Timothy L. Foutz

Diagnosis of lameness in dogs by use of artificial neural networks and ground reaction forces obtained during gait analysis

OBJECTIVE To evaluate the accuracy of artificial neural networks (ANNs) for use in predicting subjective diagnostic scores of lameness with variables determined from ground reaction force (GRF) data. ANIMALS 21 adult mixed-breed dogs. PROCEDURES The left cranial cruciate ligament of each dog was transected to induce osteoarthritis of the stifle joint as part of another study. Lameness scores were assigned and GRF data were collected 2 times before and 5 times after ligament transection. Inputs and the output for each ANN were GRF variables and a lameness score, respectively. The ANNs were developed by use of data from 14 dogs and evaluated by use of data for the remaining 7 dogs (ie, dogs not used in model development). RESULTS ANN models developed with 2 preferred input variables had an overall accuracy ranging from 96% to 99% for 2 data configurations (data configuration 1 contained patterns or observations for 7 dogs, whereas data configuration 2 contained patterns or observations for 7 other dogs). When additional variables were added to the models, the highest overall accuracy ranged from 97% to 100%. CONCLUSIONS AND CLINICAL RELEVANCE ANNs provided a method for processing GRF data of dogs to accurately predict subjective diagnostic scores of lameness. Processing of GRF data via ANNs could result in a more precise evaluation of surgical and pharmacological intervention by detecting subtle lameness that could have been missed by visual analysis of GRF curves.

Effects of tibial plateau angle and spacer thickness applied during in vitro canine total knee replacement on three-dimensional kinematics and collateral ligament strain

OBJECTIVE To quantify the 3-D kinematics and collateral ligament strain of stifle joints in cadaveric canine limbs before and after cranial cruciate ligament transection followed by total knee replacement (TKR) involving various tibial plateau angles and spacer thicknesses. SAMPLE 6 hemi-pelvises collected from clinically normal nonchondrodystrophic dogs (weight range, 25 to 35 kg). PROCEDURES Hemi-pelvises were mounted on a modified Oxford knee rig that allowed 6 degrees of freedom of the stifle joint but prevented mechanical movement of the hip and tarsal joints. Kinematics and collateral ligament strain were measured continuously while stifle joints were flexed. Data were again collected after cranial cruciate ligament transection and TKR with combinations of 3 plateau angles (0°, 4°, and 8°) and spacer thicknesses (5, 7, and 9 mm). RESULTS Presurgical (ie, normal) stifle joint rotations were comparable to those previously documented for live dogs. After TKR, kinematics recorded for the 8°, 5-mm implant most closely resembled those of unaltered stifle joints. Decreasing the plateau angle and increasing spacer thickness altered stifle joint adduction, internal rotation, and medial translation. Medial collateral ligament strain was minimal in unaltered stifle joints and was unaffected by TKR. Lateral collateral ligament strain decreased with steeper plateau angles but returned to a presurgical level at the flattest plateau angle. CONCLUSIONS AND CLINICAL RELEVANCE Among the constructs tested, greatest normalization of canine stifle joint kinematics in vitro was achieved with the steepest plateau angle paired with the thinnest spacer. Furthermore, results indicated that strain to the collateral ligaments was not negatively affected by TKR.

Using argumentation as a learning strategy to improve student performance in engineering Statics

ABSTRACT Research suggests that a significant reason that a large number of students earn low grades in the fundamental engineering science course Statics is that they may be entering the course with incorrect conceptual knowledge of mathematics and physics. The self-explanation learning approach called collective argumentation helps k-12 students to understand their misconceptions of mathematical principles that often appear abstract to them. This study investigated collective argumentation as an instructional approach that helps engineering students identify and correct their misconceptions of topics taught in Statics. Results suggest that argumentation improves student performance as measured by grades earned on semester exams. Survey and focus group results suggest that students did not understand the argumentation process. Therefore, the students did not like using it as a learning approach.