Predicting timing of foot strike during running,independent of striking technique,using principal component analysis of joint angles

As 3-dimensional (3D) motion-capture for clinical gait analysis continues to evolve, new methods must be developed to improve the detection of gait cycle events based on kinematic data. Recently, the application of principal component analysis (PCA) to gait data has shown promise in detecting important biomechanical features. Therefore, the purpose of this study was to define a new foot strike detection method for a continuum of striking techniques, by applying PCA to joint angle waveforms. In accordance with Newtonian mechanics, it was hypothesized that transient features in the sagittal-plane accelerations of the lower extremity would be linked with the impulsive application of force to the foot at foot strike. Kinematic and kinetic data from treadmill running were selected for 154 subjects, from a database of gait biomechanics. Ankle, knee and hip sagittal plane angular acceleration kinematic curves were chained together to form a row input to a PCA matrix. A linear polynomial was calculated based on PCA scores, and a 10-fold cross-validation was performed to evaluate prediction accuracy against gold-standard foot strike as determined by a 10 N rise in the vertical ground reaction force. Results show 89–94% of all predicted foot strikes were within 4 frames (20 ms) of the gold standard with the largest error being 28 ms. It is concluded that this new foot strike detection is an improvement on existing methods and can be applied regardless of whether the runner exhibits a rearfoot, midfoot, or forefoot strike pattern.     

Is primate-like quadrupedalism necessary for fine-branch locomotion? A test using sugar gliders (Petaurus breviceps)

Locomotor features shared by arboreal marsupials and primates are frequently cited as a functional complex that evolved in the context of a “fine branch niche.” Adaptation to a fine branch niche cannot be understood without considering that small and large arboreal mammals may differ in their biomechanical response to a given branch size. We tested the effects of substrate diameter and orientation on quadrupedal kinematics in a small arboreal marsupial (the sugar glider, Petaurus breviceps). P. breviceps individuals were filmed moving across a flat horizontal surface and on horizontal, inclining and declining poles of diameter 2.5, 1.0, and 0.5 cm. Gait frequencies, limb phases, speeds and duty factors were compared across substrate conditions. P. breviceps had a clear preference for lateral sequence/diagonal couplets gaits, regardless of substrate type, diameter or orientation. Limb phase was significantly influenced by substrate type (higher limb phases on poles vs. the flat surface) and by orientation (higher limb phases on inclined vs. horizontal poles), but was not influenced by pole diameter. Speed was lowest on declines, and duty factors (at a given speed) were highest on the flat board, smallest pole, and on declines. P. breviceps exhibited some parallels, but also some departures from the characteristic patterns of other arboreal marsupials and primates. Notably, limb phase values, on average, remained lower in P. breviceps than those recorded for primates or other arboreal marsupials. We suggest that arboreal mammals of different body sizes may use dissimilar, but apparently equally successful strategies for navigating a “fine branch niche.”     

Mobile platform for motion capture of locomotion over long distances

Motion capture is usually performed on only a few steps of over-ground locomotion, limited by the finite sensing volume of most capture systems. This makes it difficult to evaluate walking over longer distances, or in a natural environment outside the laboratory. Here we show that motion capture may be performed relative to a mobile platform, such as a wheeled cart that is moved with the walking subject. To determine the person’s absolute displacement in space, the cart’s own motion must be localized. We present three localization methods and evaluate their performance. The first detects cart motion solely from the relative motion of the subject’s feet during walking. The others use sensed motion of the cart’s wheels to perform odometry, with and without an additional gyroscope to enhance sensitivity to turning about the vertical axis. We show that such methods are practical to implement, and with present-day sensors can yield accuracy of better than 1% over arbitrary distances.