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The filtering of the posturographic signals shows the age related features.

Michalak KP, Przekoracka-Krawczyk A, Nawrot P, Woźniak P, Vieregge P - ScientificWorldJournal (2014)

Bottom Line: The posturographic signals of old patients with idiopathic gait disturbance were compared with the control group of similar age and with younger patients.The significant differences were observed mainly in the range of filter frequencies f = 0.1-1.5 Hz and f = 2.2-5.5 Hz with a maximum effect at approximately 4-5 Hz.The results suggest that idiopathic gait disturbance is the final stage of the aging process of postural system.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Vision Science and Optometry, Faculty of Physics, Adam Mickiewicz University of Poznań, Umultowska Street 85, 61-614 Poznań, Poland.

ABSTRACT

Objective: Lower frequencies of slow oscillations of the posturographic signals can be removed using high-pass filtering. This procedure releases postural reflexes possessing higher frequencies and lower amplitude range. Mutual dependence between the x and y components of posturographic signals was analyzed using principal component analysis (PCA). The posturographic signals of old patients with idiopathic gait disturbance were compared with the control group of similar age and with younger patients. There was also the analysis of the influence of the eyes state (open versus closed) and the head position (normal or bent back). The statistically significant differences in the mutual dependence between x and y components between the groups of patients were analyzed using MANOVA. The significant differences were observed mainly in the range of filter frequencies f = 0.1-1.5 Hz and f = 2.2-5.5 Hz with a maximum effect at approximately 4-5 Hz. A detailed post-hoc analysis is also presented. The differences in the higher frequency range suggest the main disturbance to be connected with the spinal reflexes. Visual and vestibular support appear insufficient for postural stability control in the idiopathic gait disturbance group. The results suggest that idiopathic gait disturbance is the final stage of the aging process of postural system.

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Related in: MedlinePlus

Example of the decomposition of the posturographic signal using spatiotemporal decomposition. The input PCA matrix was built from 4 columns: I: xn(1~1023), II: xn(2~1024), III: yn(1~1023), and IV: yn(2~1024). Columns I-II and III-IV reflect the same signals being shifted in time by one sample (i.e., t = 0.02 s). The two upper signals represent the xn and yn signals after high-pass filtering f = 3 Hz. The 4 lower signals are the PCA columns after rotation. The SI and SII represent mainly the signal. SIII and SIV represent mainly the noise. The synchronous deflection in xn and yn is connected with high amplitude of the deflection in SI (see dashed line).
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fig2: Example of the decomposition of the posturographic signal using spatiotemporal decomposition. The input PCA matrix was built from 4 columns: I: xn(1~1023), II: xn(2~1024), III: yn(1~1023), and IV: yn(2~1024). Columns I-II and III-IV reflect the same signals being shifted in time by one sample (i.e., t = 0.02 s). The two upper signals represent the xn and yn signals after high-pass filtering f = 3 Hz. The 4 lower signals are the PCA columns after rotation. The SI and SII represent mainly the signal. SIII and SIV represent mainly the noise. The synchronous deflection in xn and yn is connected with high amplitude of the deflection in SI (see dashed line).

Mentions: Figure 2 shows the exemplary results of the PCA decomposition. Two upper signals represent the xn and yn components before orthogonal rotation and the lower 4 signals present the result of the PCA rotation for i = 2. It can be observed that the common oscillation of both xn and yn components results in high oscillation in the first PCA component SI.


The filtering of the posturographic signals shows the age related features.

Michalak KP, Przekoracka-Krawczyk A, Nawrot P, Woźniak P, Vieregge P - ScientificWorldJournal (2014)

Example of the decomposition of the posturographic signal using spatiotemporal decomposition. The input PCA matrix was built from 4 columns: I: xn(1~1023), II: xn(2~1024), III: yn(1~1023), and IV: yn(2~1024). Columns I-II and III-IV reflect the same signals being shifted in time by one sample (i.e., t = 0.02 s). The two upper signals represent the xn and yn signals after high-pass filtering f = 3 Hz. The 4 lower signals are the PCA columns after rotation. The SI and SII represent mainly the signal. SIII and SIV represent mainly the noise. The synchronous deflection in xn and yn is connected with high amplitude of the deflection in SI (see dashed line).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4281402&req=5

fig2: Example of the decomposition of the posturographic signal using spatiotemporal decomposition. The input PCA matrix was built from 4 columns: I: xn(1~1023), II: xn(2~1024), III: yn(1~1023), and IV: yn(2~1024). Columns I-II and III-IV reflect the same signals being shifted in time by one sample (i.e., t = 0.02 s). The two upper signals represent the xn and yn signals after high-pass filtering f = 3 Hz. The 4 lower signals are the PCA columns after rotation. The SI and SII represent mainly the signal. SIII and SIV represent mainly the noise. The synchronous deflection in xn and yn is connected with high amplitude of the deflection in SI (see dashed line).
Mentions: Figure 2 shows the exemplary results of the PCA decomposition. Two upper signals represent the xn and yn components before orthogonal rotation and the lower 4 signals present the result of the PCA rotation for i = 2. It can be observed that the common oscillation of both xn and yn components results in high oscillation in the first PCA component SI.

Bottom Line: The posturographic signals of old patients with idiopathic gait disturbance were compared with the control group of similar age and with younger patients.The significant differences were observed mainly in the range of filter frequencies f = 0.1-1.5 Hz and f = 2.2-5.5 Hz with a maximum effect at approximately 4-5 Hz.The results suggest that idiopathic gait disturbance is the final stage of the aging process of postural system.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Vision Science and Optometry, Faculty of Physics, Adam Mickiewicz University of Poznań, Umultowska Street 85, 61-614 Poznań, Poland.

ABSTRACT

Objective: Lower frequencies of slow oscillations of the posturographic signals can be removed using high-pass filtering. This procedure releases postural reflexes possessing higher frequencies and lower amplitude range. Mutual dependence between the x and y components of posturographic signals was analyzed using principal component analysis (PCA). The posturographic signals of old patients with idiopathic gait disturbance were compared with the control group of similar age and with younger patients. There was also the analysis of the influence of the eyes state (open versus closed) and the head position (normal or bent back). The statistically significant differences in the mutual dependence between x and y components between the groups of patients were analyzed using MANOVA. The significant differences were observed mainly in the range of filter frequencies f = 0.1-1.5 Hz and f = 2.2-5.5 Hz with a maximum effect at approximately 4-5 Hz. A detailed post-hoc analysis is also presented. The differences in the higher frequency range suggest the main disturbance to be connected with the spinal reflexes. Visual and vestibular support appear insufficient for postural stability control in the idiopathic gait disturbance group. The results suggest that idiopathic gait disturbance is the final stage of the aging process of postural system.

Show MeSH
Related in: MedlinePlus