Swarm Intelligence Algorithm Based on Plant Root System in 1D Biomedical Signal Feature Engineering to Improve Classification Accuracy

Rui Gong; Kazunori Hase

doi:10.46604/aiti.2023.11169

Authors

Rui Gong Organization of Liberal Arts Education, Mejiro University, Tokyo, Japan; Faculty of Systems Design, Tokyo Metropolitan University, Tokyo, Japan
Kazunori Hase Faculty of Systems Design, Tokyo Metropolitan University, Tokyo, Japan

DOI:

https://doi.org/10.46604/aiti.2023.11169

Keywords:

one-dimensional biomedical signal, feature engineering, plant root system algorithm, swarm intelligence

Abstract

The classification accuracy of one-dimensional (1D) biomedical signals is limited due to the lack of independence of the extracted features. To address this shortcoming, the study applies a swarm intelligence algorithm based on plant root systems (PRSs) to feature engineering. Some basic features of 1D biomedical signals are integrated into a digitized soil, and a root matrix is generated from this digitized soil and the PRS algorithm. The PRS features are extracted from the root matrix and used to classify the basic features. Following classification with the same biomedical signals and classifier, the accuracy of the added PRS set is generally higher than that of the base set. The result shows that the proposed algorithm can expand the application of 1D biomedical signals to include more biomedical signals in classification tasks for clinical diagnosis.

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