Effect of Restrictive Clothing on Balance and Gait using Motion Capture and Stability Analysis

Rahmatalla, Salam; Kim, H. J.; Shanahan, Meagan; Swan, Colby C.

doi:10.4271/2005-01-2688

Cited by 6 publications

(3 citation statements)

References 25 publications

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“…In another study by Egan et al [6], it was revealed that clothing properties such as weight can be another factor which have effects on balance and gait of people. Furthermore, Rahmatalla et al [14] concluded that restrictive clothing can impose constraints on the relative joint angle limits of the walking subject and therefore affect their gait pattern. In the study carried out by Phillips et al [15] for gait recognition using the silhouette-based approach, the recognition rate dropped sharply to 3% for the following combined covariate factors: time, footwear and clothing.…”

Section: The Clothing Effectsmentioning

confidence: 99%

Exploratory factor analysis of gait recognition

Bouchrika

Nixon

2008

2008 8th IEEE International Conference on Automatic Face &Amp; Gesture Recognition

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Many studies have now shown that it is possible to recognize people by the way they walk. As yet there has been little formal study of the effects of covariates on the recognition process. We show how these factors can separately affect the walking pattern. Further we assess the contribution and discriminatory significance of the gait dynamics used for recognition. Based on a covariate-based probe dataset of 440 samples, a high recognition rate of 73.4% is achieved using the KN N classifier. This is to confirm that people identification using dynamic gait features is still perceivable with better recognition rate even under the different covariate factors.

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Section: The Clothing Effectsmentioning

confidence: 99%

Exploratory factor analysis of gait recognition

Bouchrika

Nixon

2008

2008 8th IEEE International Conference on Automatic Face &Amp; Gesture Recognition

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“…The optical sensors approach is both effective and efficient for collecting objective data for 3D motion analysis. Today, optical systems have many applications in biomechanical studies [12][13][14][15][16]. These systems have been shown to be accurate, repeatable, and consistent [17], and, as an additional benefit, there is no pain or risk involved in using such systems.…”

Section: Motion Capture Processmentioning

confidence: 99%

A Validation Protocol for Predictive Human Locomotion

Rahmatalla¹,

Xiang²,

Smith³

et al. 2008

SAE Technical Paper Series

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A framework to validate the predicted motion of a computer human model (Santos) is presented in this work. The proposed validation framework is a taskbased methodology. It depends on the comparison of selected motion determinants and joint angles that play major roles in the task, using qualitative and quantitative statistical techniques. In the present work, the validation of Santos walking will be presented. Fortunately, the determinants for normal walking are well defined in the literature and can be represented by (i) hip flexion/extension, (ii) knee flexion/extension, (iii) ankle plantar/dorsiflexion, (iv) pelvic tilt, (v) pelvic rotation, and (vi) lateral pelvic displacement. While Santos is an ongoing research project, the results have shown significant qualitative agreements between the walking determinants of Santos and the walking determinants of four normal subjects.

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“…Alternatively, if the clothing does not permit heat to be conducted or convected away from the body, the wearer can suffer heat-induced fatigue or stroke. A recent study by Rahmatalla et al (2006) found that the stability of human motion can be significantly affected by clothing restrictions, which eventually causes wearers to change their strategies for accomplishing physical tasks.…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Modeling Framework for Analysis of Functional Clothing

Man

Swan

2007

Journal of Engineered Fibers and Fabrics

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In the analysis and design of functional clothing systems, it is helpful to quantify the effects of a system on a wearer's physical performance capabilities. Toward this end, a clothing modeling framework for quantifying the mechanical interactions between a given clothing system design and a specific wearer performing defined physical tasks is proposed. The modeling framework consists of three interacting modules: (1) a macroscale fabric mechanics/dynamics model; (2) a collision detection and contact correction module; and (3) a human motion module. In the proposed framework, the macroscopic fabric model is based on a rigorous large deformation continuum-degenerated shell theory representation. Material models that capture the stress-strain behavior of different clothing fabrics are used in the continuum shell framework. The collision and contact module enforces the impenetrability constraint between the fabric and human body and computes the associated contact forces between the two. The human body is represented in the current framework as an assemblage of overlapping ellipsoids that undergo rigid body motions consistent with human motions while performing actions such as walking, running, or jumping. The transient rigid body motions of each ellipsoidal body segment in time are determined using motion capture technology. The integrated modeling framework is then exercised to quantify the resistance that the clothing exerts on the wearer during the specific activities under consideration. Current results from the framework are presented and its intended applications are discussed along with some of the key challenges remaining in clothing system modeling.

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Effect of Restrictive Clothing on Balance and Gait using Motion Capture and Stability Analysis

Cited by 6 publications

References 25 publications

Exploratory factor analysis of gait recognition

Exploratory factor analysis of gait recognition

A Validation Protocol for Predictive Human Locomotion

A Mathematical Modeling Framework for Analysis of Functional Clothing

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