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Ankle injury assessment using inertial 3D data

Conference Paper


Abstract


  • Sport injuries can prevent athletes from maintaining

    a high level of performance; keep them away from competitions

    during long periods of recovery, resulting in loss of income or

    even career. An objective system to assess the nature of the sport

    injury, adopt effective rehabilitation training at each stage and

    determine more effectively the time that the injured athletes can

    safely return to competition can reduce such liabilities. The

    diagnosis and monitoring of rehabilitation of sport injuries are

    critical for professional athletes.

    This study explores the feasibility of using inertial sensors to

    objectively aid in the assessment of sporting injuries and to

    monitor the progress made by an injured athlete during

    rehabilitation. This is proposed through observation, and

    contrasting the resultant deficits of muscle strength, and balance

    control, between healthy and injured parts of the body. The

    posture and gait of an athlete is monitored using a motion

    capture suit consisting of 17 tri-axial inertial sensor units. Three

    methods of Centre of Mass (COM), Symmetry angle (SA) and

    Gaussian Mixture Models (GMM) are applied to injured and

    control limbs, for a group from professional athletes when they

    perform single leg stance and one meter forward hopping. All of

    the three methods successfully distinguish between injured and

    control limbs. The results are presented and future extension of

    the methods is discussed.

Publication Date


  • 2013

Citation


  • S. Zhang, F. Naghdy, D. Stirling, M. Ros & A. Gray, "Ankle injury assessment using inertial 3D data," in 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2013, pp. 810-815.

Scopus Eid


  • 2-s2.0-84883714326

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1254

Has Global Citation Frequency


Start Page


  • 810

End Page


  • 815

Place Of Publication


  • United States

Abstract


  • Sport injuries can prevent athletes from maintaining

    a high level of performance; keep them away from competitions

    during long periods of recovery, resulting in loss of income or

    even career. An objective system to assess the nature of the sport

    injury, adopt effective rehabilitation training at each stage and

    determine more effectively the time that the injured athletes can

    safely return to competition can reduce such liabilities. The

    diagnosis and monitoring of rehabilitation of sport injuries are

    critical for professional athletes.

    This study explores the feasibility of using inertial sensors to

    objectively aid in the assessment of sporting injuries and to

    monitor the progress made by an injured athlete during

    rehabilitation. This is proposed through observation, and

    contrasting the resultant deficits of muscle strength, and balance

    control, between healthy and injured parts of the body. The

    posture and gait of an athlete is monitored using a motion

    capture suit consisting of 17 tri-axial inertial sensor units. Three

    methods of Centre of Mass (COM), Symmetry angle (SA) and

    Gaussian Mixture Models (GMM) are applied to injured and

    control limbs, for a group from professional athletes when they

    perform single leg stance and one meter forward hopping. All of

    the three methods successfully distinguish between injured and

    control limbs. The results are presented and future extension of

    the methods is discussed.

Publication Date


  • 2013

Citation


  • S. Zhang, F. Naghdy, D. Stirling, M. Ros & A. Gray, "Ankle injury assessment using inertial 3D data," in 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2013, pp. 810-815.

Scopus Eid


  • 2-s2.0-84883714326

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1254

Has Global Citation Frequency


Start Page


  • 810

End Page


  • 815

Place Of Publication


  • United States