Digital Health Technologies for Eating Behavior and Obesity: Experimental and Data-Driven Approaches
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: 20 December 2026 | Viewed by 116
Special Issue Editor
Interests: obesity; eating behavior; psychophysiology; digital health; virtual reality; metabolic disorders
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Diet-related diseases, particularly obesity, remain major global health challenges driven by complex interactions between physiological, behavioral and environmental factors. Eating behavior plays a central role in these processes, yet traditional assessment methods often fail to capture its dynamic and multidimensional nature.
Recent advances in digital health technologies—including wearable sensors, mobile applications and immersive environments such as virtual reality—enable objective, real-time monitoring of behavioral patterns and physiological responses in ecologically valid settings.
These approaches support the identification of digital and physiological biomarkers associated with food intake, stress responses and decision-making patterns, while experimental frameworks allow controlled investigation of eating behavior and the development of data-driven and technology-based interventions.
This Special Issue aims to explore digital health technologies applied to eating behavior and obesity, with a focus on measurement, monitoring, experimental methodologies, sensor-based systems and data-driven analysis.
We welcome original research articles, reviews and methodological papers addressing, but not limited to:
- Digital tools for dietary assessment and eating behavior monitoring
- Sensor-based measurement of physiological responses (e.g., HRV, ECG, electrodermal activity)
- Wearable technologies and digital biomarkers
- Virtual reality and immersive environments for behavioral data collection
- Experimental systems for food choice and decision-making analysis
- Data-driven approaches and machine learning in behavioral and nutrition data analysis
- Technology-based interventions for obesity management
Prof. Dr. Veronica Mocanu
Guest Editor
Manuscript Submission Information
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Keywords
- eating behavior
- obesity
- digital health
- physiological monitoring
- digital biomarkers
- wearable technologies
- virtual reality
- sensor-based systems
- food choice
- experimental research
- artificial intelligence
- data-driven approaches
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