ROOct 18, 2017
First-Person Perceptual Guidance Behavior Decomposition using Active Constraint ClassificationAndrew Feit, Berenice Mettler
Humans exhibit a wide range of adaptive and robust dynamic motion behavior that is yet unmatched by autonomous control systems. These capabilities are essential for real-time behavior generation in cluttered environments. Recent work suggests that human capabilities rely on task structure learning and embedded or ecological cognition in the form of perceptual guidance. This paper describes the experimental investigation of the functional elements of human motion guidance, focusing on the control and perceptual mechanisms. The motion, control, and perceptual data from first-person guidance experiments is decomposed into elemental segments based on invariants. These elements are then analyzed to determine their functional characteristics. The resulting model explains the structure of the agent-environment interaction and provides lawful descriptions of specific perceptual guidance and control mechanisms.
HCMar 30, 2015
Towards Data-Driven Hierarchical Surgical Skill AnalysisBin Li, Berenice Mettler, Timonthy M. Kowalewski
This paper evaluates methods of hierarchical skill analysis developed in aerospace to the problem of surgical skill assessment and modeling. The analysis employs tool motion data of Fundamental of Laparoscopic Skills (FLS) tasks collected from clinicians of various skill levels at three different clinical teaching hospitals in the United States. Outcomes are evaluated based on their ability to provide relevant information about the underlying processes across the entire system hierarchy including control, guidance and planning.
HCNov 14, 2013
Hierarchical Model of Human Guidance Performance Based on Interaction Patterns in BehaviorBerenice Mettler, Zhaodan Kong
This paper describes a framework for the investigation and modeling of human spatial guidance behavior in complex environments. The model is derived from the concept of interaction patterns, which represent the invariances or symmetries inherent in the interactions between an agent and its environment. These patterns provide the basic elements needed for the formalization of spatial behavior and determine a natural hierarchy that can be unified under a hierarchical hidden Markov model.