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. 2018 Jun 22;15(1):54.
doi: 10.1186/s12984-018-0395-6.

Analysis of sensory system aspects of postural stability during quiet standing in adolescent idiopathic scoliosis patients

Taeyong Sim  1 , Hakje Yoo  1 , Dongjun Lee  1 , Seung-Woo Suh  2 , Jae Hyuk Yang  2 , Hyunggun Kim  3 , Joung Hwan Mun  4
Affiliations

Analysis of sensory system aspects of postural stability during quiet standing in adolescent idiopathic scoliosis patients

Taeyong Sim et al. J Neuroeng Rehabil. .

Abstract

Background: The aim of this study was to quantitatively analyze quite standing postural stability of adolescent idiopathic scoliosis (AIS) patients in respect to three sensory systems (visual, vestibular, and somatosensory).

Method: In this study, we analyzed the anterior-posterior center of pressure (CoP) signal using discrete wavelet transform (DWT) between AIS patients (n = 32) and normal controls (n = 25) during quiet standing.

Result: The energy rate (∆E EYE %) of the CoP signal was significantly higher in the AIS group than that in the control group at levels corresponding to vestibular and somatosensory systems (p < 0.01).

Conclusions: This implies that AIS patients use strategies to compensate for possible head position changes and spinal asymmetry caused by morphological deformations of the spine through vestibular and somatosensory systems. This could be interpreted that such compensation could help them maintain postural stability during quiet standing. The interpretation of CoP signal during quiet standing in AIS patients will improve our understanding of changes in physical exercise ability due to morphological deformity of the spine. This result is useful for evaluating postural stability before and after treatments (spinal fusion, bracing, rehabilitation, and so on).

Keywords: Adolescent idiopathic scoliosis (AIS); Balance; Discrete wavelet transform (DWT); Postural stability; Sensory system; Somatosensory; Vestibular; Visual.

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Conflict of interest statement

Ethics approval and consent to participate

All experimental protocol was approved by the Institutional Review Boards of Korea University Guro Hospital. All experiments were performed in accordance with relevant approved guidelines and regulations of Sungkyunkwan University.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Diagram of analysis process of CoP signal using DWT method. The level of DWT is determined by the characteristic of CoP signal and wavelet function
Fig. 2
Fig. 2
Results of the discrete decomposition of the CoP signal into 11 level low-frequency signals. This decomposition is the result of using 11 level discrete wavelet transform during quiet standing with eyes open in people without AIS. Based on level 5, open-loop and closed-loop were divided. The closed-loop (levels 6~ 10) group is divided into three sections (levels 6, 7: somatosensory (0.5~ 1.0 Hz); levels 8, 9: vestibular (0.1~ 0.5 Hz); levels 10, 11: visual (below 0.1 Hz))
Fig. 3
Fig. 3
Energy content (%) of CoP signal during quiet standing in control group. a Energy content (EEO%) for each level section with eyes open condition (b) energy content (EEC%) for each level section with eyes closed condition (c) statistical comparison of difference between EEO% and EEC% for each level section
Fig. 4
Fig. 4
Energy content (%) of CoP signal during quiet standing in AIS group. a Energy content (EEO%) for each level section with eyes open condition (b) energy content (EEC%) for each level section with eyes closed condition (c) statistical comparison of difference of EEO% and EEC% for each level section
Fig. 5
Fig. 5
Difference in energy rate (∆EEYE%) of energy contents between control and AIS groups. The energy rate of each group was obtained using energy content during quiet standing with eyes open and eyes closed
Fig. 6
Fig. 6
Difference in energy rate (∆EEYE%) of energy contents between AIS groups. The energy rate of each group classified as severity was obtained using energy content during quiet standing with eyes open and eyes closed
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