Quantifying Chaotic Behavior in Treadmill Walking

Josiński, Henryk; Michalczuk, Agnieszka; Świtoński, Adam; Mucha, Romualda; Wojciechowski, Konrad

doi:10.1007/978-3-319-15705-4_31

Cited by 8 publications

(4 citation statements)

References 19 publications

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“…Data set 1 is illustrated in Figure 6. The three-dimensional representation for this real-world data set looks chaotic, a phenomenon that has been observed in studies on human motion analysis [24].…”

Section: Numerical Test On Three Data Sets Acquired By a Smartphonementioning

confidence: 72%

A Closed-Form Expression of the Instantaneous Rotational Lurch Index to Evaluate Its Numerical Approximation

Fiori

2019

Symmetry

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The lurch index has recently been introduced in applied kinematics as an integral descriptor of the fluency of the motion of a rigid body in space. It may be defined in different versions, according to the component of motion under investigation. In the present paper, we analyze a rotational lurch index, which describes the fluency of the spin component of motion and whose value depends, through involved relations, on the dynamics of three canonical descriptors of the orientation of a rigid body in space. The aim of the present paper is to offer a closed-form expression of the instantaneous component of the rotational lurch, which leads to the namesake index upon integration and normalization. The closed form of the index is, then, used to evaluate its practical calculation, based on numerical approximations on a number of data sets.

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Section: Numerical Test On Three Data Sets Acquired By a Smartphonementioning

confidence: 72%

A Closed-Form Expression of the Instantaneous Rotational Lurch Index to Evaluate Its Numerical Approximation

Fiori

2019

Symmetry

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“…Mean values of a stride interval for every variant are 1.20 s for Normal speed (standard deviation 0.15), 1.40 m/s for Slower speed (standard deviation 0.21), 1.13 m/s for Faster speed (standard deviation 0.14), 1.27 m/s for Slope-up (standard deviation 0.18) and 1.24 m/s for Slope-down (standard deviation 0.16). This same dataset was also used in [ 22 , 31 ].…”

Section: Methodsmentioning

confidence: 99%

Quaternion Entropy for Analysis of Gait Data

Szczęsna

2019

Entropy

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Nonlinear dynamical analysis is a powerful approach to understanding biological systems. One of the most used metrics of system complexities is the Kolmogorov entropy. Long input signals without noise are required for the calculation, which are very hard to obtain in real situations. Techniques allowing the estimation of entropy directly from time signals are statistics like approximate and sample entropy. Based on that, the new measurement for quaternion signal is introduced. This work presents an example of application of a nonlinear time series analysis by using the new quaternion, approximate entropy to analyse human gait kinematic data. The quaternion entropy was applied to analyse the quaternion signal which represents the segments orientations in time during the human gait. The research was aimed at the assessment of the influence of both walking speed and ground slope on the gait control during treadmill walking. Gait data was obtained by the optical motion capture system.

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“…Human gait models have been determined to possess elements of chaotic systems in [27]. A local dynamic stability analysis of walking activity and human gait has determined a positive Lyapunov Exponent (LE) [28][29][30][31]. A positive LE is a signature characteristic of chaotic systems and a measure of sensitivity to small perturbations.…”

Section: Related Workmentioning

confidence: 99%

Hardware/Software Co-Design of Fractal Features Based Fall Detection System

Tahir

Morison

Skelton

et al. 2020

Sensors

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Falls are a leading cause of death in older adults and result in high levels of mortality, morbidity and immobility. Fall Detection Systems (FDS) are imperative for timely medical aid and have been known to reduce death rate by 80%. We propose a novel wearable sensor FDS which exploits fractal dynamics of fall accelerometer signals. Fractal dynamics can be used as an irregularity measure of signals and our work shows that it is a key discriminant for classification of falls from other activities of life. We design, implement and evaluate a hardware feature accelerator for computation of fractal features through multi-level wavelet transform on a reconfigurable embedded System on Chip, Zynq device for evaluating wearable accelerometer sensors. The proposed FDS utilises a hardware/software co-design approach with hardware accelerator for fractal features and software implementation of Linear Discriminant Analysis on an embedded ARM core for high accuracy and energy efficiency. The proposed system achieves 99.38% fall detection accuracy, 7.3× speed-up and 6.53× improvements in power consumption, compared to the software only execution with an overall performance per Watt advantage of 47.6×, while consuming low reconfigurable resources at 28.67%.

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Quantifying Chaotic Behavior in Treadmill Walking

Cited by 8 publications

References 19 publications

A Closed-Form Expression of the Instantaneous Rotational Lurch Index to Evaluate Its Numerical Approximation

A Closed-Form Expression of the Instantaneous Rotational Lurch Index to Evaluate Its Numerical Approximation

Quaternion Entropy for Analysis of Gait Data

Hardware/Software Co-Design of Fractal Features Based Fall Detection System

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