Markerless gait characterization using single video camera setup

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dc.contributor.author Khokhar, Arushi
dc.contributor.author Singh, Yogesh
dc.contributor.author Vashista, Vineet
dc.contributor.other 6th International Conference on Advances in Robotics (AIR 2023)
dc.coverage.spatial India
dc.date.accessioned 2023-12-28T16:49:21Z
dc.date.available 2023-12-28T16:49:21Z
dc.date.issued 2023-07-05
dc.identifier.citation Khokhar, Arushi; Singh, Yogesh and Vashista, Vineet, "Markerless gait characterization using single video camera setup", in the 6th International Conference on Advances in Robotics (AIR 2023), Rupnagar, IN, Jul. 5-8, 2023.
dc.identifier.uri https://doi.org/10.1145/3610419.3610465
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/9609
dc.description.abstract Gait analysis is now a standard aspect for diagnosing and treating conditions such as cerebral palsy, Parkinson’s disease, rheumatoid arthritis and other neurological disorders. It is used as an early diagnosis approach to assessing a patient’s walking pattern. The state-of-the-art gait analysis techniques require a dedicated laboratory setup along with highly skilled professionals to operate the equipment involved to get the gait parameters for analysis. In addition to this, it also involves placing external markers on the body of the subjects which may not be the actual representation of how the involved subjects walk in natural settings. In this paper, a workflow for a pipeline application has been presented that provides spatiotemporal gait parameters and joint kinematics characterization from a video shot on a single smartphone camera. The proposed method for gait analysis can be used in home conditions thus eliminating constraints caused by a lack of specialised equipment, technical expertise, time and money.
dc.description.statementofresponsibility by Arushi Khokhar, Yogesh Singh and Vineet Vashista
dc.language.iso en_US
dc.publisher Association for Computing Machinery (ACM)
dc.subject Gait analysis
dc.subject Computer vision
dc.subject Virtual reality tracking
dc.title Markerless gait characterization using single video camera setup
dc.type Conference Paper


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