Edward Nyman

Real-time feedback during drop landing training improves subsequent frontal and sagittal plane knee kinematics

BACKGROUND Although neuromuscular training featuring visual feedback may benefit modification of anterior cruciate ligament injury-risk linked knee kinematics, wide-spread clinical intervention has been limited to date. This study evaluated the effects of a Microsoft Kinect-based feedback system for modification of drop vertical jump knee kinematics traditionally consistent with predisposition to non-contact anterior cruciate ligament injury in female athletes. We hypothesized that a four-week feedback training protocol would increase peak knee flexion angle and frontal plane valgus-correlated knee separation distance during drop jump landing performance. METHODS Twenty-four female athletes were randomly divided equally into control or Kinect-based feedback groups. Subjects were pre-screened for peak knee flexion angle and minimum knee separation distance during drop landing and later performed twenty 31cm drop landings three days per week for four weeks. The feedback group received Kinect-based visual feedback, while controls did not. Kinematics were re-assessed immediately following the end of the training period. FINDINGS The feedback group increased peak knee flexion and experienced a greater improvement in peak knee flexion. The feedback group improved normalized knee separation distance with greater improvement in post-training peak knee separation distance as compared with controls. INTERPRETATION Kinect-based feedback training significantly improved drop vertical jump knee kinematics associated with non-contact anterior cruciate ligament injury. The Kinect-based feedback approach demonstrates promise for mitigating non-contact anterior cruciate ligament injury predisposing knee biomechanics in female athletes within the clinical environment.

A novel 3D approach for determination of frontal and coronal plane tibial slopes from MR imaging.

BACKGROUND The proximal tibia is geometrically complex, asymmetrical, and variable, is heavily implicated in arthrokinematics of the knee joint, and thus a contributor to knee pathologies such as non-contact anterior cruciate ligament injury. Medial, lateral, and coronal tibial slopes are anatomic parameters that may increase predisposition to knee injuries, but the extent to which each contributes has yet to be fully realized. Previously, two-dimensional methods have quantified tibial slopes, but more reliable 3D methods may prove advantageous. AIMS (1) to explore the reliability of two-dimensional methods, (2) to introduce a novel three-dimensional measurement approach, and (3) to compare data derived from traditional and novel methods. METHODS Medial, lateral, and coronal tibial slope geometry from both knees (left and right) of one subject were obtained via magnetic resonance images and measured by four trained observers from two-dimensional views. The process was repeated via three-dimensional approaches and data evaluated for intra- and inter-rater reliability. RESULTS The conventional method presented a weaker Intraclass Correlation Coefficient (ICC) for the measured slopes (ranging from 0.43 to 0.81) while the resultant ICC for the proposed method indicated greater reliability (ranging from 0.84 to 0.97). Statistical analysis supported the novel approach for production of more reliable and repeatable results for tibial slopes. CONCLUSIONS The novel three-dimensional method for calculating tibial plateau slope may be more reliable than previously established methods and may be applicable in assessment of susceptibility to osteoarthritis, as part of anterior cruciate ligament injury risk assessment, and in total knee implant design.

Prediction of contact mechanics in metal-on-metal Total Hip Replacement for parametrically comprehensive designs and loads

Manufacturers and investigators of Total Hip Replacement (THR) bearings require tools to predict the contact mechanics resulting from diverse design and loading parameters. This study provides contact mechanics solutions for metal-on-metal (MoM) bearings that encompass the current design space and could aid pre-clinical design optimization and evaluation. Stochastic finite element (FE) simulation was used to calculate the head-on-cup contact mechanics for five thousand combinations of design and loading parameters. FE results were used to train a Random Forest (RF) surrogate model to rapidly predict the contact patch dimensions, contact area, pressures and plastic deformations for arbitrary designs and loading. In addition to widely observed polar and edge contact, FE results included ring-polar, asymmetric-polar, and transitional categories which have previously received limited attention. Combinations of design and load parameters associated with each contact category were identified. Polar contact pressures were predicted in the range of 0-200 MPa with no permanent deformation. Edge loading (with subluxation) was associated with pressures greater than 500 MPa and induced permanent deformation in 83% of cases. Transitional-edge contact (with little subluxation) was associated with intermediate pressures and permanent deformation in most cases, indicating that, even with ideal anatomical alignment, bearings may face extreme wear challenges. Surrogate models were able to accurately predict contact mechanics 18,000 times faster than FE analyses. The developed surrogate models enable rapid prediction of MoM bearing contact mechanics across the most comprehensive range of loading and designs to date, and may be useful to those performing bearing design optimization or evaluation.

Automated Measurement of Patient-Specific Tibial Slopes from MRI

Background: Multi-planar proximal tibial slopes may be associated with increased likelihood of osteoarthritis and anterior cruciate ligament injury, due in part to their role in checking the anterior-posterior stability of the knee. Established methods suffer repeatability limitations and lack computational efficiency for intuitive clinical adoption. The aims of this study were to develop a novel automated approach and to compare the repeatability and computational efficiency of the approach against previously established methods. Methods: Tibial slope geometries were obtained via MRI and measured using an automated Matlab-based approach. Data were compared for repeatability and evaluated for computational efficiency. Results: Mean lateral tibial slope (LTS) for females (7.2°) was greater than for males (1.66°). Mean LTS in the lateral concavity zone was greater for females (7.8° for females, 4.2° for males). Mean medial tibial slope (MTS) for females was greater (9.3° vs. 4.6°). Along the medial concavity zone, female subjects demonstrated greater MTS. Conclusion: The automated method was more repeatable and computationally efficient than previously identified methods and may aid in the clinical assessment of knee injury risk, inform surgical planning, and implant design efforts.

Computational Modeling and Finite Element Analysis.

Computational modeling with finite element analysis (FEA) is an integral component of medical device design and development. Researchers assess dimensions and stability of the experimental device; test load sharing, stresses, and strains; and analyze failures and modifications. The most important step in FEA is validation of the model. Testing should include decompression and stabilization procedures simulated in the finite element model (FEM). Prerequisites of quality FEA include a solid understanding of morphology and material properties of the model, a firm grasp of the effects of loads on body structures, and the work of a skilled bioengineer who can translate the ideas of surgeons into an appropriate FEM. With todays modern techniques-computed tomography/magnetic resonance imaging, etc.-the bioengineer moves from scan to FEM in just weeks.