Med Biol Eng Comput - Accelerometry-based prediction of movement dynamics for balance monitoring.

Tópicos

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Resumo

This paper proposes a 2D functional evaluation tool for estimating subject-specific body segment parameters, which uses a simple motor task (repeated sit-to-stand, rSTS), recorded with one single-axis accelerometer (SAA) per segment and a force plate (FP). After this preliminary estimation, the accelerometer alone is used to make quasi-real-time predictions of ground reaction force (anterior/posterior, F ( X ), and vertical, F ( Z ), components), center of pressure (CoP) and center of mass (CoM), during rSTS and postural oscillation in the sagittal plane. These predicted dynamic variables, as well as those obtained using anthropometric parameters derived from De Leva, were compared to actual FP outputs in terms of root mean-squared errors (RMSEs). Using De Leva's parameters in place of those estimated, RMSEs increase from 12 to 21?N (F ( X )), from 21 to 24?N (F ( Z )), and from 21.1 to 55.6?mm (CoP) in rSTS; similarly, RMSEs increase from 3.1 to 3.3?N (F ( X )) and from 5.5 to 6.6?mm (CoP) in oscillatory trials. A telescopic inverted pendulum model was adopted to analyze the balance control in rSTS using only predicted CoP and CoM. Results suggest that one SAA per segment is sufficient to predict the dynamics of a biomechanical model of any degrees of freedom.

Resumo Limpo

paper propos d function evalu tool estim subjectspecif bodi segment paramet use simpl motor task repeat sittostand rsts record one singleaxi acceleromet saa per segment forc plate fp preliminari estim acceleromet alon use make quasirealtim predict ground reaction forc anteriorposterior f x vertic f z compon center pressur cop center mass com rsts postur oscil sagitt plane predict dynam variabl well obtain use anthropometr paramet deriv de leva compar actual fp output term root meansquar error rmses use de leva paramet place estim rmses increas n f x n f z mm cop rsts similar rmses increas n f x mm cop oscillatori trial telescop invert pendulum model adopt analyz balanc control rsts use predict cop com result suggest one saa per segment suffici predict dynam biomechan model degre freedom

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