A machine-learning-enabled smart neckband for monitoring dietary intake

被引:2
|
作者
Park, Taewoong [1 ]
Mahmud, Talha Ibn [2 ]
Lee, Junsang [1 ]
Hong, Seokkyoon [1 ]
Park, Jae Young [1 ]
Ji, Yuhyun [1 ]
Chang, Taehoo [3 ]
Yi, Jonghun [4 ]
Kim, Min Ku [1 ]
Patel, Rita R. [5 ]
Kim, Dong Rip [4 ]
Kim, Young L. [1 ]
Lee, Hyowon [1 ,6 ]
Zhu, Fengqing [2 ]
Lee, Chi Hwan [1 ,2 ,3 ,6 ,7 ]
机构
[1] Purdue Univ, Weldon Sch Biomed Engn, W Lafayette, IN 47907 USA
[2] Elmore Family Sch Elect & Comp Engn, W Lafayette, IN 47907 USA
[3] Purdue Univ, Sch Mat Engn, W Lafayette, IN 47907 USA
[4] Hanyang Univ, Sch Mech Engn, Seoul 04763, South Korea
[5] Indiana Univ, Dept Speech Language & Hearing Sci, Bloomington, IN 47408 USA
[6] Purdue Univ, Ctr Implantable Devices, W Lafayette, IN 47907 USA
[7] Purdue Univ, Sch Mech Engn, W Lafayette, IN 47907 USA
来源
PNAS NEXUS | 2024年 / 3卷 / 05期
关键词
bioelectronics; wearable; machine learning; dietary intake; smart neckband; MANAGEMENT; INSULIN; SENSOR;
D O I
10.1093/pnasnexus/pgae156
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. It has proved to be valuable for sports enthusiasts, individuals focused on diet control, and general health monitoring. Its wireless connectivity, ergonomic design, and advanced classification capabilities offer a promising solution for overcoming the limitations of traditional dietary tracking methods, highlighting its potential in personalized healthcare and wellness strategies.
引用
收藏
页数:9
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