Complexity-Based Measures of Postural Sway during Walking at Different Speeds and Durations Using Multiscale Entropy

Liau, Ben-Yi; Wu, Fu Lien; Lung, Chi-Wen; Zhang, Xueyan; Wang, Xiaoling; Jan, Yih‐Kuen

doi:10.3390/e21111128

Cited by 17 publications

(11 citation statements)

References 62 publications

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“…Parameters generated based on the dynamics of the COP displacement facilitate modeling mechanisms underlying balance control [8][9][10]. For example, recent studies quantify the entropy of COP dynamics during quiet standing [11][12][13] and walking [14]. These studies proposed that COP data entropy can be used to differentiate between fallers and non-fallers in standing, though it is not clear which entropy features should be used.…”

Section: Center Of Pressure and Center Of Mass Use For Assessing Postmentioning

confidence: 99%

Novel methodology for assessing total recovery time in response to unexpected perturbations while walking

et al. 2020

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Walking stability is achieved by adjusting the medio-lateral and anterior-posterior dimensions of the base of support (step length and step width, respectively) to contain an extrapolated center of mass. We aimed to calculate total recovery time after different types of perturbations during walking, and use it to compare young and older adults following different types of perturbations. Walking trials were performed in 12 young (age 26.92 ± 3.40 years) and 12 older (age 66.83 ± 1.60 years) adults. Perturbations were introduced at different phases of the gait cycle, on both legs and in anterior-posterior or medio-lateral directions, in random order. A novel algorithm was developed to determine total recovery time values for regaining stable step length and step width parameters following the different perturbations, and compared between the two participant groups under low and high cognitive load conditions, using principal component analysis (PCA). We analyzed 829 perturbations each for step length and step width. The algorithm successfully estimated total recovery time in 91.07% of the runs. PCA and statistical comparisons showed significant differences in step length and step width recovery times between anterior-posterior and medio-lateral perturbations, but no age-related differences. Initial analyses demonstrated the feasibility of comparisons based on total recovery time calculated using our algorithm.

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Section: Center Of Pressure and Center Of Mass Use For Assessing Postmentioning

confidence: 99%

Novel methodology for assessing total recovery time in response to unexpected perturbations while walking

et al. 2020

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“…Regarding nonlinear plantar pressure analysis, our previous work used the one-dimensional MSE method to analyze COP, demonstrating similar results. e findings suggested that complexity of COP was significantly lower at 3 km/h walking than the one at 6 km/h [39]. e previous literature also endorsed the results that walking faster with shorter step length might improve stability [40,41].…”

Section: Discussionmentioning

confidence: 78%

Effect of Walking Speeds on Complexity of Plantar Pressure Patterns

Liau

et al. 2021

Complexity

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Various walking speeds may induce different responses on the plantar pressure patterns. Current methods used to analyze plantar pressure patterns are linear and ignore nonlinear features. The purpose of this study was to analyze the complexity of plantar pressure images after walking at various speeds using nonlinear bidimensional multiscale entropy (MSE2D). Twelve participants (age: 27.1 ± 5.8 years; height: 170.3 ± 10.0 cm; and weight: 63.5 ± 13.5 kg) were recruited for walking at three speeds (slow at 1.8 mph, moderate at 3.6 mph, and fast at 5.4 mph) for 20 minutes. A plantar pressure measurement system was used to measure plantar pressure patterns. Complexity index (CI), a summation of MSE2D from all time scales, was used to quantify the changes of complexity of plantar pressure images. The analysis of variance with repeated measures and Fisher’s least significant difference correction were used to examine the results of this study. The results showed that CI of plantar pressure images of 1.8 mph (1.780) was significantly lower compared with 3.6 (1.790) and 5.4 mph (1.792). The results also showed that CI significantly increased from the 1st min (1.780) to the 10th min (1.791) and 20th min (1.791) with slow walking (1.8 mph). Our results indicate that slow walking at 1.8 mph may not be good for postural control compared with moderate walking (3.6 mph) and fast walking (5.4 mph). This study demonstrates that bidimensional multiscale entropy is able to quantify complexity changes of plantar pressure images after different walking speeds.

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“…McClymont et al demonstrated that when walking faster, the mean square error, one of the variability metrics of plantar pressures, increased considerably [75]. Elevated plantar pressures may accumulate tension abnormally over the plantar soft tissue [76]. Therefore, to reach the lowest PPP, DM people and non-DM may have different suitable walking speeds [31,32,77].…”

Section: Discussionmentioning

confidence: 99%

A Review of the Plantar Pressure Distribution Effects from Insole Materials and at Different Walking Speeds

et al. 2021

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Among people with diabetes mellitus (DM), the two common strategies for decreasing peak plantar pressure (PPP) to reduce diabetic foot ulcers (DFUs) risks are to modify walking speeds and to change insole materials. This study reviewed the PPP reduction based on various walking speeds and insole materials. The articles were retrieved from four major scientific databases and manual search. We identified 1585 articles, of which 27 articles were selected for full-text analysis. We found that in faster walking speeds, the forefoot PPP was higher (308 kPa) than midfoot (150 kPa) and rearfoot (251 kPa) PPP. The appropriate walking speed for reducing the forefoot PPP was about 6 km/h for non-DM and 4 km/h for DM people. The forefoot PPP in DM people was 185% higher than that of non-DM people. Ethylene–vinyl acetate (EVA) insole material was the most popular material used by experts (26%) in the forefoot and reduced 37% of PPP. In conclusion, the suitable walking speed for DM was slower than for non-DM people, and EVA was the most common insole material used to decrease the PPP under the forefoot. The clinicians might recommend DM people to walk at 4 km/h and wear EVA insole material to minimize the DFUs.

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Complexity-Based Measures of Postural Sway during Walking at Different Speeds and Durations Using Multiscale Entropy

Cited by 17 publications

References 62 publications

Novel methodology for assessing total recovery time in response to unexpected perturbations while walking

Novel methodology for assessing total recovery time in response to unexpected perturbations while walking

Effect of Walking Speeds on Complexity of Plantar Pressure Patterns

A Review of the Plantar Pressure Distribution Effects from Insole Materials and at Different Walking Speeds

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