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Abstrakty
Peripheral diabetic neuropathy (PDN) is a complication of type 2 diabetes (T2DM) that impairs posture control and increases the risk of falling. The aim of this study was to characterize the anteroposterior center of pressure (COP-AP) in the time and the frequency domains in the T2DM/PDN group in relation to the control group. To that end we: (1) evaluated the efficacy of using both linear and non-linear discrete wavelet transform (DWT) analyses to evaluate oscillation patterns in the anteroposterior center of pressure (COP-AP) in the bipedal position in terms of time and frequency and (2) established input parameters for a model for predicting the risk of falling. This study included an experimental sample of 30 people with T2DM/PDN matched by gender, age, weight and height with a control sample of 30 healthy individuals. Unreported techniques for analyzing the COP-AP literature were assessed for their capacity to model patient bodily stability in the proprioceptive, visual and vestibular systems. To measure COP-AP, five tests were performed under different conditions as outlined in the Romberg Test using the ‘‘PEDAR System’’ for measuring plantar pressure. DWTs were used to calculate excursion parameters, average speeds, range, RMS values, the average maximum and minimum amplitude, power spectral densities and energy percentages in 11 frequency bands (D1 to D10 and A10). There were significant differences between the two study groups in terms of the calculated linear parameters ( p < 0.05). Using linear and non-linear DWT analyses, a preliminary characterization of COP-AP patterns was achieved. DWT could be used alongside linear analysis to determine the effect changes in these systems have on postural oscillation in people with T2DM.
Wydawca
Czasopismo
Rocznik
Tom
Strony
306--315
Opis fizyczny
Bibliogr. 36 poz., rys., tab., wykr.
Twórcy
- Pontificia Universidad Javeriana, Faculty of Engineering, Electronics Department, FootLab-BASPI Research Laboratory, Research Group in Bioengineering, Signal Analysis and Image Processing, Bogotá, Colombia
autor
- Pontificia Universidad Javeriana, Faculty of Engineering, Electronics Department, FootLab-BASPI Research Laboratory, Research Group in Bioengineering, Signal Analysis and Image Processing, Cra. 7 No. 40-62, Bogotá, Colombia
- Pontificia Universidad Javeriana, Faculty of Engineering, Electronics Department, FootLab-BASPI Research Laboratory, Research Group in Bioengineering, Signal Analysis and Image Processing, Bogotá, Colombia
Bibliografia
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- [3] Vargas-Uricoechea H, Casas-Figueroa LÁ. An epidemiologic analysis of diabetes in Colombia. Ann Glob Heal 2015;81(6):742–53.
- [4] Vinik AI, Vinik EJ, Colberg SR, Morrison S. Falls risk in older adults with type 2 diabetes. Clin Geriatr Med 2015;31(1):89–99.
- [5] Morrison S, Colberg SR, Parson HK, Vinik AI. Relation between risk of falling and postural sway complexity in diabetes. Gait Posture 2012;35(4):662–8.
- [6] Dixit S, Maiya A. Diabetic peripheral neuropathy and its evaluation in a clinical scenario: a review. J Postgrad Med 2014;60(1):33–40.
- [7] Kukidome D, Nishikawa T, Sato M, Nishi Y, Shimamura R, Kawashima J, et al. Impaired balance is related to the progression of diabetic complications in both young and older adults. J Diabetes Complications 2017;31(8):1275–82.
- [8] Toloza D, Zequera M. Linear and non-linear methods for analysis center pressure and its application in diabetic peripheral neuropathy: a systematic review. IFMBE Proc 2017;60:713–6.
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- [22] Wickstrom J, Stergiou N, Kyvelidou A. Reliability of center of pressure measures for assessing the development of sitting postural control through the stages of sitting. Gait Posture 2017;56:8–13.
- [23] Toosizadeh N, Mohler J, Armstrong DG, Talal TK, Najafi B. The influence of diabetic peripheral neuropathy on local postural muscle and central sensory feedback balance control. PLOS ONE 2015;10(8):1–12.
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- [31] Cavanagh PR, Simoneau GG, Ulbrecht JS. Ulceration, unsteadiness, and uncertainty: the biomechanical consequences of diabetes mellitus. J Biomech 1993;26(suppl. 1):23–40.
- [32] Ferdjallah M, Harris GF, Wertsch JJ. Instantaneous spectral characteristics of postural stability using time-frequency analysis. Annual International Conference of the IEEE Engineering in Medicine and Biology – Proceedings, vol. 4;1997. p. 1675–8.
- [33] Oppenheim U, Kohen-Raz R, Alex D, Kohen-Raz A, Azarya M. Postural characteristics of diabetic neuropathy. Diabetes Care 1999;22(2):328–32.
- [34] Loughlin PJ, Redfern MS. Spectral characteristics of visually induced postural sway in healthy elderly and healthy young subjects. IEEE Trans Neural Syst Rehabil Eng 2001;9(1):24–30.
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- [36] Peterka RJ. Sensorimotor integration in human postural control. J Neurophysiol 2002;88(3):1097–118.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bd7f77a3-e109-44ab-8326-acce8ed13149