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2D Markerless Gait Analysis

2D Markerless Gait Analysis
2D Markerless Gait Analysis
We present a 2D gait analysis system which is completely markerless and extracts kinematic information by analyzing video sequences obtained from an RGB video camera. These properties make the proposed approach particularly suitable in medical contexts where visual gait observation is still a recognised procedure or the invasiveness and high costs of marker-based systems can not be afforded. Markerless motion estimation literature for medical gait analysis is generally 2D oriented, since the majority of joints dysfunctions related to gait occur in the sagittal plane. Most of the approaches are based on time consuming human body models or need human-intervention. Conversely, the method we present this contribution is silhouette-based, completely automatic and uses information on the human body anthropometric proportions for the estimation of the lower limbs’ pose in the sagittal plane with good accuracy and low computational cost. Tests on a large number of synthetic and real video sequences with normal gait have been performed. Different frame rates, image resolutions and noises have been considered. The obtained results, in terms of sagittal joint angles, have been compared with the typical trends found in biomechanical studies. The performance of the proposed method is particularly encouraging for its appliance in the real medical context. Keywords— Mark
Goffredo, Michela
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Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carter, John
e05be2f9-991d-4476-bb50-ae91606389da
Goffredo, Michela
21a346d2-8ce6-46b7-883f-89a2c584afc7
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carter, John
e05be2f9-991d-4476-bb50-ae91606389da

Goffredo, Michela, Nixon, Mark and Carter, John (2008) 2D Markerless Gait Analysis. 4th European Congress for Medical and Biomedical Engineering 2008, Antwerp, Belgium. 23 - 27 Nov 2008.

Record type: Conference or Workshop Item (Other)

Abstract

We present a 2D gait analysis system which is completely markerless and extracts kinematic information by analyzing video sequences obtained from an RGB video camera. These properties make the proposed approach particularly suitable in medical contexts where visual gait observation is still a recognised procedure or the invasiveness and high costs of marker-based systems can not be afforded. Markerless motion estimation literature for medical gait analysis is generally 2D oriented, since the majority of joints dysfunctions related to gait occur in the sagittal plane. Most of the approaches are based on time consuming human body models or need human-intervention. Conversely, the method we present this contribution is silhouette-based, completely automatic and uses information on the human body anthropometric proportions for the estimation of the lower limbs’ pose in the sagittal plane with good accuracy and low computational cost. Tests on a large number of synthetic and real video sequences with normal gait have been performed. Different frame rates, image resolutions and noises have been considered. The obtained results, in terms of sagittal joint angles, have been compared with the typical trends found in biomechanical studies. The performance of the proposed method is particularly encouraging for its appliance in the real medical context. Keywords— Mark

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More information

Published date: 2008
Additional Information: Event Dates: Nov 2008
Venue - Dates: 4th European Congress for Medical and Biomedical Engineering 2008, Antwerp, Belgium, 2008-11-23 - 2008-11-27
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 267092
URI: http://eprints.soton.ac.uk/id/eprint/267092
PURE UUID: 1ea4742c-6d2b-47d0-9c60-befaff7ba0c0
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 11 Feb 2009 16:49
Last modified: 07 Oct 2020 02:32

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Contributors

Author: Michela Goffredo
Author: Mark Nixon ORCID iD
Author: John Carter

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