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AI-Enabled Wearable and Flexible Electronics for Assessing Full Personal Exposures.
Shan, Guangcun; Li, Xin; Huang, Wei.
Afiliação
  • Shan G; School of Instrumentation Science and Opto-electronics Engineering, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Beihang University, 100191 Beijing, China.
  • Li X; School of Instrumentation Science and Opto-electronics Engineering, Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Beihang University, 100191 Beijing, China.
  • Huang W; Shaanxi Institute of Flexible Electronics, Northwestern Polytechnical University, 710072 Xi'an, China.
Innovation (Camb) ; 1(2): 100031, 2020 Aug 28.
Article em En | MEDLINE | ID: mdl-34557709
ABSTRACT
Research on the exposome has been extended to personal exposures, and full assessment of personal exposures is of great significance for personal health monitoring and epidemiological studies. Compared with static measurement instruments, wearable sensors are more suitable for dynamic personal exposures assessment. The development of flexible wearable sensors with the features of being physically comfortable and easy to use can be a promising solution for the measurement of personal exposures. With the support of big data and AI, large-scale personal exposures assessment could foster the transition from population-based to individual-based epidemiological studies and upgrade the intelligence level of medical services.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Innovation (Camb) Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Innovation (Camb) Ano de publicação: 2020 Tipo de documento: Article