Version 1
: Received: 19 August 2024 / Approved: 19 August 2024 / Online: 19 August 2024 (12:21:16 CEST)
How to cite:
Kim, W.; Joe, H.; Kim, H.-S.; Yoon, D. Interpretable Support Vector Machine and Its Application to Rehabilitation Assessment. Preprints2024, 2024081286. https://doi.org/10.20944/preprints202408.1286.v1
Kim, W.; Joe, H.; Kim, H.-S.; Yoon, D. Interpretable Support Vector Machine and Its Application to Rehabilitation Assessment. Preprints 2024, 2024081286. https://doi.org/10.20944/preprints202408.1286.v1
Kim, W.; Joe, H.; Kim, H.-S.; Yoon, D. Interpretable Support Vector Machine and Its Application to Rehabilitation Assessment. Preprints2024, 2024081286. https://doi.org/10.20944/preprints202408.1286.v1
APA Style
Kim, W., Joe, H., Kim, H. S., & Yoon, D. (2024). Interpretable Support Vector Machine and Its Application to Rehabilitation Assessment. Preprints. https://doi.org/10.20944/preprints202408.1286.v1
Chicago/Turabian Style
Kim, W., Hyun-Suk Kim and Daesub Yoon. 2024 "Interpretable Support Vector Machine and Its Application to Rehabilitation Assessment" Preprints. https://doi.org/10.20944/preprints202408.1286.v1
Abstract
This paper presents an interpretable support vector machine (SVM) and its application to rehabilitation assessment. We introduce the concept of nearest boundary point to standardize the one-class SVM decision function and determine the shortest path for data from abnormal cases to become those from normal cases. This analytical approach is computationally simple and provides a unique solution. The nearest boundary point of abnormal data can also be used to analyze the cause of abnormal classification and indicate countermeasures for normalization. These properties render the proposed interpretable SVM valuable for medical assessment applications and other problems that require careful consideration of classification results for treatment. Simulation and application results demonstrate the feasibility and effectiveness of the proposed method.
Keywords
interpretable support vector machine; muscle function assessment; nearest boundary problem; rehabilitation
Subject
Public Health and Healthcare, Physical Therapy, Sports Therapy and Rehabilitation
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
