Humans substantially outperform robotic systems in tasks that require physical interaction, despite seemingly inferior muscle bandwidth and slow neural information transmission. The control strategies that enable this performance remain poorly understood. To bridge this gap, this study examined kinematically-constrained motion as an intermediate step between the widely-studied unconstrained motions and sparsely-studied physical interactions. Subjects turned a horizontal planar crank in two directions (clockwise and counterclockwise) at three constant target speeds. With the hand constrained to move in a circle, non-zero forces against the constraint were measured. This experiment exposed two observations that could not result from mechanics alone, but may be attributed to neural control composed of dynamic primitives. A plausible mathematical model of interactive dynamics (mechanical impedance) was assumed and used to 'subtract' peripheral neuromechanics. This method revealed a summary of the underlying neural control in terms of motion-a zero-force trajectory. The estimated zero-force trajectories were approximately elliptical and their orientation differed significantly with turning direction. That is consistent with control using oscillations to generate an elliptical zero-force trajectory. However, for periods longer than 2-5 seconds, motion can no longer be perceived or executed as periodic. Instead, it decomposes into a sequence of submovements, manifest as increased variability. These quantifiable performance limitations support the hypothesis that humans simplify this constrained-motion task by exploiting at least three primitive dynamic actions: oscillations, submovements, and mechanical impedance.