Gait Variability Measures Reveal Differences Between Multiple Sclerosis Patients and Healthy Controls

Kaipust, Jeffrey P.; Huisinga, Jessie M.; Filipi, Mary L.; Stergiou, Nicholas

doi:10.1123/mcj.16.2.229

Cited by 89 publications

(65 citation statements)

References 57 publications

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“…Regarding the MS population, previous reports have clearly shown that PwMS have greater gait variability, demonstrated in short [27,28] and long distance walks [29]. Moreover, increased gait variability has clinical significance in PwMS.…”

Section: Discussionmentioning

confidence: 95%

The “butterfly diagram”: A gait marker for neurological and cerebellar impairment in people with multiple sclerosis

Kalron

Frid

2015

Journal of the Neurological Sciences

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Section: Discussionmentioning

confidence: 95%

The “butterfly diagram”: A gait marker for neurological and cerebellar impairment in people with multiple sclerosis

Kalron

Frid

2015

Journal of the Neurological Sciences

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“…Increases in gait variability are indicative of impairment in control of gait (Hausdorff, 2005;Balasubramanian et al, 2009;Kaipust et al, 2012a). The increased gait variability during the course of the 6MW indicates that individuals with MS who require assistance while walking have a further decline in the control of walking during the 6MW.…”

Section: Discussionmentioning

confidence: 97%

“…There is growing evidence that variability in spatiotemporal parameters of walking provides unique information on walking and the health of the neuromuscular system (Hausdorff, 2005;Brach et al, 2007;Myers et al, 2010;Kaipust et al, 2012a). Recently, it has been demonstrated that individuals with MS who have minimal disability have elevated gait variability compared with healthy controls and that gait variability scales with disability (Socie et al, 2012a).…”

mentioning

confidence: 97%

Examination of spatiotemporal gait parameters during the 6-min walk in individuals with multiple sclerosis

Socie¹,

Motl

Sosnoff

2014

International Journal of Rehabilitation Research

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This investigation examined spatiotemporal parameters of gait during the 6-min walk (6MW) in individuals with multiple sclerosis (MS) and in healthy controls. Eighteen individuals with MS [divided into those who were independently ambulatory (n=10) and those who were ambulatory with assistance (n=8)] and 10 healthy controls performed a 6MW while recording spatiotemporal gait parameters using a pressure-sensitive walkway. Parameters recorded were walking velocity, cadence, step length and width, step time, percent of the gait cycle in double support, and variability of step length and width, step time, and double support. The ambulatory with assistance MS group had a significantly greater reduction in walking velocity (P=0.000) over the course of the 6MW, which coincided with a significantly greater increase in step time and double support (P=0.029) than in the other groups. Only the ambulatory with assistance MS group showed an increase in step-time variability and double-support variability during the 6MW (P's<0.05). The novel results indicate that the reduction in velocity over prolonged walking occurs through a greater change in the temporal parameters of gait in persons with MS who require assistance while walking. In addition, the increase in gait variability in the individuals with MS who require assistance while walking indicates that the control over walking further deteriorates over the course of the 6MW.

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“…In fact, the popularity of entropy measures stems from their applicability to short and noisy processes with important stochastic components such as those describing the dynamical activity of real-world systems. These measures have been applied with great success to numerous research fields, including heart rate variability [3,19–23], cardiovascular control [3,24–26], cerebrovascular dynamics [27,28], cardiac arrhythmias [29], financial time series analysis [30,31], gait and posture [32–36], climatology [37], earth sciences [38], cellular automata [39,40], electromyography [41], electroencephalography [42–44], magnetoencephalography [45], functional neuroimaging [14,46,47], and others [48–51]. …”

Section: Introductionmentioning

confidence: 99%

Entropy measures, entropy estimators, and their performance in quantifying complex dynamics: Effects of artifacts, nonstationarity, and long-range correlations

2017

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Entropy measures are widely applied to quantify the complexity of dynamical systems in diverse fields. However, the practical application of entropy methods is challenging, due to the variety of entropy measures and estimators and the complexity of real-world time series, including nonstationarities and long-range correlations (LRC). We conduct a systematic study on the performance, bias, and limitations of three basic measures (entropy, conditional entropy, information storage) and three traditionally used estimators (linear, kernel, nearest neighbor). We investigate the dependence of entropy measures on estimator- and process-specific parameters, and we show the effects of three types of nonstationarities due to artifacts (trends, spikes, local variance change) in simulations of stochastic autoregressive processes. We also analyze the impact of LRC on the theoretical and estimated values of entropy measures. Finally, we apply entropy methods on heart rate variability data from subjects in different physiological states and clinical conditions. We find that entropy measures can only differentiate changes of specific types in cardiac dynamics and that appropriate preprocessing is vital for correct estimation and interpretation. Demonstrating the limitations of entropy methods and shedding light on how to mitigate bias and provide correct interpretations of results, this work can serve as a comprehensive reference for the application of entropy methods and the evaluation of existing studies.

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Gait Variability Measures Reveal Differences Between Multiple Sclerosis Patients and Healthy Controls

Cited by 89 publications

References 57 publications

The “butterfly diagram”: A gait marker for neurological and cerebellar impairment in people with multiple sclerosis

The “butterfly diagram”: A gait marker for neurological and cerebellar impairment in people with multiple sclerosis

Examination of spatiotemporal gait parameters during the 6-min walk in individuals with multiple sclerosis

Entropy measures, entropy estimators, and their performance in quantifying complex dynamics: Effects of artifacts, nonstationarity, and long-range correlations

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