Postural data from Stargardt's syndrome patients

none5noThe database is a collection of postural data acquired from 10 patients affected by the rare Stargardt's syndrome, all having the ABCA4 gene mutation, and from 10 control healthy subjects. Specifically, the database includes a file (.xlxs) called SubjectsData and 20 datasets (MATLAB structures) containing postural signals. Each subject performed a total of 15 postural tests, 5 postural tests for 3 different conditions (‘C’: eyes-closed; ‘O’: eyes-open, still target fixation; ‘M’: eyes-open, moving target tracking). For each postural test, 11 postural derived signals (the anterior-posterior force, the medio-lateral force, the vertical force, the plate moment about x axis, the plate moment about y axis, the plate moment about z axis, the plate moment about top plate surface about x axis, the plate moment about top plat surface about y axis, the x-coordinate of the center of pressure, the y-coordinate of the center of pressure, and the free moment about z axis) were computed from 8 raw signals, acquired at the Ophthalmic Hospital of Turin, Italy, through an 8-channel Kistler 9286A force platform connected to a Step32 system. Thus, a total of 285 postural signals (120 raw and 165 derived) are available for each subject. The database may be useful to: (1) investigate postural adaptations of patients affected by Stargardt's syndrome; (2) support definition of rehabilitative procedures to reduce postural instability of patients affected by Stargardt's syndrome; and (3) support investigation on visual control of balance in the general population.openSbrollini A.; Agostini V.; Cavallini C.; Burattini L.; Knaflitz M.Sbrollini, A.; Agostini, V.; Cavallini, C.; Burattini, L.; Knaflitz, M

Circular components in center of pressure signals

Static posturography provides an objective assessment of postural control by characterizing the body sway during upright standing. The Center-of-Pressure (CoP) signal is recorded by a force platform and it is analyzed by means of many different models and techniques. Most of the parameters calculated according to these different approaches are affected by relevant intra- and inter-subject variability and/or do not have a clear physiological interpretation. Traditional approaches decompose the CoP signal into antero-posterior and medio-lateral time series, corresponding to ankle plantar/dorsiflexion and hip adduction/abduction, respectively. In this study we hypothesized that CoP signals show inherent rotational characteristics. To verify our hypothesis we applied the rotary spectra analysis to the 2-dimensional CoP signal to decompose it into clockwise and counter-clockwise rotational components. We demonstrated the presence of rotational components in the CoP signal of healthy subjects, providing a reference data set of the spectral characteristics of these component

Analysis of stabilometric signals in frequency domain

Tato práce se zabývá metodami frekvenční a časově frekvenční analýzy stabilometrického signálu. V úvodu je popsána teorie k posturografii a posturografickému měření. Dále práce obsahuje popis stabilometrických parametrů pro hodnocení v časové oblasti (1D a 2 D parametry) a ve frekvenční oblasti. Cílem práce je vytvořit přehled základních metod zpracování a předzpracování stabilometrického signálu a tyto metody porovnat. Součástí je praktická realizace analýzy pomocí frekvenčních metod, Fourierovy transformace a Burgovy metody a časově-frekvenčních metod, krátkodobé Fourierovy transformace a vlnkové transformace analýzy. Součástí jsou nástroje pro srovnání těchto metod.This work deals with the metods frequency and time frequency analysis of stabilometric signal. In the introroduction is described theory about posturography and posturographic measurment. The work contains describtion of stabilometric parametrs in time domain (1D and 2D parametrs) and in frequency domain. The aim is create review of basic metods used to processing and preprocessing of stabilometric signals and comparing this methods . In work is realized ferquency analysis used Frourier transfrmation and Burg method and time-frequency analysis used Short time Frourier transformation and Wavelet transformation. One part of program is aimed on comparison of this methods.

Rotary spectra analysis applied to static stabilometry

Static stabilometry is a technique aimed at quantifying postural sway during quiet standing in the upright position. Many different models and many different techniques to analyze the trajectories of the Centre of Pressure (CoP) have been proposed. Most of the parameters calculated according to these different approaches are affected by a relevant intra- and inter-subject variability or do not have a clear physiological interpretation. In this study we hypothesize that CoP trajectories have rotational characteristics, therefore we decompose them in clockwise and counter-clockwise components, using the rotary spectra analysis. Rotary spectra obtained studying a population of healthy subjects are described through the group average of spectral parameters, i.e., 95% spectral bandwidth, mean frequency, median frequency, and skewness. Results are reported for the clockwise and the counter-clockwise components and refer to the upright position maintained with eyes open or closed. This study demonstrates that the approach is feasible and that some of the spectral parameters are statistically different between the open and closed eyes conditions. More research is needed to demonstrate the clinical applicability of this approach, but results so far obtained are promising