Catania, March 12, 2025 – Digital technologies and mobile health represent a promising solution for monitoring and smoking cessation. A new review study, published in the IEEE Journal of Biomedical and Health Informatics, analyzed the current state of research and development in this field, examining the effectiveness of smartphone applications, wearable devices, and sensor-based systems.
“We are leading a digital revolution in smoking cessation. By combining AI with wearable devices and mobile apps, our team at the University of Catania is creating smarter, more personalized ways to help people quit. With real-time tracking and instant feedback, smokers get support exactly when they need it, giving them a much better chance of success.” said Prof. Riccardo Polosa, founder of CoEHAR.
The team of computer scientists, part of the 100 experts of CoEHAR, reviewed 49 studies published between 2019 and 2023, exploring technological features, outcomes, and evaluation methods.
The team was led by Dr. Mirko Casu, CoEHAR researcher, with the collaboration of Dr. Giusy La Rosa and Dr. Francesco Guarnera, under the supervision of Prof. Sebastiano Battiato, Full Professor of Computer Science at the University of Catania, and Prof. Pasquale Caponnetto, Professor of Clinical Psychology at the same university.
As highlighted in the study, wearable sensors and motion sensors show significant potential in fighting smoking addiction and improving cessation rates but require further improvements, as they can still be influenced by individual factors such as posture or dominant hand, resulting in performance variations. Motion sensors, in particular, achieve high accuracy but face challenges in real-world applications. Machine learning models and wireless signal detection techniques show promising results, and smartphone apps also offer personalized plans and tools to monitor progress, but most still rely on manual user input—thereby risking non-compliance or forgetting to complete them—and lack rigorous scientific evaluation.
““Technology is changing how people quit smoking,” said lead researcher Dr. Mirko Casu. “Our analysis shows that smart technology can recognize smoking with over 95% accuracy. These automated tools eliminate the need for self-reporting in quitting, enhancing the effectiveness and simplicity of stop-smoking programs while addressing one of the biggest challenges in smart quitting: high dropout rates.”
The study also highlights the importance of psycho-technological strategies based on behavioral interventions, enabling the precise identification of techniques used to modify smokers’ behavior.
With the increase in harm reduction initiatives and the growing adoption of digital solutions, the future of the fight against smoking could be at a decisive turning point.
Article available in Italian here.
