2023-05-22 カリフォルニア大学サンディエゴ校(UCSD)
◆このシステムは、心血管モニタリングに利用され、深部組織の信号を連続的に測定できます。柔軟な制御回路と機械学習のアルゴリズムを組み合わせることで、データの解釈と動く被験者の追跡が可能となりました。
◆この技術は健康管理や医療診断に革新をもたらす可能性があります。
<関連情報>
- https://today.ucsd.edu/story/a-giant-leap-forward-in-wireless-ultrasound-monitoring-for-subjects-in-motion
- https://www.nature.com/articles/s41587-023-01800-0
動く被験者の深部組織をモニターする完全統合型ウェアラブル超音波システム A fully integrated wearable ultrasound system to monitor deep tissues in moving subjects
Muyang Lin,Ziyang Zhang,Xiaoxiang Gao,Yizhou Bian,Ray S. Wu,Geonho Park,Zhiyuan Lou,Zhuorui Zhang,Xiangchen Xu,Xiangjun Chen,Andrea Kang,Xinyi Yang,Wentong Yue,Lu Yin,Chonghe Wang,Baiyan Qi,Sai Zhou,Hongjie Hu,Hao Huang,Mohan Li,Yue Gu,Jing Mu,Albert Yang,Amer Yaghi,Yimu Chen,Yusheng Lei,Chengchangfeng Lu,Ruotao Wang,Joseph Wang,Shu Xiang,Erik B. Kistler,Nuno Vasconcelos & Sheng Xu
Nature Biotechnology Published:22 May 2023
DOI:https://doi.org/10.1038/s41587-023-01800-0
Abstract
Recent advances in wearable ultrasound technologies have demonstrated the potential for hands-free data acquisition, but technical barriers remain as these probes require wire connections, can lose track of moving targets and create data-interpretation challenges. Here we report a fully integrated autonomous wearable ultrasonic-system-on-patch (USoP). A miniaturized flexible control circuit is designed to interface with an ultrasound transducer array for signal pre-conditioning and wireless data communication. Machine learning is used to track moving tissue targets and assist the data interpretation. We demonstrate that the USoP allows continuous tracking of physiological signals from tissues as deep as 164 mm. On mobile subjects, the USoP can continuously monitor physiological signals, including central blood pressure, heart rate and cardiac output, for as long as 12 h. This result enables continuous autonomous surveillance of deep tissue signals toward the internet-of-medical-things.
