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A perceptual map for gait symmetry quantification and pathology detection

Overview of attention for article published in BioMedical Engineering OnLine, October 2015
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3 X users

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35 Mendeley
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Title
A perceptual map for gait symmetry quantification and pathology detection
Published in
BioMedical Engineering OnLine, October 2015
DOI 10.1186/s12938-015-0097-2
Pubmed ID
Authors

Antoine Moevus, Max Mignotte, Jacques A. de Guise, Jean Meunier

Abstract

The gait movement is an essential process of the human activity and the result of collaborative interactions between the neurological, articular and musculoskeletal systems, working efficiently together. This explains why gait analysis is important and increasingly used nowadays for the diagnosis of many different types (neurological, muscular, orthopedic, etc.) of diseases. This paper introduces a novel method to quickly visualize the different parts of the body related to an asymmetric movement in the human gait of a patient for daily clinical usage. The proposed gait analysis algorithm relies on the fact that the healthy walk has (temporally shift-invariant) symmetry properties in the coronal plane. The goal is to provide an inexpensive and easy-to-use method, exploiting an affordable consumer depth sensor, the Kinect, to measure the gait asymmetry and display results in a perceptual way. We propose a multi-dimensional scaling mapping using a temporally shift invariant distance, allowing us to efficiently visualize (in terms of perceptual color difference) the asymmetric body parts of the gait cycle of a subject. We also propose an index computed from this map and which quantifies locally and globally the degree of asymmetry. The proposed index is proved to be statistically significant and this new, inexpensive, marker-less, non-invasive, easy to set up, gait analysis system offers a readable and flexible tool for clinicians to analyze gait characteristics and to provide a fast diagnostic. This system, which estimates a perceptual color map providing a quick overview of asymmetry existing in the gait cycle of a subject, can be easily exploited for disease progression, recovery cues from post-operative surgery (e.g., to check the healing process or the effect of a treatment or a prosthesis) or might be used for other pathologies where gait asymmetry might be a symptom.

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X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 34 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 23%
Student > Ph. D. Student 7 20%
Student > Bachelor 5 14%
Other 3 9%
Student > Postgraduate 3 9%
Other 6 17%
Unknown 3 9%
Readers by discipline Count As %
Medicine and Dentistry 9 26%
Engineering 6 17%
Nursing and Health Professions 5 14%
Sports and Recreations 4 11%
Agricultural and Biological Sciences 1 3%
Other 3 9%
Unknown 7 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 November 2015.
All research outputs
#14,240,471
of 22,831,537 outputs
Outputs from BioMedical Engineering OnLine
#371
of 823 outputs
Outputs of similar age
#147,730
of 284,657 outputs
Outputs of similar age from BioMedical Engineering OnLine
#4
of 17 outputs
Altmetric has tracked 22,831,537 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 823 research outputs from this source. They receive a mean Attention Score of 4.6. This one has gotten more attention than average, scoring higher than 52% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 284,657 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.