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Body sway on force platform: the clinical relevance of the FFT Analysis


Quiet stance balance is a function developed through human species evolution with musculo-skeletal capabilities and neurological control abilities. A quick feel of the difficulty of the quiet stance task is given by remembering how long, painful and often frustrating is the process through which every child achieves the ability of standing. The task has been studied since 16851 and since 1836 it is among the clinical tests2. More recently the use of static force platforms and of Comput-ers capable of plotting the COP (Center of Pressure) during the test has resulted in the proposal of a wide range of parameters describing the physiological functional performances of the subject under test3,4. A widespread debate about these parameters is suggesting – the process is still un-derway – some significant key elements5 as more suitable for the diagnostic evaluation6 and, on another perspective, as better fitting the requirements of the design of anthropomorphic robots7.
Under known assumptions body sway is often described with the Inverse Pendulum theory where the Center of Mass is displaced over the ground by some 2/3 of the subject height. Both Antero-Posterior and Latero-Lateral Sway, in spite of different mechanical structures (on the frontal plane the two limbs, hinged on the pelvis and ankles, form a “frame” while on the sagittal plane the model is much clearer), show similar oscillating frequency values8.
Given the Pendulum Equations for a height range 150-210 cm the corresponding frequency range is 0,041 Hz (150 cm) – 0,0347 Hz (210 cm). Experimental evidence is showing higher natural fre-quencies (0,6 Hz for a subject 170 cm tall9) that seem likely to depend on the mechanical stiff-ness10 and on the time constant of feed-back control (afferent and efferent delays, low frequency muscle response) that do require the presence of a superior motor planning feed-forward function 11,12. It is however well known that musculoskeletal pain very often affects the Sway13 and possibly its frequencies.
It is therefore important to get a reliable spectral analysis from the recorded sway during the in-strumented Romberg test. Calculation and FFT (Fast Fourier Transform) algorithms offer the pos-sibility of recognizing the spectral composition of the sway motion on the two planes.
Critical parameters to obtain a reliable FFT are the duration of the test (that defines the lowest de-tectable frequency) and the sampling rate (that defines the highest detectable frequency) 13,14,15.

Harmonic Analysis of the COP Plot

By applying the FFT algorithm on a 100 Hz sampled Sway over a 40 second recording 15, it has been possible to analyze the Frequency Spectral Composition of both the Antero-Posterior and Latero-Lateral Sway of a population of 1.234 subjects (627 F + 607 M) aged 7 to 77 years and not showing evident deficit/dysfunction.
The detectable frequency range was between 0,025 Hz (1/Acquisition Time) and 10 Hz (Sampling Frequency/10).
ARGO® force platform, further developed in the FremsLife ArgoPlus®, was used. Metrologic accuracy of said platform has been demonstrated16.
To “filter” the recordings of subjects apparently in “border-line” conditions the SPF (Score of Pos-turale Functionality) Score was used. Such index was defined17 taking into account 63 parame-ters or derived indicators that were demonstrated to be statistically significant18. Each parame-ter is given value 1 when it deviates from average normal value by more than ±2σ. Thus, higher SPF are indicating worse overall characteristics. The records that were used are pertaining to sub-jects showing a SPF score  9.
Harmonic Spectral Power was calculated over 8 bands on each axis. The plot appears to be rather smooth and independent of the test mode (opened or closed eyes).
Some differences, statistically insignificant, can be seen among the sexes: males would oscillate a little more than the females. When comparing the distributions of the normalized powers to the average value of each test, a considerable dispersion due to the “information content” presented by the Harmonic Spectral Power is shown.
For example, see the harmonic analysis of the two test (Eyes Closed and Eyes Opened) of a slightly dysfunctional subject for probable arthrosis at the spine level. The peaks would appear to be in correlation with the height of the “hinges” (cervico-thoracic, thoraco-lumbar, lumbo-sacral).



For what has been said, it can be concluded that, provided that we have an adequate instrument (accuracy, frequency of sampling of the signal), the harmonic analysis can be a decisive tool for the interpretation of the possible causes of postural dysfunction.

Bibliographic references

¹ Alphonsus Borelli De Motu Animalium – COG position is found to be at 57% of the height of the subject
² Lanska DJ, Goetz CG. Romberg’s sign Development, adoption, and adaptation in the 19th century. Neurology 2000; 55: 1201-1206
³ Woollacott MH, Shumway-Cook A. Vertigo: Clinical and research methodology for the study of posture and balance. London: Sprinter, 1999
⁴ Winter DA. In: Biomechanics and motor control of human movement, 2nd ed. New York, NY: John Wiley & Sons; 1990. p. 93–6
⁵ Nieschalk M, Delank KW, Stoll W, Quantitative evaluation of the Romberg test Laryngorhinootologie 1995; 74(8): 489-94 and Collins JJ & De Luca CJ (1993). Open-loop and closed-loop control of posture: a random-walk analysis of centre-of-pressure trajectories. Exp Brain Res 95, 308–318
⁶ Yifa Jiang, Hidenori Kimura Balance-Keeping Control of Upright Standing in Biped Human Beings and its Application for Stability Assessment in Humanoid Robots I-Tech Vienna June 2007
⁷ Soames RW, Atha J The Spectral Characteristics of Postural Sway Behaviour Eur J Appl Physiol Occup Physiol 1982; 49(2):169-77
⁸ R.-J. Cherng, H.-Y. Lee, F.-C. Su Frequency spectral characteristics of standing balance in children and young adults Medical Engineering & Physics 25 (2003) 509–515 and Williams HG, McClenaghan BA, Dickerson J. Spectral characteris-tics of postural control in elderly individuals. Arch Phys Med Rehabil 1997;78:737-44
⁹ Winter, David A., Aftab E. Patla, Francois Prince, Milad Ishac, and Krystyna Gielo-Perczak. Stiffness control of balance in quiet standing. J. Neurophysiol. 80: 1211–1221, 1998
10 Morasso P, Schieppati M Can muscle stiffness alone stabilize upright standing? J. Neurophsiology 82, 1622-26, 1999
11 Tin C, Poon CS. Internal models in sensorimotor integration: perspectives from adaptive control theory. J Neural Eng. 2005 Sep;2(3):S147-63
12 Ruhe A, Fejer R, Walker B. On the relationship between pain intensity and postural sway in patients with non-specific neck pain. J Back Musculoskelet Rehabil. 2013;26(4):401-9
13 K. Michalak, P. Jaśkowski, Dimensional Complexity of Posturographic signals : I. Optimization of frequency sampling and recording time, Curr Topics in Biophys, vol. 26, no.2, pp 235-244, 2002
14 Scoppa F, Capra R, Gallamini M, Shiffer R. Clinical stabilometry standardization: basic definitions–acquisition interval–sampling frequency. Gait Posture. 2013 Feb;37(2):290-2
15 Baratto L et al La durata di registrazione nel test stabilometrico statico su piattaforma di forza Ital J Rehab Med – MR 2006;20:103-8
16 Baratto M, Cervera Ch, Jacono M Analysis of adequacy of a force platform for stabilometric clinical investigations IMEKO, IEEE, SICE 2°Int. ISHF&MCM 2004,p.207
17 Jacono M, Baratto L, Simonini M Marasso Metodologie di analisi del test di Romberg strumentale nei soggetti affetti da malattia di Parkinson SIMFER La malattia di Parkinson sett/ott 2005
18 Gallamini M, Piastra G, Porzio D, Ronchi M, Scoppa F, Bertora F. Instrumental Assessment of Balance Functional Per-formance. A Numerical Score to Discriminate Defective Subjects: A Retrospective Study J Nov Physiother 2016, 6: 305



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