Motion analyses of lower body mechanics offer new schemas to address injury prevention strategies among baseball pitchers, where the influence of stride length remains unknown. This study examined the temporal effect of stride length at constituent pitching events and phases. Nineteen competitive pitchers (15 collegiate, 4 high school) were randomly assigned to pitch two simulated, 80-pitch games at ±25% of their desired stride length. An integrated, three-dimensional motion capture system recorded each pitch. Paired t-tests were used to determine whether differences between stride conditions at respective events and within phases were significantly different. The results demonstrate the shorter strides mediated earlier onset of stride foot contact, reduced time in single support whereas double support intervals increased (p<.001). The opposite was observed with the longer strides. However, the acceleration phase, which comprises the highest throwing arm kinematics and kinetics, remained unchanged. The interaction between stride length, stride foot contact onsets, and time in single support is inferentially evidenced. The equivalent acceleration phases suggest stride length alone influenced time in single and double support by altering the onset of stride foot contact, which perhaps affects the mechanics in preparing the throwing arm for maximal external shoulder rotation.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.humov.2015.03.005DOI Listing

Publication Analysis

Top Keywords

stride length
16
events phases
8
stride
6
inferential investigation
4
investigation stride
4
length
4
length influences
4
influences temporal
4
temporal parameters
4
parameters baseball
4

Similar Publications

Clinical Manifestations.

Alzheimers Dement

December 2024

Hallym University, Chuncheon, Gangwon-do, Korea, Republic of (South).

Background: In patients with mild cognitive impairment (MCI), the presence or absence of memory deficits is associated with divergent clinical presentations, etiologies, and prognostic outcomes. These differences may also manifest in additional neurologic signs beyond cognitive impairments and are often reflected in distinct magnetic resonance imaging (MRI) profiles. Gait is one of the clinical characteristics that reflects brain function along with cognitive function.

View Article and Find Full Text PDF

A dual-stage model for classifying Parkinson's disease severity, through a detailed analysis of Gait signals using force sensors and machine learning approaches, is proposed in this study. Parkinson's disease is the primary neurodegenerative disorder that results in a gradual reduction in motor function. Early detection and monitoring of the disease progression is highly challenging due to the gradual progression of symptoms and the inadequacy of conventional methods in identifying subtle changes in mobility.

View Article and Find Full Text PDF

Early detection of Parkinson's disease (PD) and accurate assessment of disease progression are critical for optimizing treatment and rehabilitation. However, there is no consensus on how to effectively detect early-stage PD and classify motor symptom severity using gait analysis. This study evaluated the accuracy of machine learning models in classifying early and moderate-stages of PD based on spatiotemporal gait features at different walking speeds.

View Article and Find Full Text PDF

Introduction: Walking is essential for daily life but poses a significant challenge for many individuals with neurological conditions like cerebral palsy (CP), which is the leading cause of childhood walking disability. Although lower-limb exoskeletons show promise in improving walking ability in laboratory and controlled overground settings, it remains unknown whether these benefits translate to real-world environments, where they could have the greatest impact.

Methods: This feasibility study evaluated whether an untethered ankle exoskeleton with an adaptable controller can improve spatiotemporal outcomes in eight individuals with CP after low-frequency exoskeleton-assisted gait training on real-world terrain.

View Article and Find Full Text PDF

During pregnancy, women undergo significant physiological, hormonal, and biomechanical changes that influence their gait. The forward shift of the center of mass and increased joint loads often result in a "waddling gait," elevating the risk of falls. While gait changes during pregnancy have been documented, findings across studies remain inconsistent, particularly regarding variations at different pregnancy stages.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!