Evaluation of Methods Based on Conventional Videography for Detection of Gait Events

Peterson, Maxim; Ewins, David; Shaheen, Aliah F.; Formento, Paola Andrea Catalfamo

doi:10.1007/978-3-319-13117-7_61

Cited by 6 publications

(6 citation statements)

References 11 publications

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“…Using tools provided by the software (Kinovea version 0.8.5), the positions of two markers were tracked [10]. The markers were located on the heel and on the toe of the shoes used by the subject.…”

Section: Semi-automatic Event Detection Methods (Sam)mentioning

confidence: 99%

“…The frame in which the foot makes contact with the floor after the swing phase was recorded as the IC and the frame after which the foot leaves the ground after the stance phase was recorded as FO. All events were evaluated by the same researcher, although good intra and inter rater repeatability has been established for this method [10].…”

Section: Visual Event Detection Methods (Vm)mentioning

confidence: 99%

“…Visual detection was performed by direct observation of the video, without using any tools provided by the software (VirtualDub version 1.9.11) [10]. The frame in which the foot makes contact with the floor after the swing phase was recorded as the IC and the frame after which the foot leaves the ground after the stance phase was recorded as FO.…”

Section: Visual Event Detection Methods (Vm)mentioning

confidence: 99%

“…They are easy to use, portable, can be installed in small physical areas, and their cost is relatively low, therefore they could be considered for gait event detection in the clinical setting. A previous pilot study showed promising results for the use of conventional video cameras in the detection of gait events [10] on level ground. That study, investigated the accuracy and reliability for different raters of two event detection methods, the visual (VM) and the semiautomatic (SAM), using conventional video cameras in subjects walking on level ground.…”

Section: Introductionmentioning

confidence: 96%

“…The key objectives of the present study were to extend the evaluation of both event detection algorithms presented in [10], for the visual detection of IC and FO to a larger number of subjects, while walking on level ground, and to evaluate the performance of the algorithms for subjects walking on stairs. …”

Section: Introductionmentioning

confidence: 99%

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Evaluation of methods based on conventional videography for detection of gait events

Cano¹,

Ewins²,

Shaheen³

et al. 2017

VII Latin American Congress on Biomedical Engineering CLAIB 2016, Bucaramanga, Santander, Colombia, October 26th -28th, 2016

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Abstract-The detection of gait events plays an important role in gait analysis. The initial foot contact (IC) and the end of foot contact or foot off (FO) represent the start of stance and swing, respectively. They are commonly used to compute parameters that offer information for the characterization of gait.To determine these events, kinematic methods that implement optical systems, including conventional video cameras, have been suggested.The key objective of this study was to evaluate the performance of two event detection methods, one visual (VM) and one semiautomatic (SAM), which use conventional video recordings, for the visual detection of IC and FO, during level ground and stair walking. The methods were tested in 10 healthy subjects, wearing confortable shoes and walking at a self-selected speed. The accuracy of the proposed methods was compared with force plate data (gold standard). Furthermore, the VM and the SAM were compared with an alternative kinematic method: The Velocity-Algorithm (VA), previously described in the literature.The results of the level ground test showed that the VM and the SAM detected IC and FO with an absolute mean difference (AMD) lower than 30 ms.For the stair climbing test, it was found that the VM and the SAM detected IC and FO with an AMD lower than 55 ms.In general terms, the VM and the SAM produced differences within the ranges reported in the literature for both terrains.These results provide preliminary evidence supporting the use of both methods for gait event detection on level walking as well as stair climbing.

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Section: Semi-automatic Event Detection Methods (Sam)mentioning

confidence: 99%

Section: Visual Event Detection Methods (Vm)mentioning

confidence: 99%

Section: Visual Event Detection Methods (Vm)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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