Michael P. Clamann

Adaptive automation of human-machine system information-processing functions.

The goal of this research was to describe the ability of human operators to interact with adaptive automation (AA) applied to various stages of complex systems information processing, defined in a model of human-automation interaction. Forty participants operated a simulation of an air traffic control task. Automated assistance was adaptively applied to information acquisition, information analysis, decision making, and action implementation aspects of the task based on operator workload states, which were measured using a secondary task. The differential effects of the forms of automation were determined and compared with a manual control condition. Results of two 20-min trials of AA or manual control revealed a significant effect of the type of automation on performance, particularly during manual control periods as part of the adaptive conditions. Humans appear to better adapt to AA applied to sensory and psychomotor information-processing functions (action implementation) than to AA applied to cognitive functions (information analysis and decision making), and AA is superior to completely manual control. Potential applications of this research include the design of automation to support air traffic controller information processing.

Comparison of Performance Effects of Adaptive Automation Applied to Various Stages of Human-Machine System Information Processing

Limitations in automation (expert system) capabilities and negative human performance consequences of automation in complex systems have led to the contention that use of computer assistance in high-level human-machine system information processing may be inappropriate. Adaptive automation (AA) has been explored as a solution to these problems; however, research has focused on the performance effects of dynamic control allocations of early sensory and information acquisition functions between human operators and computer controllers of complex systems. It has examined to a limited extent the human performance and workload effects of AA of cognitive tasks, such as decision-making, or of psychomotor functions such as response execution. This research compared the affects of AA applied to psychomotor tasks and cognitive tasks, including information monitoring, information analysis, decision-making, and action implementation, on overall human-machine system performance. Results demonstrated that operators are better able to adapt to AA when applied to lower level functions, such as information acquisition and action implementation, as compared to AA of information analysis and decision making tasks. The results also provided support for the use of AA, as compared to completely manual control.

Evaluation of an Augmented Virtual Reality and Haptic Control Interface for Psychomotor Training

This study investigated the design of a virtual reality (VR) simulation integrating a haptic control interface for motor skill training. Twenty-four healthy participants were tested and trained in standardized psychomotor control tasks using native and VR forms with their nondominant hands in order to identify VR design features that might serve to accelerate motor learning. The study was also intended to make preliminary observations on the degree of specific motor skill development that can be achieved with a VR-based haptic simulation. Results revealed significant improvements in test performance following training for the VR with augmented haptic features with insignificant findings for the native task and VR with basic haptic features. Although performance during training was consistently better with the native task, a correspondence between the VR training and test task interfaces led to greater improvement in test performance as reported by a difference between baseline and post-test scores. These findings support use of VR-based haptic simulations of standardized psychomotor tests for motor skill training, including visual and haptic enhancements for effective pattern recognition and discrete movement of objects. The results may serve as an applicable guide for design of future haptic VR features.

APPLICABILITY OF USABILITY EVALUATION TECHNIQUES TO AVIATION SYSTEMS

Research in the field of human-computer interaction (HCI) has shown that early usability evaluation of human interfaces can reduce operator errors by optimizing functions for a specific population. HCI research has produced many methods for evaluating usability, which have proven effective in developing highly complex computer systems. Given the importance of the human in the loop in aviation systems, it is possible that advanced commercial cockpit and air traffic control systems may benefit from systematic application of usability research. This article identifies the special requirements of the aviation domain that will affect a usability evaluation and the characteristics of evaluation methods that may make them effective in this context. Recommendations are made of usability evaluation techniques, or combinations of techniques, most appropriate for evaluating complex systems in aviation technology.

Authority in Adaptive Automation Applied to Various Stages of Human-Machine System Information Processing

The goal of this study was to assess the performance and workload effects of applying adaptive automation (AA) to four stages of human-machine system information processing (information acquisition, information analysis, decision-making, and action implementation) and facilitating dynamic function allocations (DFAs) through two levels of computer authority (suggestion and mandate). The research was to provide insight into any interaction between these aspects of AA design. It was hypothesized that higher level automation, such as information analysis and decision making, would be more compatible with computer mandated allocations, while lower levels, such as information acquisition and action implementation, would be more effective under partial human control (computer suggestion and human veto). Results demonstrated that the effectiveness of AA is dependent upon both the type of automation presented to an operator and the type of invocation authority designed into the system. Performance with AA of information acquisition was superior to performance under decision automation. When using automated assistance, human acceptance of computer suggestions was superior to computer mandates. The results of this study may serve as an applicable guide for AA design in future complex systems.

Validation of a Haptic-Based Simulation to Test Complex Figure Reproduction Capability

The objective of this research was to develop a new computer-based system for psychomotor skill assessment. The focus was on the simulation of the Rey-Osterrieth Complex Figure (ROCF) reproduction test incorporating a haptic interface. Various system functions were created to support customized testing protocols that are based on specific user requirements, facilitate semiautomated scoring of tests, and produce quantitative test output. Advanced technologies of pattern recognition were reviewed and adapted for the system development. This approach yielded an application for recording freehand drawings and recognizing and normalizing drawing strokes for semiautomated scoring according to a standard. The new simulator system was validated by comparison with traditional paper-based tests in which participants were asked to use their nondominant hand to simulate a minor motor impairment. Results demonstrated the simulator to be sensitive to functional differences between dominant and nondominant hand use. The computerized scoring software also appeared to be valid for generating ROCF scores, which were consistent with manual scores determined by a trained rater for the same drawing stimuli.

The Effects of Haptic and Visual Aiding on Psychomotor Task Strategy Development During Virtual Reality-Based Training:

The objective of this work was to observe how haptic and visual assistance in virtual reality (VR) task performance can affect individual strategy selection. Participants received psychomotor training with a VR simulation of a block design (BD) test, as part of the Wechsler Abbreviated Scale for Intelligence. Training included one of three forms of assistance: haptic, visual, or a combination of both. Strategy was evaluated in terms of accuracy in orienting blocks in pattern reproduction. Results revealed participants to develop personal strategies when receiving only haptic assistance. When receiving visual assistance, participants tended to rely on the aiding instead of a strategy. Participants performed best with visual assistance and showed significant improvement during training, based on the aiding. Participants also performed well with the combination of haptic and visual assistance, but showed little improvement during training. The results confirm that properly-designed assistance can help users with different perceptual styles (e.g., field dependence) benefit from more efficient strategies.

Evaluation of a Virtual Reality and Haptic Simulation of a Block Design Test

The objective of this research was to develop a computer-based system for psychomotor skill assessment and training. The focus was on virtual reality (VR) simulation of an established pattern assembly task incorporating a haptic interface. A prototype VR and haptic-based system was developed to replicate established testing protocols, facilitate automated test scoring, and produce quantitative test output. The prototype was also compared to a native version of the test. Participants completed multiple training trials of the VR or native tests. Training effects were measured by comparing performance on objective baseline and post-tests administered before and after training, respectively. Results revealed training in either the VR or the native versions of the task to produce significant (p<;0.0001) performance increases from baseline, but neither version resulted in significant improvements over the other. The VR-haptic simulation was found to represent a viable psychomotor test and training method.

Assessing Goal-Directed Three-Dimensional Movements in a Virtual Reality Block Design Task

This study investigated three-dimensional (3D) goal-directed movements in a virtual reality (VR) simulation of a standardized psychomotor control task. Movement trajectories were collected from 22 subjects and parsed based on an existing two-phase model of motor control including ballistic and correction phases. Kinematic measures were also acquired to provide further insight into motor skill learning. Results revealed kinematic measures of total numbers of sub movements and numbers of sub movements in the correction phase to be significantly correlated with psychomotor task scores. A predictive model applied to the 3D movements revealed the correction phase movements to be more predictive of psychomotor performance than the ballistic phase. Findings indicate a greater degree of fine motor skill was required for performance of the psychomotor control task. This research supports the use of high resolution kinematic measures as reliable predictors of psychomotor task performance.

Effects of Laptop Touchpad Texturing on User Performance

This research assessed user performance with different laptop touchpad textures. In specific, the study measured discrete movement task time and accuracy. It was hypothesized that texturing would increase task times but improve accuracy by providing users with tactile references. A variable representing the frictional potential of pads was introduced into an established model of discrete movement performance (Fitts’ Law) in an attempt to accurately model user performance under experimental task conditions. Results revealed touchpad texturing to degrade task performance. However, accuracy in pointing tasks was not significantly affected. Results also revealed that the expanded form of Fitts’ Law, including a parameter for representing the frictional potential of pad texturing, was more predictive of actual movement times than the original form of the Law. Results from the study increase understanding of the effects of touchpad texture on human motor control behavior and provide some guidance for future pad design.