Movement Intermittency and Variability in Human Arm Movements

Human reaching and tracking movements exhibit a multipeaked speed profile which is commonly interpreted as evidence for submovements. As the movement gets slower, the individual peaks stand out more distinctly, accompanied by an increase in the number of the peaks. This phenomenon corresponds to non-smoothness or intermittency in the movement. In this study, we evaluate two potential sources proposed in the literature for the origins of movement intermittency and conclude that intermittency is more likely due to noise in the neuromuscular system as opposed to a central movement planner that generates intermittent plans. We also discuss our results’ relevance to movement variability and noise models. Doeringer and Hogan [1] proposed two possibilities as the source of intermittency: (1) A central movement planner that utilizes (simple) submovements to generate plans for complex movements. (2) Noise getting imposed on the plan along the neuromuscular circuitry. Although they did not arrive at a final conclusion on the source of intermittency, they stated that interpreting peaks in tangential speed profiles as incomplete blending of submovements would lead to a conclusion favoring the central planner option. We hypothesize that movement intermittency evaluated at various locations along the human arm during a constant speed tracking task will increase in the distal direction. If verified, this increase in distal direction indicates noise as the major source of intermittency since the most natural explanation is a noise mechanism; the intermittency would be amplified due to additional noise being interjected (through joint rotations connected in a serial fashion) along the arm in the distal direction. In contrast, intermittency in the original movement plan would be expected to produce similar intermittency levels for all joints along the arm. We have designed an experiment to test our hypothesis. In the experiment, five participants completed a circular tracking task by tracking a pointer on an LCD screen with their fingertip. All participants provided informed consent approved by the Institutional Review Boards of both institutions. Motion capture markers were attached on the bony parts of the arm on the shoulder, elbow, wrist joints and on the nail of the index finger as illustrated in Fig. 1. 3D trajectories of the markers were recorded using a Vicon motion capture system with ten high resolution MX 40 cameras at a sampling rate of 50 Hz.