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.
Highlights
Gait analysis aims to determine the factors that influence a person to walk in the manner that he/she does
Gait analysis has been used in clinical settings for several disorders, including cerebral palsy, Parkinson’s disease, muscular dystrophy, osteoarthritis, rheumatoid arthritis, lower limb amputation, head injury, stroke, spinal cord injury, myelodysplasia, and multiple sclerosis
This study aims to utilize mathematical formulations, including Mahalanobis–Taguchi System (MTS) as a diagnosis system and the Kanri Model as high impact prescription tool, to monitor, diagnose, and plan the actions to be taken based on the findings
Summary
Gait analysis aims to determine the factors that influence a person to walk in the manner that he/she does. Gait analysis has been used in clinical settings for several disorders, including cerebral palsy, Parkinson’s disease, muscular dystrophy, osteoarthritis, rheumatoid arthritis, lower limb amputation, head injury, stroke, spinal cord injury, myelodysplasia, and multiple sclerosis. This analytical method is widely used to organize surgery in the case of cerebral palsy and multiple joint disease, to produce unique insoles, to prescribe footwear, to schedule and monitor physiotherapy in various illnesses such as hemiplegia, to predict future issues such as foot ulceration in peripheral neuropathy, and to monitor the manufacturing and application of orthoses and prostheses
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
