Difference between revisions of "Functional data analysis for BCI and biomedical signals"

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(Created page with "''Vadim'', 2023 =Functional data analysis for brain-computer interfaces and biomedical signal analysis= <!-- My research focuses on the problems of model selection in Mach...")
 
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''[[Vadim]]'', 2023
 
''[[Vadim]]'', 2023
=Functional data analysis for brain-computer interfaces and biomedical signal analysis=
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=Functional data analysis for brain-computer interfaces and biomedical signals=
 
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My research focuses on the problems of model selection in Machine Learning. It explores methods of Applied Mathematics and Computer Science. The central issue is to select the most accurate, robust, and simplest model. This model forecasts spatial time series, and measurements in medicine, biology, and physics. The practical applications are brain-computer interfaces, health monitoring with wearable devices, human behavior analysis, and classification of human motions in sports and computer games.  
 
My research focuses on the problems of model selection in Machine Learning. It explores methods of Applied Mathematics and Computer Science. The central issue is to select the most accurate, robust, and simplest model. This model forecasts spatial time series, and measurements in medicine, biology, and physics. The practical applications are brain-computer interfaces, health monitoring with wearable devices, human behavior analysis, and classification of human motions in sports and computer games.  

Revision as of 20:23, 11 October 2022

Vadim, 2023

Functional data analysis for brain-computer interfaces and biomedical signals

Brain signal classification and dimensionality reduction

Biomedical signal decoding and multi-modeling

Continous-time physical activity recognition

Wearable device mapping

Hand movement recognition

Heterogeneous data and multi-modeling