I Meant to Do That: Determining the Intentions of Action in the Face of Disturbances

A fresh perspective on dissecting action into discrete submotions

The hypothesis that reaching motions are constructed from discrete components has been explored since the earliest scientific investigations of human movement, although composition specifics have been contentious. We reinspect this process by analyzing the underlying motor intent (rather than actual motion) using our recently-developed intent determination technique. First, synthetic data analysis was used to determine our accuracy in detecting submotion events. Next, we evaluated this on healthy reaching movements and overcame the problem of indistinguishably blended submotions by exposing subjects to strong, abruptly changing forces, which lead to clear corrections identifiable using direction-based clustering. We were able to accurately recover submotion parameters and identify patterns in submotion count, peak kinetic energy, and peak-to-peak duration. These values were all exponentially distributed, which implies that selection of submotions may follow simple rules. This provides a novel opportunity to investigate human motor action using the tools of statistics.

Reaching is Better When You Get What You Want: Realtime Feedback of Intended Reaching Trajectory Despite an Unstable Environment

Improvements in human-machine interaction may help overcome the unstable and uncertain environments that cause problems in everyday living. Here we experimentally evaluated intent feedback (IF), which estimates and displays the human operator's underlying intended trajectory in real-time. IF is a filter that combines a model of the arm with position and force data to determine the intended position. Subjects performed targeted reaching motions while seeing either their actual hand position or their estimated intent as a cursor while they experienced white noise forces rendered by a robotic handle. We found significantly better reaching performance during force exposure using the estimated intent. Additionally, in a second set of subjects with a reduced modeled stiffness, IF reduced estimated arm stiffness to about half that without IF, indicating a more relaxed state of operation. While visual distortions typically degrade performance and require an adaptation period to overcome, this particular distortion immediately enhanced performance. In the future, this method could provide novel insights into the nature of control. IF might also be applied in driving and piloting applications to best follow a person's desire in unpredictable or turbulent conditions.