Research on physiological signal analysis based on clinical statistics and machine learning

Jiaqi Feng

doi:10.1117/12.2669358

24 March 2023 Research on physiological signal analysis based on clinical statistics and machine learning

Jiaqi Feng

Proceedings Volume 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022); 126112G (2023) https://doi.org/10.1117/12.2669358
Event: International Conference on Biological Engineering and Medical Science (ICBioMed2022), 2022, Oxford, United Kingdom

Abstract

Neural network evaluation and decoding technology based on physiological signal analysis has become a hot research topic in the field of life and health. The decoding of physiological signals can enable people to break through physical limitations to communicate with the external environment, and can also enhance the effectiveness of the human body by evaluating people's cognitive and motor functions. Electroencephalogram (EEG), as a kind of physiological signal, has become a hot spot of much research due to its non-invasive, high time precision and strong explanatory characteristics. This paper summarizes the applied research based on physiological signal analysis such as EEG from three aspects of evaluation technology, human-computer interaction and clinical application, and looks forward to the development direction in the future.

Citation Download Citation

Jiaqi Feng "Research on physiological signal analysis based on clinical statistics and machine learning", Proc. SPIE 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022), 126112G (24 March 2023); https://doi.org/10.1117/12.2669358

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available