2019Medical Engineering & PhysicsRequires access

A method to estimate inertial properties and force plate inertial components for instrumented platforms

Brad Roberts, Jeremy C. Hall, Andrew D. Williams, Hossein Rouhani, Albert H. Vette

Open publisher page 6 citations

Abstract

• Moving platform-embedded force plate signals contain inertial components. • Removal of inertial components requires knowledge of the system's inertial properties. • We proposed a method to estimate inertial properties and components for any platform. • The method was used to estimate the inertial properties for one specific platform. • We found excellent agreement between measured and computed force plate signals. Kinetic data acquired from force plates embedded in moving platforms naturally contain artifacts due to platform acceleration, called force plate inertial components. While they can be estimated and removed from the measured signals, the system's inertial properties need to be known. Our objective was to: (1) develop a method for estimating the inertial properties and force plate inertial components for any instrumented platform; (2) estimate the inertial properties specifically for the Computer-Assisted Rehabilitation Environment (CAREN); and (3) validate the estimates with new experimental data. Unloaded ramp-and-hold perturbations (for estimation) and unloaded random perturbations (for validation) were executed to obtain the force, moment, and motion of the CAREN platform. Inertial properties were estimated by minimizing the error between the measured and computed inertial forces and moments. Obtained estimates were validated by calculating the coefficient of determination ( R 2 ) between the measured and computed forces or moments when keeping the inertial properties fixed. The estimates of the CAREN's inertial properties exhibited low variability across trials, and R 2 for the validation trials was 0.90 ± 0.08 (mean ± standard deviation). The developed method can be used for removing inertial components from force plate signals, yielding reliable estimates of ground reactions in dynamic biomechanical research and clinical assessments.

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What this paper is about

• Moving platform-embedded force plate signals contain inertial components. • Removal of inertial components requires knowledge of the system's inertial properties. • We proposed a method to estimate inertial properties and components for any platform. • The method was used to estimate the inertial properties for one specific platform. • We found excellent agreement between measured and computed force plate signals. Kinetic data acquired from force plates embedded in moving platforms naturally contain artifacts due to platform acceleration, called force plate inertial components. While they can be estimated and removed from the measured signals, the system's inertial properties need to be known. Our objective was to: (1) develop a method for estimating the inertial properties and force plate inertial components for any instrumented platform; (2) estimate the inertial properties specifically for the Computer-Assisted Rehabilitation Environment (CAREN); and (3) validate the estimates with new experimental data. Unloaded ramp-and-hold perturbations (for estimation) and unloaded random perturbations (for validation) were executed to obtain the force, moment, and motion of the CAREN platform. Inertial properties were estimated by minimizing the error between the measured and computed inertial forces and moments. Obtained estimates were validated by calculating the coefficient of determination ( R 2 ) between the measured and computed forces or moments when keeping the inertial properties fixed. The estimates of the CAREN's inertial properties exhibited low variability across trials, and R 2 for the validation trials was 0.90 ± 0.08 (mean ± standard deviation). The developed method can be used for removing inertial components from force plate signals, yielding reliable estimates of ground reactions in dynamic biomechanical research and clinical assessments.

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Available abstract

• Moving platform-embedded force plate signals contain inertial components. • Removal of inertial components requires knowledge of the system's inertial properties. • We proposed a method to estimate inertial properties and components for any platform. • The method was used to estimate the inertial properties for one specific platform. • We found excellent agreement between measured and computed force plate signals. Kinetic data acquired from force plates embedded in moving platforms naturally contain artifacts due to platform acceleration, called force plate inertial components. While they can be estimated and removed from the measured signals, the system's inertial properties need to be known. Our objective was to: (1) develop a method for estimating the inertial properties and force plate inertial components for any instrumented platform; (2) estimate the inertial properties specifically for the Computer-Assisted Rehabilitation Environment (CAREN); and (3) validate the estimates with new experimental data. Unloaded ramp-and-hold perturbations (for estimation) and unloaded random perturbations (for validation) were executed to obtain the force, moment, and motion of the CAREN platform. Inertial properties were estimated by minimizing the error between the measured and computed inertial forces and moments. Obtained estimates were validated by calculating the coefficient of determination ( R 2 ) between the measured and computed forces or moments when keeping the inertial properties fixed. The estimates of the CAREN's inertial properties exhibited low variability across trials, and R 2 for the validation trials was 0.90 ± 0.08 (mean ± standard deviation). The developed method can be used for removing inertial components from force plate signals, yielding reliable estimates of ground reactions in dynamic biomechanical research and clinical assessments.

Key concepts: Inertial frame of reference, Fictitious force, Inertial measurement unit, Acceleration, Accelerometer, Moment (physics), Ground reaction force, Standard deviation

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