Thresholds for step initiation induced by support-surface translation: a dynamic center-of-mass model provides much better prediction than a static model

Pai, Yi–Chung; Maki, Brian E.; Iqbal, Kamran; McIlroy, William E.; Perry, Stephen D.

doi:10.1016/s0021-9290(99)00199-2

Cited by 93 publications

(49 citation statements)

References 8 publications

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“…This approach detected a loss of balance when the center of mass exceeded the limits of the base of support defined by both feet (see, for example, Pai et al 2000). The base of support limits were calculated as a percentage of foot length.…”

Section: Candidate Kinematic Signals For Use In the Detection Func-mentioning

confidence: 99%

“…From a mechanical standpoint, determining these limits would require a model with knowledge of center of mass location, range of motion limits, and maximum torque capacities as well as base of support limits. Even then it would still be unable to account for our perception of environmental risk, sensory predictions, and even task familiarization, all of which have been shown to affect postural control and the initiation of compensatory responses (Cham and Redfern 2002;Eng et al 1994;Pai et al 2000). This paper addresses these issues by developing an alternative conceptual description of how the CNS might detect a loss of balance.…”

Section: Introductionmentioning

confidence: 99%

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On Use of a Nominal Internal Model to Detect a Loss of Balance in a Maximal Forward Reach

Ahmed

Ashton‐Miller²

2007

Journal of Neurophysiology

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Ahmed AA, Ashton-Miller JA. On use of a nominal internal model to detect a loss of balance in a maximal forward reach. J Neurophysiol 97: 2439 -2447, 2007. First published January 24, 2007 doi:10.1152/jn.00164.2006. We hypothesize that the CNS detects a loss of balance by comparing outputs predicted by a nominal, forward internal model with actual sensory outputs. When the resulting control error signal reaches an anomalously large value, this control error anomaly (CEA) signals a loss of balance and precedes any observable compensatory response. To test this hypothesis, a multi-input, multi-output internal model of a standing forward reach task was developed that incorporated on-line model identification and a Gaussian failure detection algorithm. Eleven healthy young women were then asked to stand and reach forward to a target positioned from 95 to 125% of their maximum reach distance. Kinematic and kinetic data were recorded at 100 Hz unilaterally from the upper body, leg, and foot. Evidence of successful CEA detection was a compensatory step between 100 ms and 2 s later. The results show that use of a threshold, set at 3 SD from the mean, on error in the control of leg segment acceleration detected a CEA and correctly predicted a compensatory response in 92.6% of 108 trials. Leg acceleration control error was a better predictor than upper body or foot acceleration control error (P ϭ 0.000). CEA detection performed more reliably than loss of balance detection algorithms based on kinematic thresholds (P ϭ 0.000). The results support the hypothesis that a loss of balance may be identified via the use of a nominal forward internal model and probabilistic error monitoring.

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Section: Candidate Kinematic Signals For Use In the Detection Func-mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On Use of a Nominal Internal Model to Detect a Loss of Balance in a Maximal Forward Reach

Ahmed

Ashton‐Miller²

2007

Journal of Neurophysiology

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“…Most studies evaluating stepping strategies use randomized platform (McIlroy and Maki 1996;Pai et al 2000;Schulz et al 2005) or waist-pull (Luchies et al 1994;Pai et al 1998;Mille et al 2003) perturbations. Schulz et al (2006) investigated the CoM TtC under such dynamic conditions, using the velocity-only TtC computation.…”

Section: Introductionmentioning

confidence: 99%

Predicting dynamic postural instability using center of mass time-to-contact information

Hasson

Emmerik

Caldwell

2008

Journal of Biomechanics

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Our purpose was to determine whether spatiotemporal measures of center of mass motion relative to the base of support boundary could predict stepping strategies after upper-body postural perturbations in humans. We expected that inclusion of center of mass acceleration in such time-tocontact (TtC) calculations would give better predictions and more advanced warning of perturbation severity. TtC measures were compared with traditional postural variables, which don't consider support boundaries, and with an inverted pendulum model of dynamic stability developed by Hof et al. (2005). A pendulum was used to deliver sequentially increasing perturbations to 10 young adults, who were strapped to a wooden backboard that constrained motion to sagittal plane rotation about the ankle joint. Subjects were instructed to resist the perturbations, stepping only if necessary to prevent a fall. Peak center of mass and center of pressure velocity and acceleration demonstrated linear increases with postural challenge. In contrast, boundary relevant minimum TtC values decreased nonlinearly with postural challenge, enabling prediction of stepping responses using quadratic equations. When TtC calculations incorporated center of mass acceleration, the quadratic fits were better and gave more accurate predictions of the TtC values that would trigger stepping responses. In addition, TtC minima occurred earlier with acceleration inclusion, giving more advanced warning of perturbation severity. Our results were in agreement with TtC predictions based on Hof's model, and suggest that TtC may function as a control parameter, influencing the postural control system's decision to transition from a stationary base of support to a stepping strategy.

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“…Perturbation of supporting surface is a popular approach for the dynamic balance test. The dynamic postural tests showed considerably better accuracy than the static tests to predict injury during sport and functional activities (12). In the previous research less attention was paid to dynamic postural control tests and challenging tasks in the subjects who underwent ACLreconstruction (5).…”

Section: Introductionmentioning

confidence: 99%

The Effects of Functional Knee Brace on Postural Control in Patients Who Underwent Anterior Cruciate Ligament Reconstruction

Salehi

Goharpey

Tayebi

et al. 2016

Jentashapir J Health Res

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Background: The current study aimed to evaluate the postural control in patients underwent anterior cruciate ligament reconstruction pre and post wearing functional knee brace. Methods: Eighteen athletes undergone unilateral anterior cruciate ligament reconstruction included in the study. They had unilateral anterior cruciate ligament reconstruction at least six months before session test. Postural control was assessed pre and post wearing custom-fit functional knee brace using a posturographic platform prokin 254. The balance tests included: 1) standing on prokin platform with eyes open/closed on anterior cruciate ligament reconstruction limb, 2) standing on prokin platform with eyes open/closed on both limbs. The standard deviation (SD) of body sway along the anteroposterior (AP) and mediolateral (ML) axis, mean velocity of center of pressure (COP) along AP/ ML axis and the area ellipse (measured in 2 mm) were calculated. Results: Results of the paired T-test revealed a significant effect on selected postural control variables for the brace conditions especially in low challengeable conditions (double leg, eyes open test situations) (P < 0.05). But in high challengeable conditions this effect was not significant. Conclusions: Functional knee brace improved postural control in the simple balancing task in the subjects with anterior cruciate ligament reconstruction. But this improvement in more difficult balancing task was limited.

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Thresholds for step initiation induced by support-surface translation: a dynamic center-of-mass model provides much better prediction than a static model

Cited by 93 publications

References 8 publications

On Use of a Nominal Internal Model to Detect a Loss of Balance in a Maximal Forward Reach

On Use of a Nominal Internal Model to Detect a Loss of Balance in a Maximal Forward Reach

Predicting dynamic postural instability using center of mass time-to-contact information

The Effects of Functional Knee Brace on Postural Control in Patients Who Underwent Anterior Cruciate Ligament Reconstruction

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