This study addresses the critical need for self-powered, durable pressure sensors in total knee replacement (TKR) implants to enable the collection of postoperative information. The scope of this research encompasses the design, development, and testing of a triboelectric nanogenerator (TENG) integrated into an instrumented knee implant for energy harvesting and pressure sensing. The authors' unique approach involves utilizing a porous silicone rubber as a dielectric material. This allows the TENG to withstand forces up to 2000 N and generate a maximum power output of 18 μ W . Theoretical modeling combined with experimental validation provides deeper insight into the fundamental operating principles. We elucidate the TENG output performance under an MTS servo-hydraulic load frame compared with a VIVO joint simulator. Other important characteristics, such as load sensitivity and the influence of porosity, are also presented. The proposed TENG shows great potential as a pressure sensor in TKR applications, offering high sensitivity, stability, and low cost.

Smart knee replacement technology seeks to provide an in vivo method of tracking long-term postoperative joint loads with the goal of identifying clinically relevant phenomena linked to postoperative dissatisfaction in real time. This study evaluated the ability of a piezoelectric compartmental force and compartmental center of pressure sensing total knee replacement to sense condylar lift-off, which is a clinically relevant phenomenon commonly attributed to postoperative dissatisfaction. A commercially available total knee replacement was modified to include six piezoelectric transducers capable of measuring compartmental forces and tibiofemoral centers of pressure on the articular surface of the tibial bearing insert. The smart knee replacement was evaluated with a six-degree-of-freedom joint motion simulator applying a varus lift-off profile. The study demonstrated that the lift-off was evident in both the sensed joint loads and the localized tibiofemoral centers of pressure obtained from the piezoelectric sensing system. The results indicated that the piezoelectric smart knee replacement could be effective for detecting this clinically problematic mechanical issue.

Abstract Aseptic loosening and joint instability remain the primary modes of failure in total knee arthroplasty. To provide real-time biomechanical load monitoring, this study presents a triboelectric nanogenerator (TENG) utilizing a carbon nanotube/foamed thermoplastic polyurethane composite dielectric layer paired with a Kapton tape between dual electrodes. By leveraging the triboelectric effect, the device functions simultaneously as an energy harvester and a self-powered load sensor. To overcome power density limitations, a self-charge pumping mechanism via a multi-stage voltage multiplier circuit (VMC) was integrated and evaluated under physiological cyclic loading (2100 N at 1 Hz). The system’s charge dynamics were further validated using an analytical energy-based model. Across configurations, the 3-stage VMC dramatically boosted performance, achieving a peak apparent power output of 17 μ W compared to 3 μ W for the unamplified TENG, with optimal storage capacitance determined at 470 pF, 1 nF, and 10 nF for 1-, 2-, and 3-stage VMCs, respectively. While the 1-stage setup yielded the highest force sensitivity (94.45 mV N − 1 ), the 3-stage configuration maximized energy capture–highlighting a key operational trade-off between sensing sensitivity and power harvesting for implantable orthopedics.

Triboelectric nanogenerators (TENGs) are attracting increasing attention as viable power sources for self-powered systems, due to advantages such as material and form-factor versatility, compatibility with low-frequency mechanical stimuli, and scalable, low-cost fabrication. Unlike conventional harvesters, TENGs exhibit two device-level characteristics that critically shape interface-circuit design: (i) a time-varying internal capacitance that induces a strongly dynamic source impedance, and (ii) a significantly high effective source impedance that yields very high open-circuit voltages at low currents. These characteristics directly affect impedance matching, rectification, voltage conversion, and maximum power point tracking (MPPT) strategies for maximum power transfer. While TENGs and piezoelectric energy harvesters (PEHs) share similar lumped electrical models, the time variance and voltage/current operating regime of TENGs fundamentally limit the portability of PEH-oriented power transfer methods. This paper provides two contributions. First, we introduce a figure-of-merit (FoM) that serves as an energy-extraction coefficient: the fraction of the ideal maximum power of the TENG device (under instantaneous impedance tracking) that appears at the rectifier input, typically the first stage of a power management unit (PMU). The FoM exposes losses arising from mismatch at the device-PMU boundary, thereby helping circuit designers localize dominant loss mechanisms (e.g., impedance mismatch, rectifier topology or suboptimal MPPT policies) and guiding device researchers to prioritize physical parameters (e.g., dielectric thickness, displacement, electrode area) with explicit awareness of interface constraints. Secondly, we conduct a thorough evaluation of the suitability of advanced PEH-derived methods, such as rectifiers (both passive and active configurations), DC-DC conversion, and MPPT, for application to TENGs. We derive theoretical upper bounds on extractable power for representative rectifier families under TENG-specific operating conditions, and we analyze technology-imposed voltage limits and their implications for architecture and control. We also survey recent TENG demonstrations together with their PMU interfaces and interpret reported performance through the proposed FoM. Overall, the analysis highlights that the unique characteristics of TENGs and technology limits for the voltages must be explicitly accounted for while developing interface circuits to realize maximum power extraction. This process can significantly benefit from coordinated device-circuit co-design via system-level metrics such as the proposed FoM.

With patient dissatisfaction rates in total knee arthroplasty currently at 20%, smart knee technology seeks to provide an in vivo method for tracking postoperative joint forces, which could aid in early diagnosis of postoperative complications and provide key data to help improve implant designs and surgical procedures. This study investigates the design, simulation, and experimental evaluation of a piezoelectric force sensing system integrated into a commercially available knee implant that preserves the overall implant geometry. Finite element simulation and parametric analysis are used to identify the transducer arrangement with the lowest error in sensing compartmental joint contact forces. A prototype is then subjected to an axial load profile simulating walking using a joint motion simulator. Total and compartmental contact forces are evaluated, and accuracy of compartmental center of pressure localization is evaluated via ±3 mm and ±6 mm anterior-posterior translations. Results show the ability to track the axial force profile and demonstrate center of pressure deviations of ∼1 mm or better at 3-A and 3-P translations and ∼3-4 mm at 6-A and 6-P translations. Error of the order of ∼15% is observed in the total force measurement at maximum load. Suspected sources of error include plastic deformation of the tibial bearing insert and high stress levels in the piezoelectric transducers that suggest partial depolarization. Overall, our piezoelectric smart knee replacement shows promise for in vivo joint sensing, and this work marks a path for further development for integration into commercial knee replacement components.

Introduction Research has suggested that rotating a medial open wedge high tibial osteotomy hinge axis internally or externally can change the posterior tibial slope and may create abnormal loading patterns through the tibia. Objectives (1) To develop and validate a finite element model that estimates posterior tibial slope following a medial opening wedge high tibial osteotomy with a prescribed hinge axis; (2) use the model to evaluate the effect hinge axis rotation has on the posterior tibial slope and medial mechanical proximal tibia angle; and (3) quantify the effect of rotating the hinge axis on the stress and strain response within the anterior and posterior regions of the hinge. Methods Five tibia finite element models were reconstructed from computed tomography scans of 5 cadaveric specimens. Three different hinge axis rotations were tested (15° external rotation, neutral, and 15° internal rotation) in each of the 5 models and the resulting posterior tibial slope, stresses, and strains were analyzed. Results A 15° externally rotated hinge significantly increased the posterior tibial slope angle compared with the preoperative alignment. The 15° externally rotated hinge experienced greater stresses and strains in the posterior region of the hinge, while the 15° internally rotated hinge experienced higher stresses and strains in the anterior region of the hinge. Conclusions The orientation of the medial open wedge high tibial osteotomy hinge can be manipulated to alter the posterior tibial slope but that changes in the stresses can also occur and this should be considered in the presurgical planning phase to reduce the risk of complications (eg, lateral cortical fractures).

This paper describes a method for maximizing the power delivered to the rectifier in energy harvesters. It is demonstrated that there is an optimal turn-on time for rectifiers to maximize power transfer from the harvester. Next, a maximum power point tracking methodology based on rectifier turn-on time (RTOT-MPPT) is developed for triboelectric energy harvesters. The primary advantage of the proposed approach is the relative independence of the optimal turn-on time on the frequency and peak voltage of the harvester output. Thus, the proposed RTOT-MPPT method reduces the complexity of power tracking and can be efficient for a wider range of harvesters. The method is implemented for a triboelectric harvester and simulated in a 180 n m industrial HV-CMOS process, demonstrating that 34% higher power is delivered to the rectifier in each cycle.

Developing self-powered, durable pressure sensors for Total Knee Replacement (TKR) enhances longevity, ensures consistent performance, and provides critical post-operative information. This study presents a triboelectric nanogenerator (TENG) integrated into an instrumented knee implant for energy harvesting and pressure sensing. Operating in vertical contact mode, it utilizes porous silicone rubber (SR) dielectric to improve electrical stability, and mechanical durability. The nanogenerator divides the tibial tray into two compartments for load imbalance detection. Tests simulating human walking showed the device withstands forces up to 2200N, generating a maximum of 18 mu W at 1Hz under harmonic load and a maximum of 7.5 mu W at 0.8Hz under gait loading with a VIVO joint simulator. The performance of the TENG was stable over 3000 cycles generating a peak-to-peak voltage of 350V. The porous structure enhances charge trapping, energy storage, and system efficiency. The increased power compared to previous work enhances energy harvesting capability and strengthens its potential for self-powered, real-time load monitoring at the knee joint.

This paper describes an analytic method to determine the optimal load capacitance of a full wave rectifier (FWR) in triboelectric energy harvesters. The amount of average power delivered from the harvester to the rectifier grows in each cycle, eventually reaching a peak value. In steady state, the average rectifier power depends on the harvester characteristics and the load capacitance of the rectifier. For a given harvester, if the load capacitance is too small, the rectifier power does not reach the maximum power in steady state. Alternatively, if the load capacitance is too large, the number of cycles to reach maximum power increases, causing additional delay. An analytic method is proposed to estimate the optimum value of this capacitance, which ensures maximum power while minimizing the transient time. The results are validated with the measurement results of a triboelectric harvester.

Medial Meniscus Posterior Root Tears (MMPRTs) are increasingly recognized, whereas research on contact mechanics associated with MMPRT during activities of daily living is limited. This study evaluated the effect of MMPRT on tibiofemoral pressure and the effectiveness of surgical repair during simulated gait. Eight fresh-frozen human cadaveric knees were tested using a joint motion simulator. Subject-specific loading profiles comprising seven key stages of the gait cycle were applied to (1) intact meniscus, (2) MMPRT, and (3) repair models. Contact pressure was measured at each stage using thin film pressure sensors beneath the menisci. The peak contact pressure (PCP), mean contact pressure (MCP), contact area (CA), and Dice similarity coefficient (DSC) that compares pressure distributions between conditions were evaluated. Compared to the intact condition, MMPRT caused significant differences in medial PCP, MCP, and CA, but only during the stance phase under the applied biomechanical model and loading conditions. Averaged across the stages within the stance phase, medial PCP and MPC were 32 % and 78 % higher, and CA was 35 % lower after MMPRT. After repair, these pressures generally remained significantly greater than their corresponding intact values. Specifically, medial PCP and MPC were on average 19 % and 40 % higher, and CA was 25 % lower than for the intact condition during the stance phase. DSCs relative to the intact state indicated that repair significantly improved pressure distributions (0.67-0.87) compared to MMPRT (0.47-0.78). The anatomic repair of MMPRT did not appear to fully restore intact contact pressure distributions in this study, suggesting that further improvement of surgical techniques may be beneficial.

Knee joint stability comprises passive (ligaments), active (muscles), and static (articular congruency) contributors. The stability of total knee replacement (TKR) implants can be assessed pre-clinically using joint motion simulators. However, contemporary testing methods with these platforms do not accurately reproduce the biomechanical contributions of passive stabilizers, active stabilizers, or both. A key component of joint stability is therefore missing from laxity tests. A recently developed muscle actuator system (MAS) pairs the quadriceps-driven motion capabilities of an Oxford knee simulator with the prescribed displacements and laxity testing methods of a VIVO robotic knee testing system, which also includes virtual ligament capabilities. Using a TKR-embedded non-cadaveric joint analogue, TKR with two different virtual ligament models were compared to TKR with no active ligaments. Laxity limits were then obtained for both developed models using the conventional style of laxity testing (the VIVO’s force/displacement control) and compared with results obtained under similar conditions with the MAS (gravity-dependent muscle control). Differences in joint control methods identified the need for muscle forces providing active joint stability, while differences in the effects of the virtual ligament models identified the importance of physiological representations of collateral ligaments during testing.

Although total knee replacements have an insignificant impact on patients’ mobility and quality of life, real-time performance monitoring remains a challenge. Monitoring the load over time can improve surgery outcomes and early detection of mechanical imbalances. Triboelectric nanogenerators (TENGs) present a promising approach as a self-powered sensor for load monitoring in TKR. A TENG was fabricated with dielectric layers consisting of Kapton tape and 3D-printed thermoplastic polyurethane (TPU) matrix incorporating CNT and BTO fillers, separated by an air gap and sandwiched between two copper electrodes. The sensor performance was optimized by varying the concentrations of BTO and CNT to study their effect on the energy-harvesting behavior. The test results demonstrate that the BTO/TPU composite that has 15% BTO achieved the maximum power output of 11.15 μW, corresponding to a power density of 7 mW/m2, under a cyclic compressive load of 2100 N at a load resistance of 1200 MΩ, which was the highest power output among all the tested samples. Under a gait load profile, the same TENG sensor generated a power density of 0.8 mW/m2 at 900 MΩ. By contrast, all tested CNT/TPU-based TENG produced lower output, where the maximum generated apparent power output was around 8 μW corresponding to a power density of 4.8 mW/m2, confirming that using BTO fillers had a more significant impact on TENG performance compared with CNT fillers. Based on our earlier work, this power is sufficient to operate the ADC circuit. Furthermore, we investigated the durability and sensitivity of the 15% BTO/TPU samples, where it was tested under a compressive force of 1000 N for 15,000 cycles, confirming the potential of long-term use inside the TKR. The sensitivity analysis showed values of 37.4 mV/N for axial forces below 800 N and 5.0 mV/N for forces above 800 N. Moreover, dielectric characterization revealed that increasing the BTO concentration improves the dielectric constant while at the same time reducing the dielectric loss, with an optimal 15% BTO concentration exhibiting the most favorable dielectric properties. SEM images for BTO/TPU showed that the 10% and 15% BTO/TPU composites showed better morphological characteristics with lower fabrication defects compared with higher filler concentrations. Our BTO/TPU-based TENG sensor showed robust performance, long-term durability, and efficient energy conversion, supporting its potential for next-generation smart total knee replacements.

Total knee replacement (TKR) is a reliable treatment for end-stage degenerative conditions of the knee. Patient-reported outcome measures (PROMs) are central to assessing TKR outcomes, but they have limitations. Activities of daily living (ADLs) in the early post-operative period complement PROMs for holistic patient assessment. This study presents a method for capturing ADL parameters from data generated by inertial measurement unit (IMU) devices embedded in TKR prosthesis. A conventional posterior stabilized TKR was modified to create chambers in the femoral and tibial components. The prosthesis was implanted into a cadaver knee and movement was simulated using a hydraulic actuated knee simulator (AMTI, VIVO, MA, USA). A powered IMU device was placed in each of the chambers. The simulator was activated for various ADLs and the generated data was collected wirelessly. The pre-processed data was fed into a novel multimodal deep learning artificial intelligence model created to recognize specific ADL (trained on 70% of the data, with 30% reserved for validation and testing). The model achieved 95.68% overall accuracy, with 100% for sitting, standing, stance, and knee bending. Walking, stair navigation, and jogging showed F1 scores of 0.98, 0.92, 0.91, and 0.89, respectively. This technology enables seamless knee activity recognition and reporting with positive implications for patient-specific rehabilitation protocols.

Background:Medial opening-wedge high tibial osteotomy (MOWHTO) is used to correct varus alignment; however, the optimal knee alignment during MOWHTO for medial meniscus posterior root tears (MMPRTs) remains unclear. Purpose:To determine the optimal biomechanical knee alignment for MMPRT treatment during MOWHTO. Study Design:Controlled laboratory study. Methods:This study used 10 fresh-frozen cadaveric legs from human donors (mean age, 61.3 years [range, 33-75 years]). A joint motion simulator assessed the weightbearing line (WBL) from 30% to 70% (0%: medial border; 100%: lateral border), simulating MOWHTO. Tibiofemoral peak contact pressure (PCP) and mean contact pressure (MCP) were measured using a pressure sensor under a 700-N load. MMPRTs were created via a femoral posterior approach and repaired with suture anchors. Measurements were taken in the intact, MMPRT, and repair conditions at alignments of 30% to 70% WBL, with neutral alignment defined as 50% WBL. Statistical analysis was performed using one-way analysis of variance with the Tukey post hoc test. Results:In the medial compartment, PCP was increased by 43% in the MMPRT condition compared with the intact condition at neutral alignment (P = .012). MCP was also significantly increased by 57% in the MMPRT condition compared with the intact condition (P = .006). At varus alignment, PCP and MCP increased in all conditions, with the largest statistically significant differences observed at 30% WBL (P = .002 and P < .001, respectively). PCP and MCP at neutral alignment in the intact condition were comparable with those at 60% to 65% WBL in the MMPRT condition and at 50% to 55% WBL in the repair condition. In the lateral compartment, PCP and MCP increased at valgus alignment, with no significant differences among conditions. Conclusion:MCP at neutral alignment in the intact condition was similar to that at 60% to 65% WBL in the MMPRT condition and at 50% to 55% WBL in the repair condition, indicating optimal biomechanical alignment targets for MOWHTO in patients with MMPRTs. 50-55% WBL corresponds to slight valgus alignment. Neutral alignment was not considered ideal in this context. Clinical Relevance:These findings provide biomechanical evidence to guide optimal knee alignment during MOWHTO for MMPRTs, potentially improving patient outcomes.

BACKGROUND:The French Paradox (FP) technique, characterised by line-to-line cementing, has recently been applied to polished tapered stems with favourable results despite the thin cement mantle created. However, it contravenes the minimum 2-mm cement mantle described in the standard (STD) cementing technique. AIM:This experimental study aimed to compare the FP and STD cementing techniques by comparing the cement mantle thickness, micromotion, and alignment of a polished tapered stem under clinically relevant loads. METHODS:Stems were implanted into 4 pairs of human cadaveric hips. Femurs within each pair were randomly allocated to receive either the STD or FP technique. 5 linear variable displacement transducers (LVDTs) were used to measure the real-time motion of the stem relative to the femur. The specimens were mounted onto a joint motion simulator and cyclically loaded with axial compression (0-1,600 N) and internal torsion (0-15 Nm). RESULTS:No significant differences were found in permanent migration, initial and long-term inducible motion, or stem alignment between techniques. The FP technique resulted in a thinner cement mantle (∆1.0 ± 0.2 mm). The mean permanent migration was below 20 μm, and inducible motions were below 100 μm for both techniques. CONCLUSIONS:Both FP and STD cementing techniques resulted in well-fixed stems with low migration and inducible motion.

This study investigates the energy harvesting and sensing capabilities of piezoelectric nanogenerators (PENG) and triboelectric nanogenerators (TENG) for long-term load monitoring in total knee replacement (TKR). Multi-layered polyvinylidene fluoride (PVDF) films and cuboid-patterned silicone rubber embedded with dopamine-coated BaTiO3 particles (SR/BT@PDA) TENG are compared as energy harvesting-based load sensors. Unlike prior studies relying on simplified harmonic loading, this work utilizes physiologically relevant gait cycles covering realistic force ranges to precisely evaluate electrical output, sensitivity, and activity recognition capabilities. Results indicate forward-polarized TENG samples and upward-polarized PVDF layers generate significantly higher outputs, indicating the importance of dipole alignment for enhanced sensor efficiency. The harvesters' outputs show that the SR/BT@PDA TENG achieves a maximum apparent power output of 6 μW at 1.5GΩ, while the PVDF reaches 2.7 μW at 200MΩ under normal walking conditions. The SR/BT@PDA TENG outperforms PVDF in energy harvesting, reaching 140 V in 26 gait cycles for a 10nF capacitor and powering 60 LEDs, while PVDF charges the same capacitor to 33 V in nearly 19 gait cycles, powering 14 LEDs. The TENG's micro-cuboid surface patterning and synergistic effects of embedded piezoelectric material (BaTiO3) enhance its output power density, whereas the multi-layered PVDF demonstrates reliable performance under diverse load conditions. Both sensors effectively detect diverse activities, including walking, jogging, and stair climbing. Overall, PVDF provides precise load monitoring by tracking dynamic force profiles, while TENG outperforms in energy harvesting. This study evaluates the potential of integrating TENG and PENG into TKR as energy-harvesting solutions for joint load monitoring without relying on external power sources.

A power optimization strategy is described for triboelectric energy harvesting systems by optimizing the load capacitor size within a full wave rectifier (FWR). In AC harvesters such as triboelectric nanogenerators (TENGs) with an FWR, the average power delivered to the rectifier increases in each cycle, ultimately reaching a steady state determined by system parameters. Through cycle-level analysis of input voltage, current, and rectifier turn-on time during mechanical motion, an optimal load capacitance is identified that maximizes power delivery while minimizing transient time to reach this maximum power. This approach achieves peak power delivery via capacitor sizing alone, eliminating the need for additional circuitry. Experimental results using a vertical contact-separation triboelectric nanogenerator with internal capacitance varying from 24pF to 96pF demonstrate that the optimal rectifier capacitance of 390pF achieves maximum power delivery (900nW at 1.7Hz and 2.7μW at 5Hz) within the second cycle, while suboptimal capacitances either fail to reach peak power or delay it to the seventh cycle or later. Sensitivity analysis reveals that the method exhibits high robustness, with capacitances within ±30% of the optimal value can still maintain ≥ 90% of peak power, providing flexibility when implementing or selecting the capacitor size.

Total knee replacement (TKR) failure, low patient satisfaction and high revision surgery rates may stem from insufficient preclinical testing. Conventional joint motion simulators for preclinical testing of TKR implants manipulate a knee joint in force, displacement, or simulated muscle control. However, a rig capable of using all three control modes has yet to be described in literature. This study aimed to validate a novel platform, the muscle actuator system (MAS), that can generate gravity-dependent, quadriceps-controlled squatting motions representative of an Oxford rig knee simulator and is mounted onto a force/displacement-control-capable joint motion simulator. Synthetic knee joint phantoms were created that comprised revision TKR implants and key extensor and flexor mechanism analogues, but no ligaments. The combined system implemented a constant force vector acting from simulated hip-to-ankle coordinates, effectively replicating gravity as observed in an Oxford rig. Quadriceps forces and patellofemoral joint kinematics were measured to assess the performance of the MAS and these tests showed high levels of repeatability and reproducibility. Forces and kinematics measured at a nominal patellar tendon length, and with patella alta and baja, were compared against those measured under the same conditions using a conventional Oxford rig, the Pennsylvania State Knee Simulator (PSKS). There was disagreement in absolute kinematics and muscle forces, but similar trends resulting from changing prosthesis design or patellar tendon length.

This study presents the development and characterization of a novel triboelectric nanogenerator (TENG) designed as a self-powered sensor for load monitoring in total knee replacement (TKR) implants. The triboelectric layers comprise a 3D-printed thermoplastic polyurethane (TPU) matrix with carbon nanotube (CNT) nanoparticles and kapton tape, sandwiched between two copper electrodes. To optimize sensor performance, the proposed CNT/TPU TENG sensor is fabricated with varying CNT concentrations and thicknesses, enabling a comprehensive analysis of how material composition and structural parameters influence energy harvesting efficiency. The 1% CNT/TPU composite demonstrates the highest power output among the tested samples. The solid CNT/TPU-based TENG generated the apparent output power of 4.1 µW under a cyclic compressive load of 2100 N, measured across a 1.6 GΩ load resistance and over a nominal contact area of 15.9 cm2, while the foam CNT/TPU film achieved a higher apparent output power of 6.9 µW measured across a 0.9 GΩ load resistance with the same nominal area. The generated power is sufficient to operate a power management and ADC circuit based on our earlier work. The sensors exhibit a stable open-circuit voltage of 320 V for the foam layer and 275 V for the solid one. Sensitivities are 80.50 mV N-1 ( ⩽ 1600  N) and 24.60 mV N-1 (> 1600 N) for foam CNT/TPU film, demonstrating the integrated sensor capability for wide-range force sensing on TKR implants. The foam CNT/TPU-based TENG maintained stable performance over 16 000 load cycles, confirming its potential for long-term use inside the TKR. Additionally, the dielectric constant of the CNT/TPU composite was found to increase with increasing CNT concentration. The proposed CNT/TPU TENG sensor offers a broad working range and robust energy-harvesting efficiency, making it appropriate for self-powered load sensing in biomedical applications.

Knee osteoarthritis (OA) is associated with higher-than-normal knee joint contact forces (KJCFs) during walking which cannot be easily measured. KJCFs can be estimated using neuromusculoskeletal (NMSK) modelling in electromyogram (EMG)-driven and -assisted control modes. Previous research has not examined which control mode is most appropriate for estimating KJCFs in patients with knee OA. This study aimed to evaluate a NMSK modelling framework using both control modes in patients with medial-dominant knee OA. First, EMG-assisted mode was hypothesized to better track ID-computed joint moments. Second, KJCFs estimated using the two control modes were hypothesized to differ. Gait data were measured from 27 patients with medial-dominant tibiofemoral knee OA. An OpenSim model was scaled to patient-specific anthropometrics. Inverse kinematics, inverse dynamics, and muscle analysis were performed. Resulting joint angles, moments, musculotendon kinematics, and muscle activations were input into the Calibrated Electromyography Informed Neuromusculoskeletal Modelling Toolbox. Muscle forces and KJCFs were estimated using EMG-driven and -assisted control modes. EMG-assisted mode better tracked knee flexion moments (RMSE = 2.7 ± 2.1Nm, R2 = 0.9 ± 0.1) and estimated a higher, albeit non-significant, second peak medial compartment KJCF (2.3 ± 1.1BW) compared to EMG-driven mode (RMSE = 12.6 ± 3.9Nm, R2 = 0.6 ± 0.2, KJCF = 2.1 ± 0.9BW). EMG-assisted control mode may therefore be more appropriate for evaluating KJCFs in patients with knee OA.