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    Advanced Techniques for Robotic Assessment of Neurological Impairments In Stroke Patients

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    Tyryshkin_Kathrin_201409_PhD.pdf (5.858Mb)
    Date
    2014-09-29
    Author
    Tyryshkin, Kathrin
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    Abstract
    Stroke is an acute injury of the central nervous system and is caused by the disruption of blood flow or by the rupture of blood vessels. A stroke can impact many body functions, often causing motor, speech, memory, vision and other sensory impairments.

    It is highly prevalent and often requires long hospitalizations and post-stroke rehabilitation.

    The key to successful rehabilitation after stroke is an accurate assessment

    of the impairment. Current clinical assessments of stroke-related impairments involve physical assessment and visual observation by physicians. Existing clinical scores of upper limb function often use observer-based ordinal scales that are subjective and

    commonly have floor and ceiling effects. Therefore, these methods are not adequate

    to reliably discriminate different levels of performance.

    Robotics and integrated virtual reality systems have a tremendous potential to be

    used in computational systems that analyze, visualize and aid clinicians to identify

    and assess sensory-motor impairments. This thesis presents a framework for analysis

    and extraction of reliable and valid features from robotic data that can be used

    to accurately and objectively assess neurological impairments. The framework was

    applied on the Object Hit task that assesses the ability of participants to select and

    engage motor actions with both hands.

    In addition, the Object Hit Task was compared to the Object Hit and Avoid task, which is a slight modification of the original task. The comparison was done

    using a developed feature and task analysis framework. This framework encompasses

    similarities and differences between tasks in a given experiment in terms of feature

    information. The results showed that for the data used in the analysis, Object Hit

    task is able to identify impairments more effectively than the Object Hit and Avoid

    task. The overall results demonstrate that the Object Hit task provides an objective

    and easy approach to quantify upper limb motor function and visuospatial skills after

    stroke. The developed assessment tool can also be applied for diagnosis and prognosis

    of other neurological deficits, beyond stroke assessment.
    URI for this record
    http://hdl.handle.net/1974/12514
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