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The effect of aging on the center-of-pressure power spectrum in foam posturography
Neuroscience Letters 585 (2015) 92–97
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Short communication
The effect of aging on the center-of-pressure power spectrum in foam posturography Chisato Fujimoto a,∗ , Naoya Egami a , Shinichi Demura b , Tatsuya Yamasoba a , Shinichi Iwasaki a a b
Department of Otolaryngology, Faculty of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan Graduate School of Natural Science & Technology, Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa, Japan
h i g h l i g h t s • We assess aging effect on center-of-pressure power spectrum in foam posturography. • Especially, the eyes open/foam rubber condition highlights age-related changes. • Age-related changes were found in not only older but early-middle-aged subjects.
a r t i c l e
i n f o
Article history: Received 31 July 2014 Received in revised form 15 November 2014 Accepted 24 November 2014 Available online 26 November 2014 Keywords: Aging Posture
a b s t r a c t To assess age-related frequency-domain characteristics of the sway of center of pressure (COP) in foam posturography, two-legged stance tasks were performed by 163 controls in 4 conditions: eyes open with and without foam rubber, and eyes closed with and without foam rubber. The areas under the curve (AUCs) of power spectral density of the COP were calculated across low frequency (≥0.02 Hz and <0.1 Hz, LF-AUC), middle frequency (≥0.1 Hz and <1 Hz, MF-AUC) and high frequency (≥1 Hz and <10 Hz, HF-AUC) ranges. We categorized the controls into 7 age groups and analyzed each AUC in the 4 conditions. MFand HF-AUCs tended to show a difference between younger and older age-groups in all 4 conditions. Comparing the number of pairs in which a significant difference was shown, the condition with foam rubber, especially with eyes open, tended to highlight age-related changes. In the medial-lateral axis in the eyes open/foam rubber condition, the MF-AUC of the ≥ 75 years group was significantly larger than that of the 65–74 years group, and the MF-AUC of the 65–74 years group was significantly higher than that of the 55–64 years group, although there were no significant differences of MF-AUC among age groups under 54 years. In this condition, although HF-AUC did not change in groups over 35 years old, HF-AUC of each age group over 35 years old was significantly larger than that of the group under 24 years old. This result suggests that, in the medial-lateral axis in the eyes open/foam rubber condition, MF-AUC is specifically affected by age in late-middle-aged (ages 55–64) and older subjects, while HF-AUC is specifically affected by age in early-middle-aged (ages 35–44) subjects. © 2014 Published by Elsevier Ireland Ltd.
1. Introduction Static postural control is maintained by the integration of somatosensory, visual, and vestibular components in the central nervous system, with outputs to the musculoskeletal system [14]. As age advances, the function of all components of the postural control system declines [11]. This loss of postural control in the elderly can be a significant cause of falls [16]. Identifying
∗ Corresponding author. Tel.: +81 3 5800 8665; fax: +81 3 3814 9486. E-mail address: [email protected] (C. Fujimoto). http://dx.doi.org/10.1016/j.neulet.2014.11.033 0304-3940/© 2014 Published by Elsevier Ireland Ltd.
age-related changes in postural control is important due to the major effect of postural instability and falls on health in the elderly. Posturography is used to evaluate static postural control. It measures the position of the center of pressure (COP) that is defined as the point on the force plate surface through which the subject’s center of gravity passes. For the purpose of scrutinizing the role of different sensory inputs on static postural control, dynamic posturography using a moving platform or a foam rubber surface has been devised to allow selective manipulation of vision and somatosensation [6,18]. Our group recently reported the usefulness of posturography using a foam rubber surface, i.e., foam posturography, for assessing peripheral vestibulopathy, both in the acute and
C. Fujimoto et al. / Neuroscience Letters 585 (2015) 92–97
the chronic stages [6–9]. This system is able to detect dysfunction in both the superior and inferior vestibular nerve systems [8]. The incidence of falls increases with age, and falls in the elderly have been linked not only to intrinsic but also to extrinsic risk factors [1]. Elderly subjects have more difficulty controlling posture than young subjects when visual and proprioceptive inputs are disturbed [6,13,21]. Foam posturography has great potential as a tool to detect age-related postural change, since it can manipulate both visual and somatosensory inputs and mimic more severe extrinsic circumstances for static postural control. For the purpose of investigating postural control in greater depth, power spectral analysis of COP sway has been performed [4,19]. The analysis is a useful technique for quantifying overall variability of COP sway as well as specific components associated with pathological and/or physiological effects that cause balance disorders. It has previously been shown that elderly subjects exhibit a shift in the distribution of spectral power from higher to lower
93
frequencies in medial-lateral (ML) postural forces [15]. Power spectral analyses of COP sway in foam posturography might have the potential to identify a frequency domain that is sensitive to agerelated changes and provide an initial step towards fall prevention and the development of medical interventions for postural decline in the elderly. The purpose of this study is to investigate aging effects revealed by power spectral analysis of COP sway in foam posturography. We divided subjects by age in ten-year increments and investigated the difference in frequency-domain characteristics not only between younger and older age groups but also between relatively close age groups. 2. Material and methods We enrolled 163 healthy control subjects (84 men, 79 women) in the present study. All subjects were free from episodic vertigo/
AP,Eyes closed
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-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
*** ***
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*** *** * ** *
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0.03 0.06 0.04 0.02 0
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
Fig. 1. Box plots of LF-, MF-, and HF-AUC of the AP axis in the condition without foam rubber in each age group. * = Significant difference in nonparametric Steel–Dwass method (*p < 0.05, **p < 0.01, ***p < 0.001).
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C. Fujimoto et al. / Neuroscience Letters 585 (2015) 92–97
dizziness or any obvious neurological or orthopedic disorders, and had no medical history of a psychogenic disorder, head injury, exposure to ototoxic drugs, diabetes mellitus, hypertension or coronary artery disease. These subjects were the same as our previous report [5]. The mean age (±standard deviation), height and weight of the 163 healthy control subjects were 48.7 (±22.5) years, 160.6 (±11.9) cm and 59.4 (±11.7) kg, respectively. The study was approved by the regional ethical standards committee in the Faculty of Medicine at the University of Tokyo and the Kanazawa University Department of Education. The study was conducted according to the tenets of the Declaration of Helsinki, and informed consent was obtained from each participant. The detailed methods of foam posturography have been described previously [5,6]. Briefly, two-legged stance tasks were performed under 4 conditions: eyes open or eyes closed, with or without the foam rubber. The recording time was 60 s or until the
AP,Eyes open,Foam rubber
subject required assistance to prevent falling. We estimated the power spectrum of the acceleration signal for the anterior-posterior (AP) and the medial-lateral (ML) axis by using the maximum entropy method, as we have previously reported [5]. Briefly, the area under the curves (AUCs) of power spectral density (PSD) of the COP were calculated for each axis across three frequency ranges: ≥0.02 Hz and <0.1 Hz (low-frequency range, LF-AUC), ≥0.1 Hz and <1 Hz (middle-frequency range, MF-AUC) and ≥1 Hz and <10 Hz (high-frequency range, HF-AUC). We categorized the healthy controls into 7 groups (≤24 years, 25–34, 35–44, 45–54, 55–64, 65–74, and ≥75 years) and the nonparametric Steel–Dwass method was performed for the AUC of each frequency range of each axis in the above-mentioned 4 conditions in order to calculate statistical significances in pairs of multiplecomparisons [2,20]. A significant positive relationship was defined as having a p-value less than 0.05 in the present study.
AP,Eyes closed,Foam rubber
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-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
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-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
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*** *** *** *** *** *** *** *** *** *
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*
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-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
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*
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0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
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-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
H F-AU C (cm 2)
H F-AU C (cm 2)
0.3 0.06
0.2 0.1 0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
Fig. 2. Box plots of LF-, MF-, and HF-AUC of the AP axis in the condition with foam rubber in each age group. * = Significant difference in nonparametric Steel–Dwass method (*p < 0.05, **p < 0.01, ***p < 0.001).
C. Fujimoto et al. / Neuroscience Letters 585 (2015) 92–97
3. Results The numbers of subjects in age groups of ≤24, 25–34, 35–44, 45–54, 55–64, 65–74 and ≥75 years was 34, 19, 20, 17, 22, 27 and 24, respectively. No subjects required assistance to prevent falling during upright posture for 60 s in the 4 conditions described above. First, we assessed the frequency-domain characteristics of aging by comparison of the AUC among each age group in the AP axis (Figs. 1 and 2). For LF-AUC, there were no significant differences in any pairs of multiple-comparisons in any condition. On the other hand, in multiple-comparisons of MF- AUC and HF-AUC among each age group, older age groups showed significantly larger AUCs in comparison with younger age groups in each condition. Comparing the number of pairs in which a significant difference was shown, the condition with foam rubber, especially with eyes open, tended to highlight age-related changes in comparison with the condition without foam rubber. An aging effect in the older age groups was
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apparent in the AP axis: the value of ≥75 years group was significantly larger than that of 65–74 years group though only in MF-AUC in eyes open/foam rubber condition. We then assessed the frequency-domain characteristics of aging by comparison of the AUC among each age group in the ML axis (Figs. 3 and 4). For LF-AUC, only in the condition with eyes closed without foam rubber, was the value of the ≥75 years group significantly larger than younger age groups. On the other hand, in multiple-comparisons of MF-AUC and HF-AUC among each age group, older age groups showed larger AUCs in comparison with younger age groups in each condition. Comparing the number of pairs in which a significant difference was shown, the condition with foam rubber, especially with eyes open, tended to generate age-related changes in comparison with conditions without foam rubber. This tendency in the ML axis was similar to that found in the AP axis. In the eyes open/foam rubber condition, the MF-AUC of the ≥75 years group was significantly larger than that of the 65–74
ML, Eyes open
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-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
Fig. 3. Box plots of LF-, MF-, and HF-AUC of the ML axis in the condition without foam rubber in each age group. * = Significant difference in nonparametric Steel–Dwass method (*p < 0.05, **p < 0.01, ***p < 0.001).
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ML, Eyes open, Foam rubber
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-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
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0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
0.06
1.0
0.10 0.05 0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
Fig. 4. Box plots of LF-, MF-, and HF-AUC of the AP axis in the condition with foam rubber in each age group. * = Significant difference in nonparametric Steel–Dwass method (*p < 0.05, **p < 0.01, ***p < 0.001).
years group and the MF-AUC of the 65–74 years group was significantly higher than that of the 55–64 years group, On the other hand, there were no significant differences of MF-AUC among age groups under 54 years. MF-AUC of the ML axis in the eyes open/foam rubber condition was specifically influenced by an aging effect on static postural control in late-middle-aged (ages 55–64) and older subjects. In the eyes open/foam rubber condition, although HF-AUC did not change over 35 years old, HF-AUC of each age group over 35 years old was significantly larger than that of the <24 years age group, suggesting that HF-AUC in the ML axis in this condition was specifically influenced by changes in static postural control in the early-middle-age period (ages 35–44). 4. Discussion For LF-AUC in both the AP and ML axes, there were no significant differences in pairs in each condition between the younger and older age groups. On the other hand, for MF-AUC and HF-AUC in both axes, older age groups showed significantly larger AUCs in
comparison with younger age groups in each condition. The analyses demonstrated that disturbance of somatosensory inputs by using foam rubber tended to generate a difference in MF-AUC and HF-AUC between younger and older age group. An aging effect on postural stability could mainly be seen in the frequency component above 0.1 Hz as a result of disturbance to the somatosensory inputs. In both the AP and ML axis, the value of the ≥75 years group was significantly larger than that of the 65–74 years group in MF-AUC only in the eyes open/foam rubber condition. Additionally, only in the ML axis in the eyes open/foam rubber condition, was the MFAUC of the 65–74 years group significantly higher than that of the 55–64 years group, while there were no significant differences of MF-AUC among age groups under 54 years. Therefore, it appears that MF-AUC of the ML axis in the eyes open/foam rubber condition was specifically influenced by an aging effect on static postural control in late-middle-age and older subjects. On the other hand, in the eyes closed/foam rubber condition, no obvious differences in the AUC were found among the 55–64 years group, 65–74 years group and ≥75 years group. The eyes closed/foam rubber condition causes not only a degradation of somatosensory input but also
C. Fujimoto et al. / Neuroscience Letters 585 (2015) 92–97
an absence of visual input and makes the value of MF-AUCs larger [5]. This condition may be too physically demanding to generate a difference in postural instability among late-middle-age and older groups. For the ML axis in the eyes open/foam rubber condition, HF-AUC increased up to 35 years old but remained unchanged over 35 years old, suggesting that HF-AUC of the ML axis in the eyes open/foam rubber condition was specifically influenced by an aging effect on static postural control in the early-middle-age period. So far, little is known about the change in postural control in the early-middleage period. It has been previously reported that the differences in balance control between subjects belonging to different age categories were already apparent among young and middle-aged subjects, although these differences were small and only detected by the more accurate force platform measurements [3]. The agespecific HF-AUC change in the eyes open/foam rubber condition in the early-middle-age period might be related to an early change in plantar cutaneous sensation. In the ML axis, both MF-AUC, and HF-AUC were specifically influenced by an aging effect in the eyes open/foam rubber condition: MF-AUC in late-middle-aged and older subjects, HF-AUC in earlymiddle-aged subjects. The characteristic difference between the AP and ML axes in the frequency of COP sway during aging has been reported previously [15]. The study showed that elderly subjects exhibited a shift in the distribution of spectral power from higher (>0.5 Hz) to lower frequencies (<0.5 Hz) only in the ML axis in the eyes open condition. It is not known what causes the characteristic age-related differences frequency between the axes. A possible reason could be different movement strategies between the two axes in order to maintain stability. For the ML axis, it has been proposed that the hip strategy is commonly used in response to perturbations designed to disrupt balance [12,17]. On the other hand, for the AP axis, the main movement strategy in response to perturbations is the ankle strategy, although the hip strategy is also used [10]. Therefore, the selection of the control strategy may reflect the age-related difference between the two axes. 5. Conclusions We assessed age-related frequency-domain characteristics of the sway of COP in foam posturography, The condition with foam rubber, especially with eyes open, tended to highlight age-related changes. In the ML axis in the eyes open/foam rubber condition, MF-AUC is specifically affected by age in late-middle-aged and older subjects, while HF-AUC is specifically affected by age in earlymiddle-aged subjects. This study clarified age-related changes in the frequency-domain characteristics of postural control on postural control in two-legged stance tasks. The result may be helpful for development of research related to fall prevention and medical interventions for the postural instability in the elderly. Conflict of interest The authors declare that they have no competing interests.
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References [1] A. Bueno-Cavanillas, F. Padilla-Ruiz, J.J. Jimenez-Moleon, C.A. Peinado-Alonso, R. Galvez-Vargas, Risk factors in falls among the elderly according to extrinsic and intrinsic precipitating causes, Eur. J. Epidemiol. 16 (2000) 849–859. [2] M. Dwass, Some k-sample rank-order tests, in: I. Olkin, S.G. Ghurye, W. Hoeffding, W.G. Madow, H.B. Mann (Eds.), Contributions to Probability and Statistics, Stanford University Press, Stanford, 1960. [3] P. Era, P. Sainio, S. Koskinen, P. Haavisto, M. Vaara, A. Aromaa, Postural balance in a random sample of 7979 subjects aged 30 years and over, Gerontology 52 (2006) 204–213. [4] M. Ferdjallah, G.F. Harris, J.J. Wertsch, Instantaneous postural stability characterization using time-frequency analysis, Gait Posture 10 (1999) 129–134. [5] C. Fujimoto, T. Kamogashira, M. Kinoshita, N. Egami, K. Sugasawa, S. Demura, T. Yamasoba, S. Iwasaki, Power spectral analysis of postural sway during foam posturography in patients with peripheral vestibular dysfunction, Otol. Neurotol. 35 (2014) e317–e323. [6] C. Fujimoto, T. Murofushi, Y. Chihara, M. Ushio, K. Sugasawa, T. Yamaguchi, T. Yamasoba, S. Iwasaki, Assessment of diagnostic accuracy of foam posturography for peripheral vestibular disorders: analysis of parameters related to visual and somatosensory dependence, Clin. Neurophysiol. 120 (2009) 1408–1414. [7] C. Fujimoto, T. Murofushi, Y. Chihara, M. Ushio, M. Suzuki, T. Yamaguchi, T. Yamasoba, S. Iwasaki, Effect of severity of vestibular dysfunction on postural instability in idiopathic bilateral vestibulopathy, Acta Otolaryngol. (2013). [8] C. Fujimoto, T. Murofushi, Y. Chihara, M. Ushio, T. Yamaguchi, T. Yamasoba, S. Iwasaki, Effects of unilateral dysfunction of the inferior vestibular nerve system on postural stability, Clin. Neurophysiol. 121 (2010) 1279–1284. [9] C. Fujimoto, T. Murofushi, K. Sugasawa, Y. Chihara, M. Ushio, T. Yamasoba, S. Iwasaki, Assessment of postural stability using foam posturography at the chronic stage after acute unilateral peripheral vestibular dysfunction, Otol. Neurotol. 33 (2012) 432–436. [10] F.B. Horak, Clinical measurement of postural control in adults, Phys. Ther. 67 (1987) 1881–1885. [11] F.B. Horak, C.L. Shupert, A. Mirka, Components of postural dyscontrol in the elderly: a review, Neurobiol. Aging 10 (1989) 727–738. [12] B.E. Maki, P.J. Holliday, A.K. Topper, A prospective study of postural balance and risk of falling in an ambulatory and independent elderly population, J. Gerontol. 49 (1994) M72–M84. [13] D. Manchester, M. Woollacott, N. Zederbauer-Hylton, O. Marin, Visual, vestibular and somatosensory contributions to balance control in the older adult, J. Gerontol. 44 (1989) M118–127. [14] J. Massion, M. Woollacott, Posture and equilibrium, in: T. Bronstein, M. Brandt (Eds.), Clinical Disorders of Balance, Posture and Gait, Arnold, London, 2004, pp. 1–19. [15] B.A. McClenaghan, H.G. Williams, J. Dickerson, M. Dowda, L. Thombs, P. Eleazer, Spectral characteristics of aging postural control, Gait Posture 4 (1996) 112–121. [16] L.V. Moncada, Management of falls in older persons: a prescription for prevention, Am. Fam. Physician 84 (2011) 1267–1276. [17] S. Moore, D. Rushmer, S. Windus, L. Nashner, Human automatic postural responses: responses to horizontal perturbations of stance in multiple directions, Exp. Brain Res. 73 (1988) 648–658. [18] L.M. Nashner, F.O. Black, C. Wall, Adaptation to altered support and visual conditions during stance – patients with vestibular deficits, J. Neurosci. 2 (1982) 536–544. [19] R.W. Soames, J. Atha, The spectral characteristics of postural sway behaviour, Eur. J. Appl. Physiol. Occup. Physiol. 49 (1982) 169–177. [20] R.G.D. Steel, A rank sum test for comparing all pairs of treatments, Technometrics 2 (1960) 197–207. [21] M.H. Woollacott, A. Shumway-Cook, L.M. Nashner, Aging and posture control: changes in sensory organization and muscular coordination, Int. J. Aging Hum. 23 (1986) 97–114.
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Short communication
The effect of aging on the center-of-pressure power spectrum in foam posturography Chisato Fujimoto a,∗ , Naoya Egami a , Shinichi Demura b , Tatsuya Yamasoba a , Shinichi Iwasaki a a b
Department of Otolaryngology, Faculty of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan Graduate School of Natural Science & Technology, Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa, Japan
h i g h l i g h t s • We assess aging effect on center-of-pressure power spectrum in foam posturography. • Especially, the eyes open/foam rubber condition highlights age-related changes. • Age-related changes were found in not only older but early-middle-aged subjects.
a r t i c l e
i n f o
Article history: Received 31 July 2014 Received in revised form 15 November 2014 Accepted 24 November 2014 Available online 26 November 2014 Keywords: Aging Posture
a b s t r a c t To assess age-related frequency-domain characteristics of the sway of center of pressure (COP) in foam posturography, two-legged stance tasks were performed by 163 controls in 4 conditions: eyes open with and without foam rubber, and eyes closed with and without foam rubber. The areas under the curve (AUCs) of power spectral density of the COP were calculated across low frequency (≥0.02 Hz and <0.1 Hz, LF-AUC), middle frequency (≥0.1 Hz and <1 Hz, MF-AUC) and high frequency (≥1 Hz and <10 Hz, HF-AUC) ranges. We categorized the controls into 7 age groups and analyzed each AUC in the 4 conditions. MFand HF-AUCs tended to show a difference between younger and older age-groups in all 4 conditions. Comparing the number of pairs in which a significant difference was shown, the condition with foam rubber, especially with eyes open, tended to highlight age-related changes. In the medial-lateral axis in the eyes open/foam rubber condition, the MF-AUC of the ≥ 75 years group was significantly larger than that of the 65–74 years group, and the MF-AUC of the 65–74 years group was significantly higher than that of the 55–64 years group, although there were no significant differences of MF-AUC among age groups under 54 years. In this condition, although HF-AUC did not change in groups over 35 years old, HF-AUC of each age group over 35 years old was significantly larger than that of the group under 24 years old. This result suggests that, in the medial-lateral axis in the eyes open/foam rubber condition, MF-AUC is specifically affected by age in late-middle-aged (ages 55–64) and older subjects, while HF-AUC is specifically affected by age in early-middle-aged (ages 35–44) subjects. © 2014 Published by Elsevier Ireland Ltd.
1. Introduction Static postural control is maintained by the integration of somatosensory, visual, and vestibular components in the central nervous system, with outputs to the musculoskeletal system [14]. As age advances, the function of all components of the postural control system declines [11]. This loss of postural control in the elderly can be a significant cause of falls [16]. Identifying
∗ Corresponding author. Tel.: +81 3 5800 8665; fax: +81 3 3814 9486. E-mail address: [email protected] (C. Fujimoto). http://dx.doi.org/10.1016/j.neulet.2014.11.033 0304-3940/© 2014 Published by Elsevier Ireland Ltd.
age-related changes in postural control is important due to the major effect of postural instability and falls on health in the elderly. Posturography is used to evaluate static postural control. It measures the position of the center of pressure (COP) that is defined as the point on the force plate surface through which the subject’s center of gravity passes. For the purpose of scrutinizing the role of different sensory inputs on static postural control, dynamic posturography using a moving platform or a foam rubber surface has been devised to allow selective manipulation of vision and somatosensation [6,18]. Our group recently reported the usefulness of posturography using a foam rubber surface, i.e., foam posturography, for assessing peripheral vestibulopathy, both in the acute and
C. Fujimoto et al. / Neuroscience Letters 585 (2015) 92–97
the chronic stages [6–9]. This system is able to detect dysfunction in both the superior and inferior vestibular nerve systems [8]. The incidence of falls increases with age, and falls in the elderly have been linked not only to intrinsic but also to extrinsic risk factors [1]. Elderly subjects have more difficulty controlling posture than young subjects when visual and proprioceptive inputs are disturbed [6,13,21]. Foam posturography has great potential as a tool to detect age-related postural change, since it can manipulate both visual and somatosensory inputs and mimic more severe extrinsic circumstances for static postural control. For the purpose of investigating postural control in greater depth, power spectral analysis of COP sway has been performed [4,19]. The analysis is a useful technique for quantifying overall variability of COP sway as well as specific components associated with pathological and/or physiological effects that cause balance disorders. It has previously been shown that elderly subjects exhibit a shift in the distribution of spectral power from higher to lower
93
frequencies in medial-lateral (ML) postural forces [15]. Power spectral analyses of COP sway in foam posturography might have the potential to identify a frequency domain that is sensitive to agerelated changes and provide an initial step towards fall prevention and the development of medical interventions for postural decline in the elderly. The purpose of this study is to investigate aging effects revealed by power spectral analysis of COP sway in foam posturography. We divided subjects by age in ten-year increments and investigated the difference in frequency-domain characteristics not only between younger and older age groups but also between relatively close age groups. 2. Material and methods We enrolled 163 healthy control subjects (84 men, 79 women) in the present study. All subjects were free from episodic vertigo/
AP,Eyes closed
AP,Eyes open 1.6
1.2
1.4
1.0
1.0
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0.8
LF-AU C (cm 2)
LF-AU C (cm 2)
1.2 0.8
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0.6 0.4 0.2 0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
*** ***
0.5 ** 0.4
*
*
0.6
**
**
*
0.5 0.4 M F-AU C (cm 2 )
M F-AU C (cm 2 )
0.3 0.2 0.1 0
0.04
*
0.2 0.1 0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
0.05
0.3
*** *** * ** *
0.12
** **
*
0.10 0.08
0.02 0.01 0
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
H F-AU C (cm 2)
H F-AU C (cm 2)
0.03 0.06 0.04 0.02 0
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
Fig. 1. Box plots of LF-, MF-, and HF-AUC of the AP axis in the condition without foam rubber in each age group. * = Significant difference in nonparametric Steel–Dwass method (*p < 0.05, **p < 0.01, ***p < 0.001).
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dizziness or any obvious neurological or orthopedic disorders, and had no medical history of a psychogenic disorder, head injury, exposure to ototoxic drugs, diabetes mellitus, hypertension or coronary artery disease. These subjects were the same as our previous report [5]. The mean age (±standard deviation), height and weight of the 163 healthy control subjects were 48.7 (±22.5) years, 160.6 (±11.9) cm and 59.4 (±11.7) kg, respectively. The study was approved by the regional ethical standards committee in the Faculty of Medicine at the University of Tokyo and the Kanazawa University Department of Education. The study was conducted according to the tenets of the Declaration of Helsinki, and informed consent was obtained from each participant. The detailed methods of foam posturography have been described previously [5,6]. Briefly, two-legged stance tasks were performed under 4 conditions: eyes open or eyes closed, with or without the foam rubber. The recording time was 60 s or until the
AP,Eyes open,Foam rubber
subject required assistance to prevent falling. We estimated the power spectrum of the acceleration signal for the anterior-posterior (AP) and the medial-lateral (ML) axis by using the maximum entropy method, as we have previously reported [5]. Briefly, the area under the curves (AUCs) of power spectral density (PSD) of the COP were calculated for each axis across three frequency ranges: ≥0.02 Hz and <0.1 Hz (low-frequency range, LF-AUC), ≥0.1 Hz and <1 Hz (middle-frequency range, MF-AUC) and ≥1 Hz and <10 Hz (high-frequency range, HF-AUC). We categorized the healthy controls into 7 groups (≤24 years, 25–34, 35–44, 45–54, 55–64, 65–74, and ≥75 years) and the nonparametric Steel–Dwass method was performed for the AUC of each frequency range of each axis in the above-mentioned 4 conditions in order to calculate statistical significances in pairs of multiplecomparisons [2,20]. A significant positive relationship was defined as having a p-value less than 0.05 in the present study.
AP,Eyes closed,Foam rubber
1.4
3.0
1.2
2.5
1.0
2.0
LF-AU C (cm 2 )
LF-AU C (cm 2)
0.8 0.6 0.4 0.2 0
1.5 1.0 0.5 0
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
1.4 1.2 1.0
*
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
*** ***
*** *** *** *** *** *** *** *** *** *
2.5 2.0
**
*
1.0
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0.2 0
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0.08
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M F-AU C (cm 2)
0.6 0.4
0.10
*
*
1.5
0.8
0.12
*** *** **
*
*** *** ** *** *** ** *** *
0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
0.5 0.4
*** ** *** *** ** *** **
0.04 0.02 0
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
H F-AU C (cm 2)
H F-AU C (cm 2)
0.3 0.06
0.2 0.1 0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
Fig. 2. Box plots of LF-, MF-, and HF-AUC of the AP axis in the condition with foam rubber in each age group. * = Significant difference in nonparametric Steel–Dwass method (*p < 0.05, **p < 0.01, ***p < 0.001).
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3. Results The numbers of subjects in age groups of ≤24, 25–34, 35–44, 45–54, 55–64, 65–74 and ≥75 years was 34, 19, 20, 17, 22, 27 and 24, respectively. No subjects required assistance to prevent falling during upright posture for 60 s in the 4 conditions described above. First, we assessed the frequency-domain characteristics of aging by comparison of the AUC among each age group in the AP axis (Figs. 1 and 2). For LF-AUC, there were no significant differences in any pairs of multiple-comparisons in any condition. On the other hand, in multiple-comparisons of MF- AUC and HF-AUC among each age group, older age groups showed significantly larger AUCs in comparison with younger age groups in each condition. Comparing the number of pairs in which a significant difference was shown, the condition with foam rubber, especially with eyes open, tended to highlight age-related changes in comparison with the condition without foam rubber. An aging effect in the older age groups was
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apparent in the AP axis: the value of ≥75 years group was significantly larger than that of 65–74 years group though only in MF-AUC in eyes open/foam rubber condition. We then assessed the frequency-domain characteristics of aging by comparison of the AUC among each age group in the ML axis (Figs. 3 and 4). For LF-AUC, only in the condition with eyes closed without foam rubber, was the value of the ≥75 years group significantly larger than younger age groups. On the other hand, in multiple-comparisons of MF-AUC and HF-AUC among each age group, older age groups showed larger AUCs in comparison with younger age groups in each condition. Comparing the number of pairs in which a significant difference was shown, the condition with foam rubber, especially with eyes open, tended to generate age-related changes in comparison with conditions without foam rubber. This tendency in the ML axis was similar to that found in the AP axis. In the eyes open/foam rubber condition, the MF-AUC of the ≥75 years group was significantly larger than that of the 65–74
ML, Eyes open
ML, Eyes closed
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*
*
0.8 LF-AU C (cm 2)
LF-AU C (cm 2)
0.6 0.4 0.2 0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years) *** *** **
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*
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M F-AU C (cm 2 )
0
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H F-AU C (cm 2)
H F-AU C (cm 2)
0.03 0.10 0.05 0
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
Fig. 3. Box plots of LF-, MF-, and HF-AUC of the ML axis in the condition without foam rubber in each age group. * = Significant difference in nonparametric Steel–Dwass method (*p < 0.05, **p < 0.01, ***p < 0.001).
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ML, Eyes open, Foam rubber
ML, Eyes closed, Foam r ubber 1.2
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*** *** *** *** *** ** *** *** ** *
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0
** **
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*
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* *
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M F-AU C (cm 2)
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0.08
***
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* *
*
*
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*
0.15 0.04 0.02 0
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
H F-AU C (cm 2)
H F-AU C (cm 2)
0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
-24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
0.06
1.0
0.10 0.05 0 -24 25- 35- 45- 55- 65- 7534 44 54 64 74 Age (years)
Fig. 4. Box plots of LF-, MF-, and HF-AUC of the AP axis in the condition with foam rubber in each age group. * = Significant difference in nonparametric Steel–Dwass method (*p < 0.05, **p < 0.01, ***p < 0.001).
years group and the MF-AUC of the 65–74 years group was significantly higher than that of the 55–64 years group, On the other hand, there were no significant differences of MF-AUC among age groups under 54 years. MF-AUC of the ML axis in the eyes open/foam rubber condition was specifically influenced by an aging effect on static postural control in late-middle-aged (ages 55–64) and older subjects. In the eyes open/foam rubber condition, although HF-AUC did not change over 35 years old, HF-AUC of each age group over 35 years old was significantly larger than that of the <24 years age group, suggesting that HF-AUC in the ML axis in this condition was specifically influenced by changes in static postural control in the early-middle-age period (ages 35–44). 4. Discussion For LF-AUC in both the AP and ML axes, there were no significant differences in pairs in each condition between the younger and older age groups. On the other hand, for MF-AUC and HF-AUC in both axes, older age groups showed significantly larger AUCs in
comparison with younger age groups in each condition. The analyses demonstrated that disturbance of somatosensory inputs by using foam rubber tended to generate a difference in MF-AUC and HF-AUC between younger and older age group. An aging effect on postural stability could mainly be seen in the frequency component above 0.1 Hz as a result of disturbance to the somatosensory inputs. In both the AP and ML axis, the value of the ≥75 years group was significantly larger than that of the 65–74 years group in MF-AUC only in the eyes open/foam rubber condition. Additionally, only in the ML axis in the eyes open/foam rubber condition, was the MFAUC of the 65–74 years group significantly higher than that of the 55–64 years group, while there were no significant differences of MF-AUC among age groups under 54 years. Therefore, it appears that MF-AUC of the ML axis in the eyes open/foam rubber condition was specifically influenced by an aging effect on static postural control in late-middle-age and older subjects. On the other hand, in the eyes closed/foam rubber condition, no obvious differences in the AUC were found among the 55–64 years group, 65–74 years group and ≥75 years group. The eyes closed/foam rubber condition causes not only a degradation of somatosensory input but also
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an absence of visual input and makes the value of MF-AUCs larger [5]. This condition may be too physically demanding to generate a difference in postural instability among late-middle-age and older groups. For the ML axis in the eyes open/foam rubber condition, HF-AUC increased up to 35 years old but remained unchanged over 35 years old, suggesting that HF-AUC of the ML axis in the eyes open/foam rubber condition was specifically influenced by an aging effect on static postural control in the early-middle-age period. So far, little is known about the change in postural control in the early-middleage period. It has been previously reported that the differences in balance control between subjects belonging to different age categories were already apparent among young and middle-aged subjects, although these differences were small and only detected by the more accurate force platform measurements [3]. The agespecific HF-AUC change in the eyes open/foam rubber condition in the early-middle-age period might be related to an early change in plantar cutaneous sensation. In the ML axis, both MF-AUC, and HF-AUC were specifically influenced by an aging effect in the eyes open/foam rubber condition: MF-AUC in late-middle-aged and older subjects, HF-AUC in earlymiddle-aged subjects. The characteristic difference between the AP and ML axes in the frequency of COP sway during aging has been reported previously [15]. The study showed that elderly subjects exhibited a shift in the distribution of spectral power from higher (>0.5 Hz) to lower frequencies (<0.5 Hz) only in the ML axis in the eyes open condition. It is not known what causes the characteristic age-related differences frequency between the axes. A possible reason could be different movement strategies between the two axes in order to maintain stability. For the ML axis, it has been proposed that the hip strategy is commonly used in response to perturbations designed to disrupt balance [12,17]. On the other hand, for the AP axis, the main movement strategy in response to perturbations is the ankle strategy, although the hip strategy is also used [10]. Therefore, the selection of the control strategy may reflect the age-related difference between the two axes. 5. Conclusions We assessed age-related frequency-domain characteristics of the sway of COP in foam posturography, The condition with foam rubber, especially with eyes open, tended to highlight age-related changes. In the ML axis in the eyes open/foam rubber condition, MF-AUC is specifically affected by age in late-middle-aged and older subjects, while HF-AUC is specifically affected by age in earlymiddle-aged subjects. This study clarified age-related changes in the frequency-domain characteristics of postural control on postural control in two-legged stance tasks. The result may be helpful for development of research related to fall prevention and medical interventions for the postural instability in the elderly. Conflict of interest The authors declare that they have no competing interests.
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References [1] A. Bueno-Cavanillas, F. Padilla-Ruiz, J.J. Jimenez-Moleon, C.A. Peinado-Alonso, R. Galvez-Vargas, Risk factors in falls among the elderly according to extrinsic and intrinsic precipitating causes, Eur. J. Epidemiol. 16 (2000) 849–859. [2] M. Dwass, Some k-sample rank-order tests, in: I. Olkin, S.G. Ghurye, W. Hoeffding, W.G. Madow, H.B. Mann (Eds.), Contributions to Probability and Statistics, Stanford University Press, Stanford, 1960. [3] P. Era, P. Sainio, S. Koskinen, P. Haavisto, M. Vaara, A. Aromaa, Postural balance in a random sample of 7979 subjects aged 30 years and over, Gerontology 52 (2006) 204–213. [4] M. Ferdjallah, G.F. Harris, J.J. Wertsch, Instantaneous postural stability characterization using time-frequency analysis, Gait Posture 10 (1999) 129–134. [5] C. Fujimoto, T. Kamogashira, M. Kinoshita, N. Egami, K. Sugasawa, S. Demura, T. Yamasoba, S. Iwasaki, Power spectral analysis of postural sway during foam posturography in patients with peripheral vestibular dysfunction, Otol. Neurotol. 35 (2014) e317–e323. [6] C. Fujimoto, T. Murofushi, Y. Chihara, M. Ushio, K. Sugasawa, T. Yamaguchi, T. Yamasoba, S. Iwasaki, Assessment of diagnostic accuracy of foam posturography for peripheral vestibular disorders: analysis of parameters related to visual and somatosensory dependence, Clin. Neurophysiol. 120 (2009) 1408–1414. [7] C. Fujimoto, T. Murofushi, Y. Chihara, M. Ushio, M. Suzuki, T. Yamaguchi, T. Yamasoba, S. Iwasaki, Effect of severity of vestibular dysfunction on postural instability in idiopathic bilateral vestibulopathy, Acta Otolaryngol. (2013). [8] C. Fujimoto, T. Murofushi, Y. Chihara, M. Ushio, T. Yamaguchi, T. Yamasoba, S. Iwasaki, Effects of unilateral dysfunction of the inferior vestibular nerve system on postural stability, Clin. Neurophysiol. 121 (2010) 1279–1284. [9] C. Fujimoto, T. Murofushi, K. Sugasawa, Y. Chihara, M. Ushio, T. Yamasoba, S. Iwasaki, Assessment of postural stability using foam posturography at the chronic stage after acute unilateral peripheral vestibular dysfunction, Otol. Neurotol. 33 (2012) 432–436. [10] F.B. Horak, Clinical measurement of postural control in adults, Phys. Ther. 67 (1987) 1881–1885. [11] F.B. Horak, C.L. Shupert, A. Mirka, Components of postural dyscontrol in the elderly: a review, Neurobiol. Aging 10 (1989) 727–738. [12] B.E. Maki, P.J. Holliday, A.K. Topper, A prospective study of postural balance and risk of falling in an ambulatory and independent elderly population, J. Gerontol. 49 (1994) M72–M84. [13] D. Manchester, M. Woollacott, N. Zederbauer-Hylton, O. Marin, Visual, vestibular and somatosensory contributions to balance control in the older adult, J. Gerontol. 44 (1989) M118–127. [14] J. Massion, M. Woollacott, Posture and equilibrium, in: T. Bronstein, M. Brandt (Eds.), Clinical Disorders of Balance, Posture and Gait, Arnold, London, 2004, pp. 1–19. [15] B.A. McClenaghan, H.G. Williams, J. Dickerson, M. Dowda, L. Thombs, P. Eleazer, Spectral characteristics of aging postural control, Gait Posture 4 (1996) 112–121. [16] L.V. Moncada, Management of falls in older persons: a prescription for prevention, Am. Fam. Physician 84 (2011) 1267–1276. [17] S. Moore, D. Rushmer, S. Windus, L. Nashner, Human automatic postural responses: responses to horizontal perturbations of stance in multiple directions, Exp. Brain Res. 73 (1988) 648–658. [18] L.M. Nashner, F.O. Black, C. Wall, Adaptation to altered support and visual conditions during stance – patients with vestibular deficits, J. Neurosci. 2 (1982) 536–544. [19] R.W. Soames, J. Atha, The spectral characteristics of postural sway behaviour, Eur. J. Appl. Physiol. Occup. Physiol. 49 (1982) 169–177. [20] R.G.D. Steel, A rank sum test for comparing all pairs of treatments, Technometrics 2 (1960) 197–207. [21] M.H. Woollacott, A. Shumway-Cook, L.M. Nashner, Aging and posture control: changes in sensory organization and muscular coordination, Int. J. Aging Hum. 23 (1986) 97–114.