With　the　accelerated　aging　of　the　global　population　and　escalating　labor　costs,　more　service　robots　are　needed　to　help　people　perform　complex　tasks.　As　such,　human-robot　interaction　is　a　particularly　important　research　topic.　To　effectively　transfer　human　behavior　skills　to　a　robot,　in　this　study,　we　conveyed　skill-learning　functions　via　our　proposed　wearable　device.　The　robotic　teleoperation　system　utilizes　interactive　demonstration　via　the　wearable　device　by　directly　controlling　the　speed　of　the　motors.　We　present　a　rotation-invariant　dynamical-movement-primitive　method　for　learning　interaction　skills.　We　also　conducted　robotic　teleoperation　demonstrations　and　designed　imitation　learning　experiments.　The　experimental　human-robot　interaction　results　confirm　the　effectiveness　of　the　proposed　method.