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<p>The human body emanated metabolic odor encompass biometric information used for tracking metabolic conditions of individuals. The challenge of decoding these long-unappreciated physiological signals of metabolic states impedes the development of technologies for real-time monitoring and next-generation personal health digitization. Here we introduce a monolithic AI-wearable biometric ring designed to non-invasively and reliably monitor skin volatile-organic-compounds associated with diet-related metabolism. The ring utilizes the attention-based feature fusion algorithm on a miniaturized olfactory sensor chip, incorporating three-dimensional vertical hetero-interfaces within a small footprint of 0.0081 mm². It discriminates six categories of diet-induced emanated volatile-organic-compound patterns, three physical activities, and quantifies food intake with a 0.991 determination coefficient. Through gas chromatography-mass spectrometry validation and the personalized AI health agent, our biometric ring demonstrates broad efficacy in human body odor monitoring with evident diet-induced metabolic adherence.</p>

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Miniaturized olfactory sensor chip-based AI-wearable biometric ring for human body metabolic odor analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月27日

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  • Wenhao Ye,
  • Ruochen Ding,
  • Chen Wang,
  • Wenying Tang,
  • Daquan Zhang,
  • Xiao Qiu,
  • Swapnadeep Poddar,
  • Zixi Wan,
  • Chak Lam Jonathan Chan,
  • Feng Xue,
  • Yu Fu,
  • Beitao Ren,
  • Bin Wang,
  • Yu Zhou,
  • Zhenghao Long,
  • Yucheng Ding,
  • Weiqi Zhang,
  • Zhu’an Wan,
  • Jianhao Zhao,
  • Yuanjing Lin,
  • Zhiyong Fan

摘要

The human body emanated metabolic odor encompass biometric information used for tracking metabolic conditions of individuals. The challenge of decoding these long-unappreciated physiological signals of metabolic states impedes the development of technologies for real-time monitoring and next-generation personal health digitization. Here we introduce a monolithic AI-wearable biometric ring designed to non-invasively and reliably monitor skin volatile-organic-compounds associated with diet-related metabolism. The ring utilizes the attention-based feature fusion algorithm on a miniaturized olfactory sensor chip, incorporating three-dimensional vertical hetero-interfaces within a small footprint of 0.0081 mm². It discriminates six categories of diet-induced emanated volatile-organic-compound patterns, three physical activities, and quantifies food intake with a 0.991 determination coefficient. Through gas chromatography-mass spectrometry validation and the personalized AI health agent, our biometric ring demonstrates broad efficacy in human body odor monitoring with evident diet-induced metabolic adherence.