METHOD AND SYSTEM FOR POSTURAL STABILITY ASSESSMENT

    公开(公告)号:US20190008417A1

    公开(公告)日:2019-01-10

    申请号:US15914286

    申请日:2018-03-07

    Abstract: This disclosure relates generally to health monitoring and assessment systems, and more particularly to perform postural stability assessment of a user and quantify the assessed postural stability. In an embodiment, the system, by monitoring specific actions (which are part of certain tests done for the postural stability assessment) being performed by a user, collects inputs which are then processed to determine SLS duration, the body joint vibration, and the body sway area of the user, while performing the tests. By processing the SLS duration, the body joint vibration, and the body sway area together, a postural stability index score for the user is determined, and based on this score, postural stability assessment for the user is performed.

    SYSTEMS AND METHODS FOR OPTIMIZING A JOINT COST FUNCTION AND DETECTING NEURO MUSCULAR PROFILES THEREOF

    公开(公告)号:US20190115109A1

    公开(公告)日:2019-04-18

    申请号:US16159245

    申请日:2018-10-12

    Abstract: Unimaginable are the difficulties faced by patients affected by sensory-motor disabilities while executing day to day activities. The flamboyant progress that has made in other areas of medical science does not translate itself in diagnosing them. Early detection and personalized therapy of these disorders is still out of reach. Present disclosure provides systems and methods for optimizing a joint cost function and detecting neuro muscular profiles (e.g., state of user under observation) thereof by implementing a model that quantifies these disorders in terms of a cost functional, which captures the trade-off between the torques applied and the velocities experienced at the joints. Estimation of this cost functional, otherwise known as Inverse optimal control was then carried out using an optimization procedure. To validate ability of estimated cost functional to distinguish weakly distinct neuro-motor conditions, Microsoft Kinect® motion capture data from normal subjects and a patient population with mild sensory-motor disabilities.

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