Objective: To examine the perceived value, benefits, drawbacks, and ideas for technology development and implementation of surface electromyography (sEMG) recordings in neurologic rehabilitation practice from clinical stakeholder perspectives. Design: A qualitative, phenomenological study was conducted. In-depth, semi-structured interviews and focus groups were completed. Sessions included questions about clinician perspectives and demonstrations of four sEMG systems to garner perceptions of specific system features. Setting: The study was conducted at four hospital systems in a large metropolitan area. Participants: 22 adult and pediatric physical therapists, occupational therapists, and physiatrists from inpatient, outpatient, and research settings took part in the study. Interventions: Not Applicable Main Outcome Measures: Interviews and focus groups were audio-recorded, transcribed verbatim, then coded for analysis into themes.

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In human-in-the-loop control systems, operators can learn to manually control dynamic machines with either hand using a combination of reactive (feedback) and predictive (feedforward) control. This paper studies the effect of handedness on learned controllers and performance during a trajectory-tracking task. In an experiment with 18 participants, subjects perform an assay of unimanual trajectory-tracking and disturbancerejection tasks through second-order machine dynamics, first with one hand then the other. To assess how hand preference (or dominance) affects learned controllers, we extend, validate, and apply a non-parametric modeling method to estimate the concurrent feedback and feedforward controllers. We find that performance improves because feedback adapts, regardless of the hand used. We do not detect statistically significant differences in performance or learned controllers between hands. Adaptation to reject disturbances arising exogenously (i.e. applied by the experimenter) and endogenously (i.e. generated by sensorimotor noise) explains observed performance improvements.

In human-in-the-loop control systems, operators can learn to manually control dynamic machines with either hand using a combination of reactive (feedback) and predictive (feedforward) control. This paper studies the effect of handedness on learned controllers and performance during a continuous trajectory-tracking task. In an experiment with 18 participants, subjects perform an assay of unimanual trajectory-tracking and disturbance-rejection tasks through second-order machine dynamics, first with one hand then the other. To assess how hand preference (or dominance) affects learned controllers, we extend, validate, and apply a non-parametric modeling method to estimate the concurrent feedback and feedforward elements of subjects' controllers. We find that handedness does not affect the learned controller and that controllers transfer between hands. Observed improvements in time-domain tracking performance may be attributed to adaptation of feedback to reject disturbances arising exogenously (i.e. applied by the experimenter) and endogenously (i.e. generated by sensorimotor noise)

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