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Pedometers are basically step counters usually used to estimate the distance walked by a pedestrian. Although their precision to compute the number of steps is quite accurate (about 1%), their feasibility to estimate the walked distance is very poor, as they do not consider the intrinsic variability of human gait. Reported results show values of 10% of precision in optimal conditions, increasing to 50% when conditions differ. Electronic accelerometer-based pedometers base their functioning on a basic processing of the vertical acceleration of the waist. Recently, different approaches have been proposed to relate such signals to the step length. This can lead to an improvement of the performance of this kind of device for estimating the walked distance. In this article, we analyze four gait models applied to the vertical accelerations of the body’s center of gravity, three biomechanical and one empirical. We compare their precision and accuracy. Results support the superior performance of three of them over an ideal pedometer. We also analyze their feasibility to be implemented in pedometer-like devices.

Efforts to compare different surface marker configurations in 3-dimensional motion analysis are warranted as more complex and custom marker sets become more common. At the knee, different markers can been used to represent the proximal shank. Often, two anatomical markers are placed over the femoral condyles, with their midpoint defining both the distal thigh and proximal shank segment ends. However, two additional markers placed over the tibial plateaus have been used to define the proximal shank end. For this experiment, simultaneous data for both proximal shank configurations were independently collected at two separate laboratories by different investigators, with one laboratory capturing a walking population and the other a running population. Common discrete knee joint variables were then compared between marker sets in each population. Using the augmented marker set, peak knee flexion after weight acceptance was less (1.2−1.7°, P < .02) and peak knee adduction was greater (0.7−1.4°, P < .001) in both data sets. Similarly, the calculated peak knee flexion moment was less by 15–20% and internal rotation moment was greater by 11–18% (P < .001). These results suggest that the calculation of knee joint mechanics are influenced by the proximal shank’s segment endpoint definition, independent of dynamic task, investigator, laboratory environment, and population in this study.

Results from instrumented gait analysis vary between test situations. Subject characteristics and the biomechanical model can influence the total amount of variability. The purpose of this study was to quantify reliability of gait data in general, and with respect to the applied model, and investigated population group. Reliability was compared between a functional and a predictive gait model in subjects with knee osteoarthritis and healthy controls. Day-to-day consistency for sagittal plane variables was comparable between models and population groups. Transversal plane variables relative to joint excursion showed larger inconsistency for repeated measures, even for a more sophisticated biomechanical approach. In conclusion, the presented reliability data of sagittal plane kinematics should be used for a reasonable interpretation of results derived in clinical gait analysis. Variables of the transversal plane should not be used as long as sources of error are not sufficiently minimized.

This study aimed to determine the effect of tibia marker placement on walking kinematics in children with pathological gait. Three-dimensional lower extremity gait data were collected using both a traditional tibia wand (protruding laterally from the distal shank) and a tibia crest marker on 25 children with pathological gait. Kinematic variables during walking and quiet standing were calculated using each marker and the “Plug-in Gait” implementation of the conventional gait model. For walking, average differences in kinematics between tibia markers ranged from 0.1° to 1.9° at the knee and ankle, except in the transverse plane where differences were 6.0° to 7.2°. No significant differences were found during quiet standing, indicating that differences in kinematics derive primarily from dynamic sources, which likely affect the tibia wand more than the tibia crest marker. These results suggest that the tibia crest marker can be used in place of the traditional tibia wand in clinical gait analysis.