care
Florenc Demrozi
Full Professor
Department of Electrical Engineering and Computer Science, University of Stavanger
Research interests
Human activity recognition · Internet of Medical Things · Active and Assisted Living · AI-enabled sensing · Wearable and wireless sensing
Florenc Demrozi is Full Professor in Biomedical/Medical Engineering and Technology at the University of Stavanger, Norway, and a collaborator of IoT4Care. He received his PhD in Computer Science from the University of Verona in 2020 under the supervision of Graziano Pravadelli, with a thesis on IoT-based virtual coaching for activities of daily life. He had previously completed both his BSc and MSc at Verona.
He is a co-founder of the IoT4Care research group and has been one of the main contributors to its work on Human Activity Recognition, Active and Assisted Living and the Internet of Medical Things. His research combines machine learning with wearable, body-area, WiFi and other wireless sensing technologies to infer human activities and clinically relevant behaviour outside highly instrumented laboratory environments.
The Verona research line in which Florenc worked includes virtual coaching, indoor occupancy and localisation, low-cost body-area networks, Parkinson’s disease monitoring and freezing-of-gait analysis, smart-home platforms and contactless sensing. At Stavanger his work continues toward AI-enabled sensor systems for proactive healthcare, while maintaining active collaborations with the Verona group. He also serves the research community through conference organisation and editorial activity, including work with the IEEE Sensors Journal.
Projects
An IoT infrastructure for monitoring motor fluctuations in Parkinson's disease.
A Brain Research Foundation Verona project on an Internet of Things infrastructure for observing motor fluctuations in Parkinson’s disease, supporting the broader IoT4Care research line on wearable and data-driven movement monitoring.
Smart-Pump
Smart-Pump: Intelligent assistive system to regulate the continuous administration of drugs in Parkinson’s patients.
A Veneto FSE project combining motor-symptom monitoring and intelligent assistance to support more personalised continuous drug administration for people with Parkinson’s disease and give clinicians a richer view of treatment response.
Bip-Bip
Bip-Bip: a wearable smart system to prevent freezing of gait in people affected by Parkinson’s disease.
A Veneto FSE research project on wearable sensing and machine-learning support for anticipating freezing of gait in Parkinson’s disease, with the goal of triggering assistance before or during a freezing episode.
ADA
ADA: An IoT-based virtual coaching platform for assisting daily life activities of ageing persons with Down syndrome.
A multidisciplinary IoT and virtual-coaching project for supporting autonomy and healthy ageing in people with Down syndrome, combining unobtrusive smart objects, personalised data analytics and daily-life coaching.
Publications
2025
2024
Artifact: WirelessEye - Seeing over WiFi Made Accessible
PerCom Workshops
Environmental Microchanges in WiFi Sensing
DATE
ICT-Based Solutions for Alzheimer's Disease Care: A Systematic Review
IEEE Access
SN Comput. Sci.
WirelessEye - Seeing over WiFi Made Accessible
PerCom Workshops
2023
A Comprehensive Review of Automated Data Annotation Techniques in Human Activity Recognition
CoRR
IEEE Trans. Emerg. Top. Comput.
Fostering Human Activity Recognition Workflows: An Open-Source Baseline Framework
ICDH
Non-Invasive Monitoring of Alzheimer's patients through WiFi Channel State Information
IWASI
Towards Deep Learning-based Occupancy Detection Via WiFi Sensing in Unconstrained Environments
DATE
2022
A freely available system for human activity recognition based on a low-cost body area network
COMPSAC
A virtual coaching platform to support therapy compliance in obesity
COMPSAC
ISoLA
Practical identity recognition using WiFi's Channel State Information
DATE
WifiEye - Seeing over WiFi Made Accessible
CoRR
2021
2020
IEEE Access
Joint Distribution and Transitions of Pain and Activity in Critically Ill Patients
EMBC
Toward a Wearable System for Predicting Freezing of Gait in People Affected by Parkinson's Disease
IEEE J. Biomed. Health Informatics

