Assessment of Quality of Gyrocardiograms Based on Features Derived from Symmetric Projection Attractor Reconstruction
Authors: 
Szymon Siecinski, Muhammad Tausif Irshad, Md Abid Hasan, Ewaryst Tkacz, Marcin GrzegorzekAuthors Info & Claims
Szymon Siecinski, Muhammad Tausif Irshad, Md Abid Hasan, Ewaryst Tkacz, Marcin GrzegorzekAuthors Info & ClaimsArticle No.: 15, Pages 1 - 5
Abstract
Signal quality assessment is essential for biomedical signal processing, analysis, and interpretation. Various methods exist, including averaged numerical values, thresholding, time- or frequency-domain analysis, and nonlinear approaches. This study evaluated the quality of gyrocardiographic signals (GCG) using symmetric projection attractor reconstruction (SPAR) analysis. Two classifiers, random forest and bagged trees, were used to assess the performance of the SPAR-based approach. Eleven features were extracted from the variables v and w, calculated on the basis of the signal delay. These features included minimum and maximum values, mean, standard deviation (SD), median, and Euclidean distance. The results showed that the SPAR-based approach achieved high accuracy, precision, and recall. The random forest classifier achieved 0.729 accuracy, 0.726 precision, and 0.729 recall, while the bagged trees classifier achieved 0.792 accuracy, 0.804 precision, and 0.792 recall. These findings suggest that the SPAR-based approach is a promising method to accurately assess the quality of GCG signals.
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Index Terms
- Assessment of Quality of Gyrocardiograms Based on Features Derived from Symmetric Projection Attractor Reconstruction
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Published In
September 2023
171 pages
ISBN:9798400708169
DOI:10.1145/3615834
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Published: 11 October 2023
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iWOAR 2023
iWOAR 2023: 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence
September 21 - 22, 2023
Lübeck, Germany
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