Singular Spectrum Analysis of Tremorograms for Human Neuromotor Reaction Estimation
Singular spectrum analysis (SSA) is a method of time series analysis and is used in various fields, including medicine. A tremorogram is a biological signal that allows evaluation of a person’s neuromotor reactions in order to infer the state of the motor parts of the central nervous system (CNS). A...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/10/11/1794 |
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| author | Olga Bureneva Nikolay Safyannikov Zoya Aleksanyan |
| author_facet | Olga Bureneva Nikolay Safyannikov Zoya Aleksanyan |
| author_sort | Olga Bureneva |
| collection | DOAJ |
| description | Singular spectrum analysis (SSA) is a method of time series analysis and is used in various fields, including medicine. A tremorogram is a biological signal that allows evaluation of a person’s neuromotor reactions in order to infer the state of the motor parts of the central nervous system (CNS). A tremorogram has a complex structure, and its analysis requires the use of advanced methods of signal processing and intelligent analysis. The paper’s novelty lies in the application of the SSA method to extract diagnostically significant features from tremorograms with subsequent evaluation of the state of the motor parts of the CNS. The article presents the application of a method of singular spectrum decomposition, comparison of known variants of classification, and grouping of principal components for determining the components of the tremorogram corresponding to the trend, periodic components, and noise. After analyzing the results of the SSA of tremorograms, we proposed a new algorithm of grouping based on the analysis of singular values of the trajectory matrix. An example of applying the SSA method to the analysis of tremorograms is shown. Comparison of known clustering methods and the proposed algorithm showed that there is a reasonable correspondence between the proposed algorithm and the traditional methods of classification and pairing in the set of periodic components. |
| first_indexed | 2024-03-10T01:07:01Z |
| format | Article |
| id | doaj.art-054c8455f5bf409d81ed108e6ed7f90e |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T01:07:01Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-054c8455f5bf409d81ed108e6ed7f90e2023-11-23T14:24:36ZengMDPI AGMathematics2227-73902022-05-011011179410.3390/math10111794Singular Spectrum Analysis of Tremorograms for Human Neuromotor Reaction EstimationOlga Bureneva0Nikolay Safyannikov1Zoya Aleksanyan2Department of Computer Science and Engineering, Saint Petersburg Electrotechnical University «LETI», 197022 Saint Petersburg, RussiaDepartment of Computer Science and Engineering, Saint Petersburg Electrotechnical University «LETI», 197022 Saint Petersburg, RussiaInstitute of the Human Brain, Russian Academy of Sciences, 197376 Saint Petersburg, RussiaSingular spectrum analysis (SSA) is a method of time series analysis and is used in various fields, including medicine. A tremorogram is a biological signal that allows evaluation of a person’s neuromotor reactions in order to infer the state of the motor parts of the central nervous system (CNS). A tremorogram has a complex structure, and its analysis requires the use of advanced methods of signal processing and intelligent analysis. The paper’s novelty lies in the application of the SSA method to extract diagnostically significant features from tremorograms with subsequent evaluation of the state of the motor parts of the CNS. The article presents the application of a method of singular spectrum decomposition, comparison of known variants of classification, and grouping of principal components for determining the components of the tremorogram corresponding to the trend, periodic components, and noise. After analyzing the results of the SSA of tremorograms, we proposed a new algorithm of grouping based on the analysis of singular values of the trajectory matrix. An example of applying the SSA method to the analysis of tremorograms is shown. Comparison of known clustering methods and the proposed algorithm showed that there is a reasonable correspondence between the proposed algorithm and the traditional methods of classification and pairing in the set of periodic components.https://www.mdpi.com/2227-7390/10/11/1794time series analysissingular spectrum analysis (SSA)principal component analysistime series classification |
| spellingShingle | Olga Bureneva Nikolay Safyannikov Zoya Aleksanyan Singular Spectrum Analysis of Tremorograms for Human Neuromotor Reaction Estimation Mathematics time series analysis singular spectrum analysis (SSA) principal component analysis time series classification |
| title | Singular Spectrum Analysis of Tremorograms for Human Neuromotor Reaction Estimation |
| title_full | Singular Spectrum Analysis of Tremorograms for Human Neuromotor Reaction Estimation |
| title_fullStr | Singular Spectrum Analysis of Tremorograms for Human Neuromotor Reaction Estimation |
| title_full_unstemmed | Singular Spectrum Analysis of Tremorograms for Human Neuromotor Reaction Estimation |
| title_short | Singular Spectrum Analysis of Tremorograms for Human Neuromotor Reaction Estimation |
| title_sort | singular spectrum analysis of tremorograms for human neuromotor reaction estimation |
| topic | time series analysis singular spectrum analysis (SSA) principal component analysis time series classification |
| url | https://www.mdpi.com/2227-7390/10/11/1794 |
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