An EMG-Assisted Muscle-Force Driven Finite Element Analysis Pipeline to Investigate Joint- and Tissue-Level Mechanical Responses in Functional Activities: Towards a Rapid Assessment Toolbox

Abstract

Joint tissue mechanics (e.g., stress and strain) are believed to have a major involvement in the onset and progression of musculoskeletal disorders, e.g., knee osteoarthritis (KOA). Accordingly, considerable efforts have been made to develop musculoskeletal finite element (MS-FE) models to estimate highly detailed tissue mechanics that predict cartilage degeneration. However, creating such models is time-consuming and requires advanced expertise. This limits these complex, yet promising, MS-FE models to research applications with few participants and makes the models impractical for clinical assessments. Also, these previously developed MS-FE models have not been used to assess activities other than gait. This study introduces and verifies a semi-automated rapid state-ofthe-art MS-FE modeling and simulation toolbox incorporat-

Toward Tailored Rehabilitation by Implementation of a Novel Musculoskeletal Finite Element Analysis Pipeline

“…However, since marker-based motion analysis are reported to be inaccurate in estimating knee secondary kinematics during dynamic activities [51], the knee's extra DoFs for all the MS models were either locked (e.g., abduction/adduction and internal/external rotations) or defined as a function of the knee flexion angle (e.g., tibiofemoral translations and patella DoFs) [50], [52]. Importantly, previous studies, including ours on the development of the current workflow [21], [36], [37], [53], have shown that a 12 DoFs FE knee model driven by a 1 DoF knee EMG-assisted MS model is capable of estimating knee joint kinetics, secondary kinematics, and tissue mechanics consistent with in vivo data and those of a similar FE model when driven by a 12 DoFs knee MS model. Likewise, it has been reported that muscle activation patterns, as used in the current study to inform the MS analyses, are directed to effectively stabilize knee abduction/adduction moment and well estimate JCFs even when using an MS model with a 1 DoF knee joint [54].…”

“…Hence, the OpenSim API for MATLAB and scaled models (i.e., 15 MS models in total) were used to execute inverse kinematics, inverse dynamics (to calculate knee external moments), and SO-based muscle force estimation. Then muscle moment arms, muscle-tendon lengths, and tibiofemoral and patellofemoral JCFs were calculated using OpenSim analysis toolbox via the API (i.e., muscle analysis and joint reaction tools, respectively) [36]. Muscle moment arms and muscle-tendon lengths were calculated to be used as input to the EMG-assisted MS model (section II.B.2), and later to calculate the corresponding inputs for the FE models of the study (section II.C.2) (Fig.…”

“…1). The muscle moment arms were extracted for flexion/extension, abduction/adduction, and internal/external DoFs of both the tibiofemoral and patellofemoral joints [36]. For the sake of clarity, we note that in this manuscript, JCF in the MS analysis refers to the joint reaction force reported by the OpenSim joint reaction analysis tool [61].…”

“…Nevertheless, remarkable efforts are made to develop knee joint MS-FE models capable of incorporating a 12 degrees of freedom (DoFs) knee joint [21], [23], [29]- [33], complex soft tissue material models [21], [34], [35], and subject's muscle activation patterns (EMG-assistance) [36], [37]. However, previous studies have investigated only healthy subjects [21], [34], [38], used simplified joint models in terms of limited DoFs [9], [39], did not include subject-specific joint geometries [9], [38], [39] and muscle activation patterns [22], [23], [32], [34], [38]- [40], neglected crucial joint tissues such as menisci [9], [38], and/or employed simplistic soft tissue material models [31], [38].…”

“…Here in the current study, we aimed to evaluate the mechanical responses of knee cartilages and menisci, particularly those related to the fibrillar (collagen) and nonfibrillar (proteoglycans) matrices, of individuals with KOA while they performed different daily activities and rehabilitation exercises. For this aim, we utilized a previously developed semi-automatic atlas-based MS-FE modeling pipeline [36], considering subject-specific muscle activation patterns and the FRP(V)E material model of cartilages and menisci. We hypothesized that the novel EMG-assisted MS-FE modeling method would show highly personalized mechanical responses of cartilage, indicative of tissue health and degeneration, in different functional activities.…”