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The purpose of this study was to introduce a simple gait training method using real-time gait modification to reduce the peak knee adduction moment during walking by producing a subtle weight bearing shift to the medial side of the foot. The hypothesis of this study was that this weight shift could be achieved via either verbal instruction or an active feedback system, and that the weight shift would result in a reduction in the first peak knee adduction moment compared with the control tests. Nine individuals were tested during walking using two intervention methods: verbal instruction and an active feedback system placed on the right shoe. The first peak of the knee adduction moment for each condition was assessed using a motion capture system and force plate. The active feedback system significantly reduced (14.2%) the peak knee adduction moment relative to the control. This study demonstrated that a subtle weight bearing shift to the medial side of the foot produced with an active feedback system during walking reduced the first peak of the knee adduction moment and suggests the potential application of this method to slow the rate of progression of medial compartment knee osteoarthritis. [DOI: 10.1115/1.4001584] Keywords: gait modification, osteoarthritis, knee adduction moment, active feedback

Accurate subject-specific body segment parameters (BSPs) are necessary to perform kinetic analyses of human movements with large accelerations, or no external contact forces or moments. A new automated topographical image-based method of estimating segment mass, center of mass (CM) position, and moments of inertia is presented. Body geometry and volume were measured using a laser scanner, then an automated pose and shape registration algorithm segmented the scanned body surface, and identified joint center (JC) positions. Assuming the constant segment densities of Dempster, thigh and shank masses, CM locations, and moments of inertia were estimated for four male subjects with body mass indexes (BMIs) of 19.7-38.2. The subject-specific BSP were compared with those determined using Dempster and Clauser regression equations. The influence of BSP and BMI differences on knee and hip net forces and moments during a running swing phase were quantified for the subjects with the smallest and largest BMIs. Subject-specific BSP for 15 body segments were quickly calculated using the image-based method, and total subject masses were overestimated by 1.7-2.9%. When compared with the Dempster and Clauser methods, image-based and regression estimated thigh BSP varied more than the shank parameters. Thigh masses and hip JC to thigh CM distances were consistently larger, and each transverse moment of inertia was smaller using the image-based method. Because the shank had larger linear and angular accelerations than the thigh during the running swing phase, shank BSP differences had a larger effect on calculated intersegmental forces and moments at the knee joint than thigh BSP differences did at the hip. It was the net knee kinetic differences caused by the shank BSP differences that were the largest contributors to the hip variations. Finally, BSP differences produced larger kinetic differences for the subject with larger segment masses, suggesting that parameter accuracy is more important for studies focused on overweight populations. The new image-based BSP estimation method described in this paper addressed the limitations of currently used geometric and regression methods by using exact limb geometry to determine subject-specific parameters. BSP differences have the largest effect on kinetic analyses of motions with large limb accelerations, for joints farther along the kinematic chain from the known forces and moments, and for subjects with larger limb masses or BMIs. [DOI: 10.1115/1.4000155] Keywords: body segment parameters, inertia, joint forces, joint moments, markerless motion capture

Cartilage morphology change is an important biomarker for the progression of osteoarthritis. The purpose of this study was to assess the accuracy of in vivo cartilage thickness measurements from MR image-based 3D cartilage models using a laser scanning method and to test if the accuracy changes with cartilage thickness. Three-dimensional tibial cartilage models were created from MR images (in-plane resolution of 0.55 mm and thickness of 1.5 mm) of osteoarthritic knees often patients prior to total knee replacement surgery using a semi-automated B-spline segmentation algorithm. Following surgery, the resected tibial plateaus were laser scanned and made into 3D models. The MR image and laser-scan based models were registered to each other using a shape matching technique. The thicknesses were compared point wise for the overall surface. The linear mixed-effects model was used for statistical test. On average, taking account of individual variations, the thickness measurements in MRI were overestimated in thinner ( Keywords: cartilage, thickness, accuracy, osteoarthritis, MRI

Dear Editor: It was with great interest that we read the article by Chappell et al, 'Effect of Fatigue on Knee Kinetics and Kinematics in Stop-Jump Tasks' (July 2005, pages [...]