Analysis of data from biomedical multisensor optical systems

Mazing M.S., Zaitceva A.Y., Novikov L.V.

For Russian citation (Opticheskii Zhurnal):

Мазинг М.С., Зайцева А.Ю., Новиков Л.В. Анализ данных медико-биологических мультисенсорных оптических систем // Оптический журнал. 2024. Т. 91. № 7. С. 121–131. http://doi.org/10.17586/1023-5086-2024-91-07-121-131

Mazing M.S., Zaitseva A.Yu., Novikov L.V. Analysis of data from medical and biological multisensor optical systems [in Russian] // Opticheskii Zhurnal. 2024. V. 91. № 7. P. 121–131. http://doi.org/10.17586/1023-5086-2024-91-07-121-131

For citation (Journal of Optical Technology):

Abstract:

Subject of study. Multisensor optical systems intended for biomedical research, and the methodology for applying the multisensor approach in optical biomedical diagnostics. The aim of study. Development and detailed study of a multichannel optical system designed for collecting, transmitting and subsequent analysis of diagnostic information, as well as the development of an effective algorithm for preprocessing a large volume of optical signals describing the state of a biological object, using data mining methods. Method. Methods for mining multidimensional data as applied to a multisensory approach to ranking optical spectroscopy signals. Main results. A small-sized optical multisensor system for biomedical diagnostics is presented, which includes an array of 18 photodiode sensitive elements with selective sensitivity to the visible and infrared ranges of optical radiation at wavelengths from 410 to 940 nm. The stages of analysis of multidimensional information received from the system are described, in which the use of the principal component method and cluster analysis algorithms is proposed. An experimental study was conducted with the participation of subjects, which confirmed the effectiveness of the proposed approaches. Using data mining methods, the results of ranking the subjects were visualized, which made it possible to identify hidden patterns in the functional state of microcirculatory tissue systems according to the readings of an array of optical sensors. Practical significance. The results of the research can be used in the design of automated complexes based on optical multisensor systems to solve problems of identification and analysis of the functional state of complex multicomponent biological tissues and fluids of the human body.

Keywords:

multisensor optical system, optical spectroscopy, data mining, principal component analysis

Acknowledgements:

this work was supported by the Russian Science Foundation, project № 24-21-00404.

OCIS codes: 170.3880, 170.1470, 170.4580

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