Edited by: Tarun Goswami, Wright State University, United States
Reviewed by: Lindsey Westover, University of Alberta, Canada; Francesco Travascio, University of Miami, United States
This article was submitted to Biomechanics, a section of the journal Frontiers in Bioengineering and Biotechnology
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Knee braces are a common conservative treatment option for reducing pain and improving function in people with musculoskeletal injuries and disease (Chew et al.,
A new brace concept was recently introduced to provide simultaneous
Levitation™ tricompartment unloader brace (Spring Loaded Technologies, Halifax, Nova Scotia, Canada). Components include straps to attach the brace to the leg, upper and lower carbon-fiber shells, and spring-powered and unpowered hinges. When the knee joint is flexed (e.g., during a squat), the spring-powered lateral hinge applies an assistive extension moment to reduce the user's quadriceps muscle effort. This assistive moment is transferred to the back of the user's leg via reaction forces at the proximal strap (Strap 3) and lower shell and cuff as an anteriorly directed force, ~20 cm above- and below-knee center (Budarick et al.,
There are a wide variety of models in literature that can be used to estimate changes in knee loads due to an assistive brace [see review in Fregly et al. (
Because the TCU brace acts primarily in the sagittal plane, in the present study we chose a planar model of the knee previously described by O'Connor et al. (
The main objective of this study was to use the model, with kinematic and kinetic motion analysis data from healthy participants, to simulate the biomechanical effects of wearing the different TCU brace models during a weight-bearing deep knee flexion activity. The deep knee bend (DKB) test is commonly used in clinical studies of the knee (Stiehl et al.,
Because the intended function of the TCU brace is to reduce TF and PF contact forces during weight-bearing knee flexion, it is important to be confident in the predictions of the model. The secondary objective was therefore to establish the fidelity of the model predictions. To this end, we evaluated the sensitivity of the force predictions to uncertainties in knee model geometry and validated the model output against a criterion standard, in this case the Grand Challenge (GC) data from Fregly et al. (Fregly et al.,
Three-dimensional (3D) human movement data for healthy participants who participated in a different study (Mohamed et al.,
A 3D inverse dynamics model of the lower-leg and foot (McGibbon et al.,
Left: Single degrees-of-freedom kinematic knee model used to determine position and orientation of major load-bearing knee structures (O'Connor et al.,
The knee kinematic model, first described by Kapandji (
Given a prescribed knee flexion angle, the kinematic model outputs the origin and orientation of the ACL and PCL lines of action (LoA), TF contact LoA, hamstring tendon LoA, and LoA of the quadriceps mechanisms (patellar tendon, quadriceps muscle tendon, and PF contact). As such, the force system at the proximal tibia (
Because this was a retrospective simulation where participants' data did not include detailed quantification of subject-specific knee geometry (e.g., medical imaging), it was important to first evaluate the sensitivity of the model to uncertainty in knee geometry input parameters. Therefore, a parameter analysis was conducted using estimated uncertainties of each input parameters of the knee geometry model. Uncertainties were assumed to be δ
In this analysis, inertial contributions (mass, mass moment of inertia, and limb accelerations) and ground reaction forces were assumed true. An expanded Taylor's series was used to combine the parametric output uncertainties (δ
where
In order to determine which parameter uncertainties were most influential, each parameter's contribution (ευi) to the total uncertainty was expressed by rearranging the above equation and normalizing the left side to unity by dividing parameter squared uncertainties by total squared uncertainty.
or
In order to evaluate the overall sensitivity of the force outputs to input geometry uncertainties, the “variability ratio” of mean sum of square errors δ
A variability ratio υ << 1 would indicate that parameter sensitivity is less a concern than natural between-subject variability, whereas υ approaching or greater than unity would suggest model results may not be trusted. We arbitrarily selected a ratio of 20% (υ = 0.2) as the threshold of acceptability.
Finally, to determine the range in which the knee model is valid, a two-legged DKB activity was simulated using published motion capture data from
The simulation was predicated on the assumption that participants could, in theory, produce the same kinematics and ground reaction forces as the non-braced condition for each of the simulated brace conditions (Brandon et al.,
Deep knee bend test:
The design of the TCU brace is detailed elsewhere (Budarick et al.,
Three different TCU brace models (squat, plateau, and general) were considered in this study (
Simulated brace conditions.
No brace | Brace moment is 0 at all knee angles (observed case). |
Brace model 1–squat | Brace moment increases with knee angle in an approximate linear fashion. This brace model should provide the greatest amount of knee assist throughout the range of knee motion of a squat. |
Brace model 2–general | Brace moment increases with knee angle gradually at first and with increasing force at higher flexion angles. This brace model was designed for general purpose use. |
Brace model 3–plateau | Brace moment increases with knee angle but plateaus at ~100–110 degrees of knee flexion. This brace model supports the knee at lower flexion angles. |
Brace moment/angle curves used in the simulation. Green = squat brace (brace #1, linear fit), red = general brace (brace #2, quadratic fit), purple = plateau brace (brace #3, quadratic fit).
We compared non-brace and brace conditions using Statistical Parameter Mapping (SPM), a relatively recent waveform analysis technique. Detailed description of this analysis technique can be found elsewhere (Kiebel and Friston,
Mean knee forces during DKB are shown in
Knee forces during deep knee bend (DKB) using the model (no-brace condition).
Variability ratio (υ) using Equation (4) is plotted as a function of knee flexion angle (for the DKB descent phase) in
Variability ratio (mean sum of square errors δ
Evaluation of the model using data from four participants in the GC dataset is summarized in
Both the sensitivity analysis and the validity analysis indicate that the region of knee flexion where joint forces from the analytical knee model may be considered trustworthy is ~0 to 100 degrees of knee flexion.
SPM analysis results are summarized in
Statistical Parameter Mapping (SPM) results for no-brace condition compared to each simulated brace condition (moment/angle curve). Blue curves represent the no-brace condition. Green represents the squat brace; red represents the general brace, and purple represents the plateau brace. Horizontal bars represent the SPM predicted effectual region where the force curves of each brace condition are significantly different than the no-brace condition. Vertical dashed lines represent the point at which the calculated
Mean knee forces at 90 degrees of flexion during descent and ascent portions of the DKB are summarized in
Knee forces at 90 degrees of knee flexion [units of body weight (BW)] during observed DKB descent and ascent (non-braced) and with three different simulated TCU brace models for healthy participants (
Descent | ||||||||||||||
2.07 | 0.35 | 1.10 | 0.32 | <0.001 | 4.31 | 1.37 | 0.31 | <0.001 | 4.32 | 1.26 | 0.32 | <0.001 | 4.30 | |
3.46 | 0.59 | 1.84 | 0.54 | <0.001 | 4.31 | 2.29 | 0.52 | <0.001 | 4.32 | 2.10 | 0.53 | <0.001 | 4.30 | |
4.13 | 0.70 | 2.19 | 0.64 | <0.001 | 4.31 | 2.73 | 0.63 | <0.001 | 4.33 | 2.51 | 0.63 | <0.001 | 4.30 | |
2.96 | 0.47 | 1.66 | 0.40 | <0.001 | 4.27 | 2.01 | 0.41 | <0.001 | 4.37 | 1.86 | 0.41 | <0.001 | 4.29 | |
0.00 | 0.00 | 0.02 | 0.02 | 0.049 | −0.84 | 0.01 | 0.01 | 0.351 | −0.35 | 0.01 | 0.02 | 0.281 | −0.41 | |
0.50 | 0.15 | 0.16 | 0.11 | <0.001 | 4.66 | 0.23 | 0.13 | <0.001 | 4.12 | 0.20 | 0.12 | <0.001 | 4.24 | |
Ascent | ||||||||||||||
2.10 | 0.28 | 1.12 | 0.24 | <0.001 | 4.27 | 1.39 | 0.23 | <0.001 | 4.27 | 1.28 | 0.23 | <0.001 | 4.28 | |
3.50 | 0.47 | 1.88 | 0.39 | <0.001 | 4.28 | 2.33 | 0.38 | <0.001 | 4.27 | 2.14 | 0.39 | <0.001 | 4.29 | |
4.19 | 0.57 | 2.24 | 0.47 | <0.001 | 4.27 | 2.78 | 0.46 | <0.001 | 4.27 | 2.56 | 0.46 | <0.001 | 4.28 | |
2.97 | 0.41 | 1.67 | 0.33 | <0.001 | 4.74 | 2.02 | 0.34 | <0.001 | 4.47 | 1.87 | 0.34 | <0.001 | 4.59 | |
0.00 | 0.00 | 0.01 | 0.03 | 0.148 | −0.57 | 0.00 | 0.00 | — | — | 0.01 | 0.01 | 0.179 | −0.53 | |
0.48 | 0.11 | 0.13 | 0.09 | <0.001 | 7.23 | 0.21 | 0.11 | <0.001 | 5.09 | 0.19 | 0.10 | <0.001 | 7.00 |
Knee forces were significantly (
Unloading of joint contact forces is widely recognized as a best practice in the conservative care of knee OA patients and may be achieved through a range of strategies including BW reduction, activity modification, strengthening/exercise, and the use of walking aids or knee braces (Sarzi-Puttini et al.,
Compared to the non-braced condition, significant force reduction was predicted for all major structures of the knee during the DKB task for the simulated TCU braced conditions. Because of its large assistive moment (
It was also apparent that the effectual region was not symmetric with respect to descent and ascent phases. As shown in
The observed reduction in QT force with all three brace models suggests reduced sagittal plane muscle effort with TCU brace use. This provides evidence in support of the proposed mechanism of unloading, whereby reduced quadriceps muscle effort is expected to correspond with reduced force in knee joint structures. The current findings show significant reductions in both TF and PF joint contact forces with all three brace models, demonstrating that the TCU brace is capable of providing simultaneous unloading benefits to multiple compartments in the knee. Although our study was planar and therefore unable to quantify force sharing between medial and lateral TF compartments, given the mechanism of unloading (reduced QT and PT forces), it can be reasonably expected that both medial and lateral compartments would experience unloading during the DKB.
This finding differentiates the TCU from traditional unicompartment off-loader braces that are restricted to providing an unloading effect to one side of the TF joint by redistributing (or “off-loading”) forces to the opposite side of the knee (Gross and Hillstrom,
The TCU may be of particular interest in the treatment of PF disorders resulting in PF pain such as trochlear dysplasia, chondromalacia, patellar tendonitis, and OA. These PF conditions are considered challenging to treat (McCarthy and Strickland,
The knee model results were largely consistent with results from other knee models evaluated during squat or DKB, in terms of the relative magnitudes of the QT, PT and PF forces (Nisell et al.,
Overall, the knee model performed well under small (+/−5 mm or +/−5 degrees) perturbations in the geometric inputs.
Lower limb bone geometry can be measured with very high accuracy using medical imaging techniques (Van den Broeck et al.,
This conclusion was also borne out by the GC analysis, which showed acceptable agreement (RMSE = 0.7 BW) between instrumented and calculated TF force until ~100 degrees of flexion (or 1.1 BW across the entire range of movement), with mean prediction errors centered near zero (
Finally, the parameter sensitivity analysis performed at 90 degrees of knee flexion (Figure A3) may be useful for identifying the most important variables in the model. For example, the PF and QT forces were most sensitive to the radius of curvature of the PF notch, whereas TF contact forces were most sensitive to the length of the AC ligament and a variety of anatomical measures of the femoral condyle. These findings point to the need for accurate, subject-specific musculoskeletal anatomy to ensure valid force predictions at more extreme knee angles.
While the predicted reductions in knee joint tissue forces with the simulated TCU brace were considerable, they should be considered carefully in light of some of the limitations of the study. For example, we assumed in the simulation that participants were able to adapt muscle effort to produce identical kinematics and kinetics of the lower leg with and without the brace. Support for this assumption is provided by biomechanical studies of experimental exoskeletons that provide an assistive moment to joints of the lower extremity (Kao et al.,
We also assumed the brace has perfect force transmission to the user (i.e., the spring force in the brace is entirely transmitted as a force perpendicular to the tibia) and that the brace does not deflect or become misaligned with the knee axis of rotation. Future studies applying the brace to human subjects directly will require a means of quantifying force transmission at the skin interface and moment arm of the brace(s) to verify the assistive moment being generated.
In general, the knee model overestimated
We interpret our findings as tricompartmental unloading, yet we cannot directly confirm unloading of both medial and lateral condyles of the TF joint with the model we used. The TF contact model is represented in our study by a single set of articulating condyles; therefore, we could only compute the overall joint contact force and not the medial and lateral distribution. It stands to reason, though, that a reduction in knee extensor muscle force would reduce the contact force for both medial and lateral condyles.
A final limitation of this study was the fact that the resulting sample was six females and two males, which prevented any meaningful comparison of biological sex.
The biomechanical analysis of the simulated TCU brace provides proof-of-concept evidence in support of a TCU knee extension-assist brace to significantly reduce forces for all major knee structures during a DKB. The primary mechanism of unloading was reduction of muscle forces, which reduced forces transmitted to all internal structures of the knee. Three different TCU brace models were simulated, which altered the degree of brace assistance as expected. This suggests the technology can be developed to provide a customized level of assistance, all which should have a benefit in reducing knee forces, which is the intended benefit of the TCU brace.
Data supporting the conclusions of this article will be made available by the authors, without undue reservation.
The studies involving human participants were reviewed and approved by University of New Brunswick, Research Ethics Board. Written informed consent for participation was not required for this secondary study in accordance with the national legislation and the institutional requirements.
All authors contributed to the interpretation of the data and drafting the manuscript. CM wrote the computer code for the biomechanical analysis, acquired the data used in the study and conducted the statistical analysis. EB and CM developed the knee model sensitivity analysis. SB conducted the Grand Challenge analysis. EB and CC-S generated the brace model data. All authors have read and approved the final submitted version.
CC-S was President and CEO of Spring Loaded Technologies Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The authors thank students and staff of the UNB Institute of Biomedical Engineering, the Andrew and Marjorie McCain Human Performance Laboratory (UNB Faculty of Kinesiology), and Mr. Bradley Mackeil from Spring Loaded Technology.
The Supplementary Material for this article can be found online at: