SenseHunger: Machine Learning Approach to Hunger Detection Using Wearable Sensors

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 20; p. 7711
• Main Authors: Irshad, Muhammad Tausif, Nisar, Muhammad Adeel, Huang, Xinyu, Hartz, Jana, Flak, Olaf, Li, Frédéric, Gouverneur, Philip, Piet, Artur, Oltmanns, Kerstin M., Grzegorzek, Marcin
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2022; MDPI
• Subjects: Body weight; Chronic diseases; Classification; Connectivity; Data processing; Epidemiology; Hormones; hunger; Investigations; Machine learning; multimodal sensing; Neural networks; non-invasive sensing; Overweight; physiological signals; Physiology; satiety; Sensors; Signal processing; United States; New Jersey; Germany

The perception of hunger and satiety is of great importance to maintaining a healthy body weight and avoiding chronic diseases such as obesity, underweight, or deficiency syndromes due to malnutrition. There are a number of disease patterns, characterized by a chronic loss of this perception. To our...