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A 2D markerless gait analysis protocol to estimate the sagittal joint kinematics of children with cerebral palsy
Department of Biomedical Sciences, University of Sassari, Sassari, Italy; DIAG, Sapienza University of Rome, Rome, Italy.
GPEM Srl, Alghero, Italy.
Department of Biomedical Sciences, University of Sassari, Sassari, Italy.
GPEM Srl, Alghero, Italy.
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2019 (English)In: 2019 IEEE 23RD INTERNATIONAL SYMPOSIUM ON CONSUMER TECHNOLOGIES (ISCT), IEEE , 2019, p. 192-196Conference paper, Published paper (Refereed)
Abstract [en]

The quantitative analysis of human movement provides a deep understanding of the pathophysiological mechanisms underlying locomotion. The traditional marker-based stereo-photogrammetric systems and clinical protocols for motion analysis, although very accurate, have a number of disadvantages that limit their use to large clinical facilities. Among the disadvantages is the use of markers on the body, which can make the patient uneasy, especially children with cerebral palsy. To overcome the limitations of the marker-based stereophotogrammetry and to guarantee accuracy, reproducibility and usability of the measurement, a new markerless protocol is introduced, which, estimates the lower limb sagittal joint kinematics from RGB video images combined with measurements from an infrared depth (D) sensor. The validity of the markerless protocol is demonstrated by comparing the estimates obtained, with those resulting from the application of a common protocol applied to marker-based measurements. The joint kinematics patterns obtained from the ML protocol and the one of reference showed a good agreement after removing the angular offsets with RMSD values between 3.5 and 5 degrees for all joints and R values between 0.8 and 1. The interpretation of the differences found in this study should be treated carefully since they are the results not only of different measurement systems but also of different protocols (2D vs 3D). The proposed protocol for the estimation of the 2D joint kinematics of the lower limbs from RGB-D sensor data is a promising low-cost and simple solution for monitoring children with cerebral palsy.

Place, publisher, year, edition, pages
IEEE , 2019. p. 192-196
Keywords [en]
Gait Analysis, Joint Kinematics, Markerless, RGB-D, Cerebral Palsy, Video Analysis
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-88072DOI: 10.1109/ISCE.2019.8901029ISI: 000587279800041Scopus ID: 2-s2.0-85075634781ISBN: 978-1-7281-3570-0 (print)OAI: oai:DiVA.org:oru-88072DiVA, id: diva2:1509960
Conference
23rd IEEE International Symposium on Consumer Technologies (ISCT 2019), Ancona, Italy, June 19-21, 2019
Note

Funding Agency:

POR FESR 2014/2020

Available from: 2020-12-15 Created: 2020-12-15 Last updated: 2020-12-15Bibliographically approved

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Pantzar-Castilla, Evelina

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Citation style
  • apa
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Output format
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