Gait Analysis and Mathematical Index-Based Health Management Following Anterior Cruciate Ligament Reconstruction

Sakeran, Hamzah and Abu Osman, Noor Azuan and Abdul Majid, Mohd Shukry and Rahiman, Mohd Hafiz Fazalul and Wan Muhamad, Wan Zuki Azman and Mustafa, Wan Azani (2019) Gait Analysis and Mathematical Index-Based Health Management Following Anterior Cruciate Ligament Reconstruction. Applied Sciences, 9 (21). p. 4680. ISSN 2076-3417, DOI https://doi.org/10.3390/app9214680.

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Official URL: https://doi.org/10.3390/app9214680

Abstract

Gait analysis is recognized as a method used in quantifying gait disorders and in clinical evaluations of patients. However, the current guidelines for the evaluation of post anterior cruciate ligament reconstruction (ACLR) patient outcomes are primarily based on qualitative assessments. This study aims to apply gait analyses and mathematical, index-based health management, using the Mahalanobis Taguchi System (MTS) and the Kanri Distance Calculator (KDC) to diagnose the level of the gait abnormality and to identify its contributing factors following ACLR. It is hypothesized that (1) the method is able to discriminate the gait patterns between a healthy group (HG) and patients with ACLR (PG), and (2) several contributing factors may affect ACLR patients' rehabilitation performance. This study compared the gait of 10 subjects in the PG group with 15 subjects in the HG. The analysis was based on 11 spatiotemporal parameters. Gait data of all subjects were collected in a motion analysis laboratory. The data were then analyzed using MTS and KDC. In this study, two significant groups were recognized: the HG, who achieved results which were within the Mahalanobis space (MS), and (ii) the PG who achieved results above the MS. The results may be seen as being on-target and off-target, respectively. Based on the analysis, three variables (i.e., step width, single support time, and double support time) affected patient performance and resulted in an average mark of above 1.5 Mahalanobis distance (MD). The results indicated that by focusing on the contributing factors that affect the rehabilitation performance of the patients, it is possible to provide individualized and need-based treatment. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Item Type: Article
Funders: UNSPECIFIED
Uncontrolled Keywords: gait analysis; Mahalanobis-Taguchi system; Kanri Distance Calculator; ACLR; rehabilitation
Subjects: R Medicine
T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 24 Jan 2020 02:18
Last Modified: 24 Jan 2020 02:18
URI: http://eprints.um.edu.my/id/eprint/23570

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