AI Article Synopsis

  • ACL rehabilitation involves multiple phases, guided by subjective assessments of activities like running and jumping, while understanding knee loading is essential for creating effective therapy plans.
  • Current methods for measuring knee joint forces require costly lab equipment, but researchers are exploring using Inertial Measurement Units (IMUs) and algorithms for easier, more accessible assessments.
  • A systematic review indicates that IMUs can accurately estimate kinetic parameters during rehabilitation, though improvements are needed for better application in diverse patient populations, particularly those recovering from ACL injuries.

Article Abstract

After an ACL injury, rehabilitation consists of multiple phases, and progress between these phases is guided by subjective visual assessments of activities such as running, hopping, jump landing, etc. Estimation of objective kinetic measures like knee joint moments and GRF during assessment can help physiotherapists gain insights on knee loading and tailor rehabilitation protocols. Conventional methods deployed to estimate kinetics require complex, expensive systems and are limited to laboratory settings. Alternatively, multiple algorithms have been proposed in the literature to estimate kinetics from kinematics measured using only IMUs. However, the knowledge about their accuracy and generalizability for patient populations is still limited. Therefore, this article aims to identify the available algorithms for the estimation of kinetic parameters using kinematics measured only from IMUs and to evaluate their applicability in ACL rehabilitation through a comprehensive systematic review. The papers identified through the search were categorized based on the modelling techniques and kinetic parameters of interest, and subsequently compared based on the accuracies achieved and applicability for ACL patients during rehabilitation. IMUs have exhibited potential in estimating kinetic parameters with good accuracy, particularly for sagittal movements in healthy cohorts. However, several shortcomings were identified and future directions for improvement have been proposed, including extension of proposed algorithms to accommodate multiplanar movements and validation of the proposed techniques in diverse patient populations and in particular the ACL population.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11014074PMC
http://dx.doi.org/10.3390/s24072163DOI Listing

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