Modeling Hand Movements in a Sequential Reach Task with Continuous Material

Abstract

Manual precision tasks are a staple in many manufacturing and product assembly jobs. Sequential reach tasks in the assembly of products made with continuous material (e.g., textile threads and electrical wire), wherein operators manually route material to sequential target locations comprising multiple pulleys and idlers during routine operations, present unique physical and temporal demands on operators. Accurate predictions of human movement and task performance are important for evaluating and improving the ergonomics of such jobs. While the ergonomics literature is replete with models to predict speed-accuracy relationships during discrete reach movements in the Fitts’ law paradigm, corresponding studies to quantify human performance in sequential reach tasks while manipulating continuous material are absent. Thus, the goal of this research was to quantify the spatial and temporal properties of hand movements in sequential reach tasks that involve handling continuous material. Based on a series of human factors experiments, an original empirically-based model leveraging functional statistical analysis was developed to predict reach trajectory shapes, speed profiles, and task completion times when reaching to coplanar sequential targets with task parameters (e.g., target tolerances and location, reach direction and amplitude, and line of sight availability) as predictors. The analysis of measured trajectory shapes and speed provided unique theoretical insights into the speed-accuracy trade-off and the modulation of movement generation and speed control in sequential reach movements with continuous material. The resultant prediction model is compatible with digital human modeling software and promises new simulation capabilities in the ergonomics analysis of industrial tasks that require manual precision handling of light-weight flexible material.