Automatic versus manual tuning of robot-assisted gait training in people with neurological disorders

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    Introduction: In clinical practice, therapists choose the amount of assistance
    that patients receive while walking in a robotic gait trainer. A disadvantage is
    that therapists cannot directly feel what the device does. Therefore, algorithms
    were developed that automatically adjust the assistance, however,
    they have not been compared to the settings that therapists would choose.
    Main objective: The goal of this study was to compare the assistance set by
    an automatically-tuned (AT) algorithm to manually-tuned (MT) assistance in
    a robotic gait trainer.

    Methods: Ten participants (6x stroke, 4x spinal cord injury) walked with
    both approaches in the LOPES II gait trainer. In both cases, the assistance
    was adjusted for various subtasks of walking (e.g. step height). Either the
    therapist changed the assistance for each subtask (MT) or the AT algorithm
    adjusted the assistance based on errors compared to reference trajectories.

    Results and discussion: The different approaches did not always focus on
    the same subtasks. On average, participants received less assistance with
    the AT algorithm for all subtasks. In spite of this, the largest errors
    compared to the reference trajectory were found for the MT approach.
    A possible reason for this is that therapists might focus on other factors
    while setting the assistance.

    Conclusion: An automatically-tuned algorithm can decrease deviations
    from a reference trajectory, however, large differences were found
    compared to the settings chosen by a therapist and further research should
    focus on how this information can be used to optimize robotic gait therapy.
    Original languageEnglish
    Number of pages1
    Publication statusPublished - 23 May 2019
    Event3rd Congress on NeuroRehabilitation and Neural Repair 2019 - Maastricht, Netherlands
    Duration: 22 May 201924 May 2019
    Conference number: 3


    Conference3rd Congress on NeuroRehabilitation and Neural Repair 2019


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