European Academy of Natural Sciences Hannover e.V.

Yin Jibin

Prof. Yin Jibin achieved his Ph.D. degree in Human-Computer Interaction from Kochi University of Technology (KUT), Japan, and was a postdoctoral researcher at the Multimedia Laboratory of National University of Singapore (NUS), where he worked as an assistant professor in the Human-Computer Interaction Laboratory of KUT. Currently, he is a professor in Kunming University of Science and Technology, the director of Intelligent Human-Computer Interaction Laboratory, and the director of Yunnan Pervasive Computing Technology Research Institute. He has many years of research experience in the field of Intelligent Human-Computer Interaction, Wearable Devices, and Big Data Analytics, and he has chaired/participated in more than 10 projects of the National Natural Science Foundation of China and the Provincial Foundation of China, and he has published more than 60 papers in international high-level journals and conferences. He has been selected for Nanjing 321 Talent Program, Xiamen “Double Hundred Talents” Program and Yunnan Province Vice President of Science and Technology Talent Program. He has been invited to present 3 times at the conferences, served as Deputy Editor-in-Chief of the international conference IEEE AIM2010-2018, Vice Chairman of AIM 2020, member of IEEE, member of ACM, Deputy Editor-in-Chief of JMI, and member of National Standardization Working Group of Special Operation Robotics. Member of Special Operation Robot Standardization Working Group.

Prof. Yin Jibin led theoretical and technological research focusing on intelligent medical and elderly care technologies and systems, experimental prototype development and product application demonstration, and researched and developed new types of low-power biomedical sensors for monitoring, guarding and management of the elderly and chronic high incidence of diseases, as well as intelligent telecare systems based on big data, in response to the problem of the aging of the population and the demand for integration of medical care and healthcare.

Major scientific achievements:

1. Development of a muscular robot based on motor intent recognition.
2. Proposing a health monitoring algorithm based on physiological data-driven machine learning models.
3. Functional Design of Multifunctional Intelligent Nursing System.
4. Continuous non-contact monitoring of key vital signs and health conditions.
5. Recognition of defecation intention based on spectral analysis of human electrical impedance.
6. Trunk plyometric training based on motor intention recognition.

 

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