This paper presents a novel approach to infer navigational intent of the user of a walker, based on measuring forces and moments applied to the walker's handles. While there are many types of "intent" that could be inferred for a given user action, the experiments conducted here focused on the determining user's navigational intent, i.e. their desired heading. Our experiments used two 6-DOF force/ moment sensors on the walker's handles and a digital motion capture system to correlate applied force with actual motion. Preliminary results revealed that the intent to turn, represented by changes in the heading angle, highly correlates with the overall turning moment around the vertical axis as well as the side forces applied by the user. Other force/moment components reveal additional information, such as support needs. The inferred user intent will be incorporated into a passive shared steering control system for the walker.
Abstract-This paper describes a method that passively assesses basic walker-assisted gait characteristic, including heel strikes, toe-off events, as well as stride time, double support and right & left single support phases using only force-moment measurements from the walker's handles. The passively derived gait characteristics were validated against motion capture gait analysis and showed good correlations. This research is part of an effort that aims to identify user intent, from measuring forces and moments exerted on the handles of the walker as well as from perceiving the environment, and to incorporate identified intent into a passive shared steering control system for the walker. The primary focus of the work leading to this paper is to identify the double support phase, and to engage the steering control at the beginning of this phase to maximize the user's stability. However, the application of the method presented and the instrumented walker can be extended to longitudinal outside the lab Gait assessment.
A multibody dynamics model integrated with space-time constraints based optimization is presented in this paper for generating optimal trajectories of human lifting movements. “Space-time constraints” is a two-point boundary value dynamic optimization technique developed for animation of computer graphics characters and has a significant potential for biomechanics and other mechanical movement based dynamic optimization problems. Optimization results demonstrate the ability to consider different preferences for minimizing the loading of specific joints such as an ankle, or a knee, or a shoulder during the lifting motion and the resulting lifting trajectories are shown to be different. Lumped muscle models to generate the joint torques are incorporated at five joints to model the actuation effects of the muscular system during the dynamic movement. The dynamic optimization is then based on the muscle activation parameters instead of the traditionally used joint torques. The muscle activation model optimization is shown to correlate better with the actual motion tests conducted by the VICON video capture and test data analysis system.
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