Influence of Age on Postconcussive Postural Control Measures and Future Implications for Assessment

Hugentobler, Jason; Gupta, Rahul; Slater, Robert; Paterno, Mark V.; Riley, Michael A.; Quatman‐Yates, Catherine

doi:10.1097/jsm.0000000000000286

Cited by 18 publications

(16 citation statements)

References 36 publications

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“…Addressing the choice of parameters ( r , m ), Yentes et al found m = 2 to be optimal for gait and theoretical data [ 10 ]. Postural control studies typically utilized either m = 2 (e.g., [ 5 , 9 , 11 ]) or m = 3 (e.g., [ 4 , 6 , 8 ]). Yentes et al also suggested that, for gait data, the radius of similarity should be examined per the experimental conditions.…”

Section: Introductionmentioning

confidence: 99%

“…When it comes to SampEn, however, it has been suggested that a traditional filter may smooth out the unique features of the time series [ 19 , 20 ]. The literature is diverse here as well with several studies applying a filter [ 4 – 6 ], others applying down-sampling techniques [ 7 , 11 , 21 ] and others analyzing the original data set [ 8 , 9 ]. These differences in data processing techniques have been shown to impact the value of SampEn, especially following down-sampling to 25 Hz or when SampEn was derived from differenced data [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

“…The risk of detrending, however, is the possibility of removing part of the dynamics of the signal [ 20 ]. With that, several studies have chosen to calculate SampEn for the original COP position time-series [ 8 , 11 , 21 ]. Better understanding of what each of these procedures does to the signal and how it affects the SampEn outcome may lead to improved consistency across postural control research.…”

Section: Introductionmentioning

confidence: 99%

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On the effects of signal processing on sample entropy for postural control

2018

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Sample entropy, a measure of time series regularity, has become increasingly popular in postural control research. We are developing a virtual reality assessment of sensory integration for postural control in people with vestibular dysfunction and wished to apply sample entropy as an outcome measure. However, despite the common use of sample entropy to quantify postural sway, we found lack of consistency in the literature regarding center-of-pressure signal manipulations prior to the computation of sample entropy. We therefore wished to investigate the effect of parameters choice and signal processing on participants’ sample entropy outcome. For that purpose, we compared center-of-pressure sample entropy data between patients with vestibular dysfunction and age-matched controls. Within our assessment, participants observed virtual reality scenes, while standing on floor or a compliant surface. We then analyzed the effect of: modification of the radius of similarity (r) and the embedding dimension (m); down-sampling or filtering and differencing or detrending. When analyzing the raw center-of-pressure data, we found a significant main effect of surface in medio-lateral and anterior-posterior directions across r’s and m’s. We also found a significant interaction group × surface in the medio-lateral direction when r was 0.05 or 0.1 with a monotonic increase in p value with increasing r in both m’s. These effects were maintained with down-sampling by 2, 3, and 4 and with detrending but not with filtering and differencing. Based on these findings, we suggest that for sample entropy to be compared across postural control studies, there needs to be increased consistency, particularly of signal handling prior to the calculation of sample entropy. Procedures such as filtering, differencing or detrending affect sample entropy values and could artificially alter the time series pattern. Therefore, if such procedures are performed they should be well justified.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On the effects of signal processing on sample entropy for postural control

2018

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“…Whilst this enabled a direct comparison with the most-common clinician scoring system, it did not allow us to elucidate effects of time on the structure of the COP signal. COP movement is known to exhibit non-stationary characteristics (Carroll and Freedman, 1993) There are known effects of age on postural control COP metrics in both the time domain and the frequency domain (Barozzi et al, 2014;Gouleme et al, 2014;Hugentobler et al, 2016;Quatman-Yates et al, 2018;Singh et al, 2012;Williams et al, 1997) so the spectra and summary statistics presented here should not be generalised to groups of different ages (e.g. young children or older adults).…”

Section: Discussionmentioning

confidence: 99%

The use of continuous spectral analysis for the assessment of postural stability changes after sports-related concussion

Daniels

Henderson

Strike

et al. 2019

Journal of Biomechanics

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“…Increased total length indicates the decreased ability of postural control. 24,26 Total length per unit area reflects minute postural adjustments controlled by the spinal proprioceptive reflex of the lower extremities. It indicates the fine control of posture by proprioceptive reflexes.…”

Section: Effect Of Teeth Clenching On Dynamic Balancementioning

confidence: 99%

The Effect of Teeth Clenching on Dynamic Balance at Jump-Landing: A Pilot Study

Nakamura

Yoshida

Churei

et al. 2017

Journal of Applied Biomechanics

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The aim of this study was to analyze the effect of teeth clenching on dynamic balance at jump landing. Twenty-five healthy subjects performed jump-landing tasks with or without teeth clenching. The first 3 trials were performed with no instruction; subsequently, subjects were ordered to clench at the time of landing in the following 3 trials. We collected the data of masseter muscle activity by electromyogram, the maximum vertical ground reaction force (vGRFmax) and center of pressure (CoP) parameters by force plate during jump-landing. According to the clenching status of control jump-landing, all participants were categorized into a spontaneous clenching group and no clenching group, and the CoP data were compared. The masseter muscle activity was correlated with vGRFmax during anterior jump-landing, while it was not correlated with CoP. In comparisons between the spontaneous clenching and the no clenching group during anterior jump-landing, the spontaneous clenching group showed harder landing and the CoP area became larger than the no clenching group. There were no significant differences between pre-and postintervention in both spontaneous clenching and no clenching groups. The effect of teeth clenching on dynamic balance during jump-landing was limited.Keywords: dynamic balance, teeth clenching, ground reaction force, center of pressure, electromyogramTeeth clenching is performed in a voluntary manner by the contraction of mandibular muscles. These muscles receive innervation from the motor area of the cerebral cortex, the same as skeletal muscles of the limbs.1 Recently, it has been reported that chewing activity has a positive effect on attention, mood improvement, and stress relief.2,3 Moreover, positive correlation between muscle strength of the skeletal muscles and teeth clenching was reported. Sasaki et al 4 reported that teeth clenching force had a positive correlation with isometric gastrocnemius muscle strength. A number of studies have demonstrated that voluntary teeth clenching facilitated the H-reflex in both the agonist and antagonist muscles of the lower limb, [5][6][7][8][9] suggesting that teeth clenching contributed to stabilization of body orientation by strengthening the skeletal muscles of the limb.There were also several reports that confirmed the oral motor activity relations on postural control, 10-15 revealing the superior effect of teeth clenching on body balance control against body sway. However, these pieces of research were subjected to static balance, and there were few reports that investigated the effect of teeth clenching on dynamic balance.Stabilization of dynamic balance is important for sport activity and injury prevention. Although the effects of teeth clenching on sport performance and injury prevention were investigated in several pieces of research, 16-18 they remain controversial. Additionally, the subsequent occlusion status (presence and force of teeth clenching) in various sports is also unknown. In this study, we investigated the occlusion status and the effect ...

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Influence of Age on Postconcussive Postural Control Measures and Future Implications for Assessment

Abstract: This study demonstrates that age is a critical factor that needs to be accounted for to improve the clinical appropriateness and utility of current postconcussion postural control assessments.

Cited by 18 publications

References 36 publications

On the effects of signal processing on sample entropy for postural control

On the effects of signal processing on sample entropy for postural control

The use of continuous spectral analysis for the assessment of postural stability changes after sports-related concussion

The Effect of Teeth Clenching on Dynamic Balance at Jump-Landing: A Pilot Study

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