Possibility of Using Entropy Method to Evaluate the Distracting Effect of Mobile Phones on Pedestrians

Nurwulan, Nurul Retno; Jiang, Bernard C.

doi:10.3390/e18110390

Cited by 13 publications

(9 citation statements)

References 66 publications

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“…Following its introduction by Costa et al [ 14 ], multiscale entropy (MSE) was successfully applied to quantify the complexity of signals in different research fields, such as biomedical [ 15 , 16 , 17 , 18 , 19 ], electroseismic [ 20 ], and the vibration of rotary machines [ 21 ].…”

Section: Methodsmentioning

confidence: 99%

Development of Postural Stability Index to Distinguish Different Stability States

Nurwulan

Jiang

Novak

2019

Entropy

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A key factor for fall prevention involves understanding the pathophysiology of stability. This study proposes the postural stability index (PSI), which is a novel measure to quantify different stability states on healthy subjects. The results of the x-, y-, and z-axes of the acceleration signals were analyzed from 10 healthy young adults and 10 healthy older adults under three conditions as follows: Normal walking, walking with obstacles, and fall-like motions. The ensemble empirical mode decomposition (EEMD) was used to reconstruct the acceleration signal data. Wearable accelerometers were located on the ankles and knees of the subjects. The PSI indicated a decreasing trend of its values from normal walking to the fall-like motions. Free-walking data were used to determine the stability based on the PSI. The segmented free-walking data indicated changes in the stability states that suggested that the PSI is potentially helpful in quantifying gait stability.

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Section: Methodsmentioning

confidence: 99%

Development of Postural Stability Index to Distinguish Different Stability States

Nurwulan

Jiang

Novak

2019

Entropy

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“…These information theory based approaches have been considered in the study of postural control to quantify how individuals regulate their postural fluctuations during their daily activities [ 21 ]. Nonlinear, non-stationary signals from the force platform are also suited to the relatively localised characterisation and underpin the entropy-based methods by capturing the postural stability to a higher degree of accuracy [ 22 ]. Furthermore, there has been a renewed interest in identifying how the complexity of physiological signals changes along with the health status [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

Quantification of Axial Abnormality Due to Cerebellar Ataxia with Inertial Measurements

Nguyen

Phan

Pathirana

et al. 2018

Sensors

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Cerebellar Ataxia (CA) leads to deficiencies in muscle movement and lack of coordination that is often manifested as gait and balance disabilities. Conventional CA clinical assessments are subjective, cumbersome and provide less insight into the functional capabilities of patients. This cross-sectional study investigates the use of wearable inertial sensors strategically positioned on the front-chest and upper-back locations during the Romberg and Trunk tests for objective assessment of human postural balance due to CA. The primary aim of this paper is to quantify the performance of postural stability of 34 patients diagnosed with CA and 22 healthy subjects as controls. Several forms of entropy descriptions were considered to uncover characteristics of movements intrinsic to CA. Indeed, correlation with clinical observation is vital in ascertaining the validity of the inertial measurements in addition to capturing unique features of movements not typically observed by the practicing clinician. Both of these aspects form an integral part of the underlying objective assessment scheme. Uncertainty in the velocity contained a significant level of information with respect to truncal instability and, based on an extensive clustering and discrimination analysis, fuzzy entropy was identified as an effective measure in characterising the underlying disability. Front-chest measurements demonstrated a strong correlation with clinical assessments while the upper-back measurements performed better in classifying the two cohorts, inferring that the standard clinical assessments are relatively influenced by the frontal observations. The Romberg test was confirmed to be an effective test of neurological diagnosis as well as a potential candidate for objective assessment resulting in a significant correlation with the clinical assessments. In contrast, the Trunk test is observed to be relatively less informative.

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“…Although this game is beneficial to encourage people to exercise, it is rather dangerous when people do not really pay attention to the road [1]. Mobile phone use during walking has a negative impact on working memory that increases perturbation that may cause accidents [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Decomposition Methods in Perturbed Walking

Nurwulan¹

2020

RIA

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Mobile phones cannot be separated from our daily lives. Most of young adults use their mobile phones while walking and this potentially cause accidents. The current study aimed to evaluate the performance of decomposition methods to detect perturbed walking. Ten young adults were asked to perform normal walking and walking while playing game on their phones. The vertical acceleration data were decomposed using 4, 6, and 8 levels of ensemble empirical mode decomposition (EEMD), discrete wavelet transform (DWT), and wavelet packet decomposition (WPD) before the calculation of the step stability index (SSI) to detect the perturbation during walking. Machine learning techniques were used to evaluate the performance of the decomposition methods. The evaluation results showed that DWT with 6 levels of decomposition outperformed other decomposition methods. In conclusion, the DWT can be used to increase the sensitivity of the SSI method in detecting walking perturbation.

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Possibility of Using Entropy Method to Evaluate the Distracting Effect of Mobile Phones on Pedestrians

Cited by 13 publications

References 66 publications

Development of Postural Stability Index to Distinguish Different Stability States

Development of Postural Stability Index to Distinguish Different Stability States

Quantification of Axial Abnormality Due to Cerebellar Ataxia with Inertial Measurements

Performance Evaluation of Decomposition Methods in Perturbed Walking

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