On the Measurement of Dynamic Stability of Human Locomotion

Hürmüzlü, Yildirim; Başdoğan, Çağatay

doi:10.1115/1.2895701

Cited by 166 publications

(159 citation statements)

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“…Stability is a critical component of walking [10,14]. It can be defined as the ability to maintain functional locomotion despite the presence of small kinematic disturbances or control errors.…”

Section: Introductionmentioning

confidence: 99%

“…These disturbances are attenuated in time by the neuro-controller and musculoskeletal system in order to maintain a stable walking pattern. Thus, stability must be estimated from the time-dependent expansion or attenuation of kinematic variability [10,14].…”

Section: Introductionmentioning

confidence: 99%

“…Disturbance to the walking trajectory is an ongoing process so the attenuation of kinematic variability is continually manifest. Poincare maps quantify the attenuation of kinematic variability between consecutive strides [14]. This method has the advantage of measuring stability in a multi-degree-of-freedom system.…”

Section: Introductionmentioning

confidence: 99%

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The influence of gait speed on local dynamic stability of walking

2007

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The focus of this study was to examine the role of walking velocity in stability during normal gait. Local dynamic stability was quantified through the use of maximum finite-time Lyapunov exponents, λ Max . These quantify the rate of attenuation of kinematic variability of joint angle data recorded as subjects walked on a motorized treadmill at 20%, 40%, 60%, and 80% of the Froude velocity. A monotonic trend between λ Max and walking velocity was observed with smaller λ Max at slower walking velocities. Smaller λ Max indicates more stable walking dynamics. This trend was evident whether stride duration variability remained or was removed by time normalizing the data. This suggests that slower walking velocities lead to increases in stability. These results may reveal more detailed information on the behavior of the neuro-controller than variability-based analyses alone.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The influence of gait speed on local dynamic stability of walking

2007

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“…Stability is a critical component of both static standing balance and dynamic walking (Goswami et al, 1998;Hurmuzlu and Basdogan, 1994a). It is characterized by the dynamic state of a system wherein the state is the multidimensional posture and movement trajectories at an instant in time.…”

Section: Introductionmentioning

confidence: 99%

Dynamic stability differences in fall-prone and healthy adults

Granata

Lockhart

2008

Journal of Electromyography and Kinesiology

139

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Typical stability assessments characterize performance in standing balance despite the fact that most falls occur during dynamic activities such as walking. The objective of this study was to identify dynamic stability differences between fall-prone elderly individuals, healthy age-matched adults, and young adults. Three-dimensional video-motion analysis kinematic data were recorded for 35 contiguous steps while subjects walked on a treadmill at three speeds. From this data, we estimated the vector from the center-of-mass to the center of pressure at each foot-strike. Dynamic stability of walking was computed by methods of Poincare analyses of these vectors. Results revealed that the fall-prone group demonstrated poorer dynamic stability than the healthy elderly and young adult groups. Stability was not influenced by walking velocity, indicating that group differences in walking speed could not fully explain the differences in stability. This pilot study supports the need for future investigations using larger population samples to study fall-prone individuals using nonlinear dynamic analyses of movement kinematics.

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“…[14][15][16][17]). Allen & Sracic have even proposed that a general nonlinear system might be more easily identified if excited such that an LTP model is appropriate [18].…”

Section: Introductionmentioning

confidence: 99%

Output-Only Modal Analysis of Linear Time Periodic Systems with Application to Wind Turbine Simulation Data

Allen

Sracic

Chauhan

et al. 2011

Structural Dynamics and Renewable Energy, Volume 1

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Abstract:Many important systems, such as turbomachinery, helicopters and wind turbines, must be modeled with linear time-periodic equations of motion to correctly predict resonance phenomena. Time periodic effects in wind turbines might arise due to stratification in the velocity of the wind with height, changes in the aerodynamics of the blades as they pass the tower and/or blade-to-blade manufacturing variations. These effects may cause parametric resonance or other unexpected resonances, so it is important to properly characterize them so that these machines can be designed that achieve the high reliability, safety, and long lifetimes demanded to provide economical power. This work presents an output-only system identification methodology that can be used to identify models for linear, periodically time-varying systems. The methodology is demonstrated for the simple Mathieu oscillator and then used to interrogate simulated measurements from a rotating wind turbine, revealing that at least one of the turbine's modes seems to be time-periodic. The measurements were simulated using a state-of-the-art wind turbine model called HAWC2 that includes both structural dynamic and aerodynamic effects. Simulated experiments such as this may be useful both to validate dynamic models for a turbine or to obtain a set of time-periodic equations of motion from a numerical model; these are not readily available by other means due to the way that the aeroelastic effects are treated in the simulation code.

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On the Measurement of Dynamic Stability of Human Locomotion

Cited by 166 publications

References 0 publications

The influence of gait speed on local dynamic stability of walking

The influence of gait speed on local dynamic stability of walking

Dynamic stability differences in fall-prone and healthy adults

Output-Only Modal Analysis of Linear Time Periodic Systems with Application to Wind Turbine Simulation Data

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