A novel control model for elucidating human postural balance

Frazier, P.D.; Chouikha, Mohamed F.

doi:10.1109/wcica.2004.1342018

Cited by 4 publications

(4 citation statements)

References 18 publications

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“…The concept of employing SIE to mathematically model processes which undergo rapid changes in their state has been in practice for over a half of a century [8,[18][19][20][21][22][23][24][25]. While SIE have been successful at modeling a wide range of physical occurrences, such as RC circuits [20] and biological systems [24,25], there has been little attempt to use SIE in the signal-modeling context.…”

Section: Introductionmentioning

confidence: 99%

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Effective Parametric Estimation of Non-Gaussian Autoregressive Moving Average Processes Exhibiting Noise with Impulses

Frazier

Chouikha

2006

J VLSI Sign Process Syst Sign Image Video Technol

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In statistical signal processing, parametric modeling of non-Gaussian processes experiencing noise interference is a very important research topic. Particularly challenging to some researchers is how to estimate signals encountering stochastic noise process exhibiting sharp spikes. The authors propose the use of systems with impulse effect along with the classic autoregressive moving average model as a novel parametric modeling tool to successfully estimate these specific processes. The proficiency of this original system is illustrated in a performance table.

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Section: Introductionmentioning

confidence: 99%

“…While SIE have been successful at modeling a wide range of physical occurrences, such as RC circuits [20] and biological systems [24,25], there has been little attempt to use SIE in the signal-modeling context. Most of the significant studies on the topic of SIE have focused on stability issues [18,19,[21][22][23]26].…”

Section: Introductionmentioning

confidence: 99%

Effective Parametric Estimation of Non-Gaussian Autoregressive Moving Average Processes Exhibiting Noise with Impulses

Frazier

Chouikha

2006

J VLSI Sign Process Syst Sign Image Video Technol

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“…In 2004, Frazier and Chouikha presented a new nonlinear postural controller [38]. It was an optimal switching state controller that also contained a learning algorithm intended to imitate the central nervous system, thereby providing improved performance over a controller using a linear quadratic Gaussian (LQG) and an extended Kalman filter.…”

Section: Nonlinear Control Strategiesmentioning

confidence: 99%

“…The controller was designed to select which method to use based on the current system state. A feedforward control was also used by Frazier and Chouikha in order to minimize the transient error in response to a disturbance [38] in conjunction with a feedback component and other control components.…”

Section: Open-loop Controlmentioning

confidence: 99%

Prediction of Human Postural Response in Shipboard Environments Using Multibody Dynamics and Sensory-Based Control

Bourgeois¹

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Accurate prediction of the human response to ship motion can lead to improved safety and efficiency of ship operation and design. The objective of this thesis is to derive and validate a human postural stability model having similar dynamic response to an actual human when exposed to six-degree-of-freedom ship motion. The human body is modelled as a four-link inverted pendulum, which allows for representative motion of the ankles, knees, waist, and neck. Human postural stability experiments were performed during an eight day heavy-weather sea trial in the North Atlantic Ocean. This was the first known attempt to use a variety of advanced data acquisition techniques in a shipboard environment to record human sensory stimuli. This included using two full-body motion capture systems to record body segment positions and orientations, instrumented shoe insoles to measure somatosensory data, an inertial sensor to measure head vestibular data, and a head-mounted camera to capture visual proprioceptive data. The separate data sets were combined in order to describe the motion of each subject's centre of mass and centre of force within their base of support. Human postural reactions during the sea trial were correlated with the ship motion in order to derive control gains for the inverted pendulum model which included both open-loop and closed-loop components. Simulation results were compiled from 49 test cases and it was observed that the derived controller matched human response frequently in both postural roll and pitch. Further analysis indicated that there was a consistent relationship between the accuracy of the model's motions and the direction of greater ship angular motions. The specific contributions of this thesis include the spatial postural stability model, the detailed biometric data gathered during the sea trial, the control system developed by correlating ship motions with human response, and the compilation of comprehensive data sets of postural stability parameters of humans experiencing six-degree-of-freedom motion.ii Acknowledgements I would like to thank Rob Langlois, my supervisor and friend, for his support and guidance over the last five point five years of this doctorate degree. If you had not tempted me back to grad school with exciting research opportunities at a research facility that is even now still being built, none of this wonderful journey would have taken place.I would like to thank Aren Hunter, Roger Arsenault, Alex Ritchie, and the rest of the scientific staff at DRDC-Atlantic for all of their generous support in planning and performing the sea trial experiments. I would also like to extend my gratitude to the crew of CFAV Quest because without their help the human postural stability experiments would not have been as successful as they were.

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A novel parametric estimation algorithm for non-Gaussian processes experiencing impulsive noise

Frazier¹,

Chouikha

2007

2007 6th International Conference on Information, Communications &Amp; Signal Processing

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A novel control model for elucidating human postural balance

Cited by 4 publications

References 18 publications

Effective Parametric Estimation of Non-Gaussian Autoregressive Moving Average Processes Exhibiting Noise with Impulses

Effective Parametric Estimation of Non-Gaussian Autoregressive Moving Average Processes Exhibiting Noise with Impulses

Prediction of Human Postural Response in Shipboard Environments Using Multibody Dynamics and Sensory-Based Control

A novel parametric estimation algorithm for non-Gaussian processes experiencing impulsive noise

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