Taewoong Park, Talha Ibn Mahmud, Junsang Lee, Seokkyoon Hong, Jae Young Park, Yuhyun Ji, Taehoo Chang, Jonghun Yi, Min Ku Kim, Rita R Patel, Dong Rip Kim, Young L Kim, Hyowon Lee, Fengqing Zhu, Chi Hwan Lee
The increasing need for precise dietary monitoring across various health scenarios has led to innovations in wearable sensing technologies. However, continuously tracking food and fluid intake during daily activities can be complex. In this study, we present a machine-learning-powered smart neckband that features wireless connectivity and a comfortable, foldable design. Initially considered beneficial for managing conditions such as diabetes and obesity by facilitating dietary control, the device's utility extends beyond these applications...
May 2024: PNAS Nexus