Purpose: This study presents the use of dry needling (DN) as an intervention to support functional rehabilitation for an adult diagnosed with lateral epicondylosis.
Methods: A retrospective, single subject, AB design was implemented. A 50-year-old male with a six-month history of dominant left lateral epicondylosis received traditional interventions for 4 weeks (baseline phase; A) followed by the same interventions with the addition of DN (intervention phase; B).
Autonomous navigation to a specified waypoint is traditionally accomplished with a layered stack of global path planning and local motion planning modules that generate feasible and obstacle-free trajectories. While these modules can be modified to meet task-specific constraints and user preferences, current modification procedures require substantial effort on the part of an expert roboticist with a great deal of technical training. In this paper, we simplify this process by inserting a Machine Learning module between the global path planning and local motion planning modules of an off-the shelf navigation stack.
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