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pro vyhledávání: '"Manjin Xu"'
Autor:
Manjin Xu, Huixia Niu, Lizhi Wu, Mingluan Xing, Zhe Mo, Zhijian Chen, Xueqing Li, Xiaoming Lou
Publikováno v:
Metabolites, Vol 14, Iss 9, p 504 (2024)
Microplastics are emerging pollutants that have garnered significant attention, with evidence suggesting their association with the pathogenesis of type 2 diabetes mellitus. In order to assess the impact of polystyrene microplastic exposure on altera
Externí odkaz:
https://doaj.org/article/4ef20995afa34e558403841cc47d83f7
Autor:
Huixia Niu, Manjin Xu, Pengcheng Tu, Yunfeng Xu, Xueqing Li, Mingluan Xing, Zhijian Chen, Xiaofeng Wang, Xiaoming Lou, Lizhi Wu, Shengzhi Sun
Publikováno v:
Toxics, Vol 12, Iss 1, p 47 (2024)
Emerging contaminants have been increasingly recognized as critical determinants in global public health outcomes. However, the intricate relationship between these contaminants and glucose metabolism remains to be fully elucidated. The paucity of co
Externí odkaz:
https://doaj.org/article/dc91f34a7e3c4d79abbaa4692eee4019
Publikováno v:
Sensors, Vol 21, Iss 21, p 7002 (2021)
Surface electromyography (sEMG) is a kind of biological signal that records muscle activity noninvasively, which is of great significance in advanced human-computer interaction, prosthetic control, clinical therapy, and biomechanics. However, the num
Externí odkaz:
https://doaj.org/article/8e6f7afe8d1346c99716328529116b03
Publikováno v:
Sensors (Basel, Switzerland)
Sensors, Vol 21, Iss 7002, p 7002 (2021)
Sensors
Volume 21
Issue 21
Sensors, Vol 21, Iss 7002, p 7002 (2021)
Sensors
Volume 21
Issue 21
Surface electromyography (sEMG) is a kind of biological signal that records muscle activity noninvasively, which is of great significance in advanced human-computer interaction, prosthetic control, clinical therapy, and biomechanics. However, the num
Publikováno v:
2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE).
Surface electromyography(sEMG) can reflect the state of muscle activity which has important application value in human-computer interaction, prosthetic control and clinical diagnosis. In this paper, a gesture recognition method based on convolutional