The Effect of Metronome Pacing on Gait in Healthy Subjects

The complex process of gait is rendered partially automatic by central pattern generators (CPGs). To further our understanding of their role in gait control in healthy subjects, we applied a paradigm of anti-phase, or syncopated, movement to gait. To provide a context for our results, we reviewed the literature on in-phase, or synchronized, gait. The review results are as follows. Auditory cueing increased step/stride rate for older subjects, but not younger. Stride rate variability decreased for younger subjects, perhaps because the metronome’s cue acted as a temporal ‘anchor point’ for each step. Step width increased in half of the treadmill studies, but none of the overground ones, suggesting a cumulative effect of the attentional demands of synchronizing gait while on a treadmill. Time series analysis revealed that the α exponent was the most sensitive parameter reported, decreasing toward anti-persistence in almost all cued-gait studies. This project compares in-phase (IN) and anti-phase gait (ANTI) in young and old healthy subjects. We expected gait to be less disrupted during ANTI trials at preferred speed, when the facilitating effect of CPGs would be strongest. The measures step time variability, jerk index, and harmonic ratio quantified gait perturbation: none indicated that ANTI was easiest at preferred walking speed. Surprisingly, the gait of older subjects was no more perturbed than that of younger subjects. When they successfully matched the pace of the beat, they unwittingly synchronized to it. The temporal relationship of their steps to the beat was the same in the IN and ANTI conditions. Younger subjects, visibly struggling during ANTI trials, were able to walk in syncopation. This result suggests that cognitive resources available only to the younger group are required to resist synchronizing to the beat.

Methods for objective and interpretative evaluation of function and motor control: gait in perturbed condition and in the aquatic therapy

Gait analysis allows to characterize motor function, highlighting deviations from normal motor behavior related to an underlying pathology. The widespread use of wearable inertial sensors has opened the way to the evaluation of ecological gait, and a variety of methodological approaches and algorithms have been proposed for the characterization of gait from inertial measures (e.g. for temporal parameters, motor stability and variability, specific pathological alterations). However, no comparative analysis of their performance (i.e. accuracy, repeatability) was available yet, in particular, analysing how this performance is affected by extrinsic (i.e. sensor location, computational approach, analysed variable, testing environmental constraints) and intrinsic (i.e. functional alterations resulting from pathology) factors. The aim of the present project was to comparatively analyze the influence of intrinsic and extrinsic factors on the performance of the numerous algorithms proposed in the literature for the quantification of specific characteristics (i.e. timing, variability/stability) and alterations (i.e. freezing) of gait. Considering extrinsic factors, the influence of sensor location, analyzed variable, and computational approach on the performance of a selection of gait segmentation algorithms from a literature review was analysed in different environmental conditions (e.g. solid ground, sand, in water). Moreover, the influence of altered environmental conditions (i.e. in water) was analyzed as referred to the minimum number of stride necessary to obtain reliable estimates of gait variability and stability metrics, integrating what already available in the literature for over ground gait in healthy subjects. Considering intrinsic factors, the influence of specific pathological conditions (i.e. Parkinson’s Disease) was analyzed as affecting the performance of segmentation algorithms, with and without freezing. Finally, the analysis of the performance of algorithms for the detection of gait freezing showed how results depend on the domain of implementation and IMU position.