Literature DB >> 20089472

Moment measurement accuracy of a parallel spherical robot for dynamic posturography.

Paolo Cappa1, Jennifer L Jackson, Fabrizio Patanè.   

Abstract

This paper characterizes the moment measurement accuracy for a novel parallel spherical robot (SR) for dynamic posturography, controllable by position or impedance. The SR consists of three linear motors placed on a support base, a moving base, and three passive arms equipped with uniaxial load cells permitting impedance controlled perturbations. To evaluate the accuracy, a subject stood still on the SR, set in position control mode, while selected sinusoidal trajectories were applied. The moments computed by the load cells were compared to the value measured by a six-component force platform, placed on top of the rotating base. For the intended application of the SR, the errors were negligible with the worse case of only 4 Nm in a total of 15 trials (five conditions, three repetitions). The observed moment error was related mainly to the intrinsic accuracy of the sensors, equal to about 7 N. To demonstrate clinical applicability, the platform was set to impedance control mode and a protocol was tested with a 12-year-old girl with brain injury and a group of four healthy subjects. In total, 24 trials (eight conditions, three repetitions) were recorded for each subject. The results of this pilot study identified distinctive postural behaviors and therefore showed that the SR can be considered as an effective tool for dynamic posturography.

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Year:  2010        PMID: 20089472     DOI: 10.1109/TBME.2009.2037807

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  3 in total

1.  Quantification of postural stability in minimally disabled multiple sclerosis patients by means of dynamic posturography: an observational study.

Authors:  Lucia Grassi; Stefano Rossi; Valeria Studer; Gessica Vasco; Caterina Motta; Fabrizio Patanè; Enrico Castelli; Silvia Rossi; Paolo Cappa
Journal:  J Neuroeng Rehabil       Date:  2017-01-10       Impact factor: 4.262

2.  Measurement of Human Walking Movements by Using a Mobile Health App: Motion Sensor Data Analysis.

Authors:  Sungchul Lee; Ryan M Walker; Yoohwan Kim; Hyunhwa Lee
Journal:  JMIR Mhealth Uhealth       Date:  2021-03-05       Impact factor: 4.773

3.  In Memoriam: Paolo Cappa.

Authors:  Eduardo Palermo; Stefano Rossi; Fabrizio Patanè; Jeffrey Laut; Maurizio Porfiri
Journal:  Sensors (Basel)       Date:  2017-11-18       Impact factor: 3.576

  3 in total

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