Quantifying complexity and variability in phase portraits of gait

DiBerardino, Louis A.; Polk, John D.; Rosengren, Karl S.; Spencer-Smith, Jesse; Hsiao-Wecksler, Elizabeth T.

doi:10.1016/j.clinbiomech.2010.03.007

Cited by 25 publications

(26 citation statements)

References 18 publications

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“…Generally, these representations approximate elliptical shapes. Figure 3 shows example phase portraits from our work examining the influence of bracing a knee joint (adapted from data published in [52]). Researchers have generally described differences in phase portrait shapes, such as those shown in the figure qualitatively.…”

Section: Complexity and Variability Of Phase Portraitsmentioning

confidence: 99%

“…Inter-cycle complexity and variability have been assessed by quantifying fluctuations in the upper arm phase portraits over multiple propulsion cycles at a range of speeds. This research study utilized the metrics presented above [52] to quantify changes in the variability and complexity of motion patterns brought about by manual wheelchair propulsion experience. These pilot data suggest that slower speeds resulted in more complex and less variable motion patterns.…”

Section: Application Beyond Gait: Manual Wheelchair Propulsionmentioning

confidence: 99%

“…The full fit included a high number of harmonics (500) to more completely describe the shapes, while the reduced fit was computed with a lower number of harmonics (e.g., 10). In our more recent research [52], data was collected while 20 healthy young male subjects walked on a treadmill during three-minute trials of normal (unbraced) or right knee-braced walking. EFA was performed on 20 consecutive gait cycles for each limb segment using a custom-modified version of an existing MATLAB elliptical Fourier program [57], based on the methodology of Kuhl and Giardina [58].…”

Section: Complexity and Variability Of Phase Portraitsmentioning

confidence: 99%

“…For this reason, we have been developing metrics to quantify changes in the variability and complexity of consecutive phase portraits generated by a specific body segment while doing repetitive cyclic movement. We have used this approach to examine symmetry between the movement patterns of the right and left lower limb [49,50,52]. Variability measures were based on the fluctuation in phase portrait centroid location between individual consecutive gait cycles.…”

Section: Complexity and Variability Of Phase Portraitsmentioning

confidence: 99%

“…These include (1) Region of Deviation Analysis (ROD), (2) complexity and variability analysis of phase portraits, and (3) multivariate shape-alignment and decomposition. These techniques were developed using a series of different data sets including previously published data on gait ontogeny [49], a set of motion capture data of typically and atypically developing older children [50], and motion capture data that simulated injuries which restrict joint range of motion to either the right knee or ankle [51][52][53]. These later studies involved controlled experiments with healthy individuals that were fitted with an external brace to immobilize the desired joint to mimic asymmetrical joint impairment.…”

Section: New Tools For Capturing the Multivariate And Dynamic Nature mentioning

confidence: 99%

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A Review of New Analytic Techniques for Quantifying Symmetry in Locomotion

et al. 2010

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Abstract:We present a review of novel techniques developed by our research group to improve quantitative assessment of human movement, especially assessments related to symmetric and asymmetric gait patterns. These new methods use motion capture data of the lower limb joints (e.g., joint and body segment angular position and/or velocity, or joint center locations) and include: (1) Regions of Deviation (ROD) analysis, (2) complexity and variability of phase portraits, and (3) multivariate shape-alignment and decomposition. We provide example demonstrations of these techniques using data from infants, typical and atypically developing children, simulated injuries of a knee or ankle, and wheelchair propulsion.

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Section: Complexity and Variability Of Phase Portraitsmentioning

confidence: 99%

Section: Application Beyond Gait: Manual Wheelchair Propulsionmentioning

confidence: 99%

Section: Complexity and Variability Of Phase Portraitsmentioning

confidence: 99%

Section: Complexity and Variability Of Phase Portraitsmentioning

confidence: 99%

Section: New Tools For Capturing the Multivariate And Dynamic Nature mentioning

confidence: 99%

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A Review of New Analytic Techniques for Quantifying Symmetry in Locomotion

et al. 2010

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Wearable Carbon Nanotube‐Spandex Textile Yarns for Knee Flexion Monitoring

Fay

Mannering

Jeiranikhameneh

et al. 2022

Advanced Sensor Research

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Carbon nanotube-spandex textiles are rapidly gaining in popularity as sensors for human motion, yet their use as-and comparison to-viable clinical-based instrumentation has not been thoroughly investigated. Herein, the use of novel yarn-based sensors that show excellent characteristics, ideal for joint kinematic sensing, is described. Knee kinematic monitoring of nine healthy participants while walking on a treadmill is examined. This is enabled through a 3D-printed knee brace integrated with a wireless transmission device. The design, development, and testing of the wearable device is presented along with wireless data capture and processing. Additionally, the findings are compared in vivo to those reported by a reference optoelectronic measurement system (KneeKG) for validation purposes. The results show a high correlation between both systems, with an average Pearson's r-value of 0.89 across each corresponding knee. This study is the first to explore the use of these novel yarn sensors for sagittal knee kinematic monitoring on participants during trials and validate the findings via an optoelectronic measurement system.

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Footfall Placement Variability and Falls in Multiple Sclerosis

et al. 2012

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Gait variability (i.e., fluctuations in walking) provides unique information about the control of movement and is associated with falls. This investigation examined the association between gait variability and falls in persons with multiple sclerosis (MS) and healthy controls. Traditional distributional metrics of gait variability (i.e., coefficient of variation (CV)) and a novel metric based on Fourier series analysis of footfall placement variability were determined for 41 individuals with MS and 20 age- and sex-matched controls. Spatiotemporal parameters of gait were collected using a 7.9 m electronic walkway that recorded individual footfalls during steady state comfortable walking. Persons with MS were divided into two groups based on fall history (non-fallers and recurrent fallers). Overall, persons with MS had greater gait variability than controls as indexed by CV and Fourier-based variability (p's < 0.05). Moreover, recurrent fallers with MS had greater Fourier-based variability than non-fallers with MS (p = 0.025), whereas there was no difference in MS groups in traditional gait variability metrics (p > 0.05). These observations highlight that footfall placement variability is related to fall status in MS. Future work determining the sensitivity of footfall placement variability to dysfunction is warranted.

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Quantifying complexity and variability in phase portraits of gait

Cited by 25 publications

References 18 publications

A Review of New Analytic Techniques for Quantifying Symmetry in Locomotion

A Review of New Analytic Techniques for Quantifying Symmetry in Locomotion

Wearable Carbon Nanotube‐Spandex Textile Yarns for Knee Flexion Monitoring

Footfall Placement Variability and Falls in Multiple Sclerosis

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