The current status of vestibular system models.
Mathematical models of human vestibular system for dynamic space orientation, using control theory
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Mathematical models of human vestibular system for dynamic space orientation, using control theory
Linear constant dynamical system which approximates human input-output behavior in particular tracking tasks
Seat comfort and safety research since the early part of the century is reviewed. The approach blends empirical and theoretical human factors and technical knowledge of seated humans under static and dynamic conditions experienced on commercial aircraft.
SAINT (Systems Analysis of Integrated Networks of Tasks) is a network modeling and simulation technique for design and analysis of complex man machine systems. SAINT provides the conceptual framework for representing systems that consist of discrete task elements, continuous state variables, and interactions between them. It also provides a mechanism for combining human performance models and dynamic system behaviors in a single modeling structure. The SAINT technique is described and applications of the SAINT are discussed.
Mathematical models describing vehicle dynamics as well as human behavior may be useful in evaluating driver performance and in establishing design criteria for vehicles more compatible with man. In 1977, a two level model of driver steering behavior was developed, but its parameters were identified for clear visibility conditions only. Since driver performance degrades under conditions of reduced visibility, e.g., fog, the two level model should be investigated to determine its applicability to such conditions. The data analysis of a recently performed driving simulation experiment showed that the model still performed reasonably well under fog conditions, although there was a degradation in its predictive capacity during fog. Some additional parameters affecting anticipation and lag time may improve the model's performance for reduced visibility conditions.
An investigation was carried out to quantitatively evaluate left ventricular volume flow rate, momentum, force and impulse derived from application of conservation principles for mass and momentum of blood within the ventricle during the ejection phase. An automated digital image processing system was developed and applied to left ventricular angiograms which are computer processed and analyzed frame by frame to determine the dynamical relations by numerical methods. The initial experience with force and impulse has indicated that neither quantity seemed to be a sensitive indicator of coronary artery disease as evaluated by qualitative angiography for the particular patient group studied. Utilization of the dynamical relations in evaluating human left ventricular performance requires improved means of measurement and interpretation of clinical studies.
Two project areas were pursued: the intelligent cockpit and human problem solving. The first area involves an investigation of the use of advanced software engineering methods to aid aircraft crews in procedure selection and execution. The second area is focused on human problem solving in dynamic environments, particulary in terms of identification of rule-based models land alternative approaches to training and aiding. Progress in each area is discussed.
To better describe the linear-dynamic properties of the human visual-cortical response system, transient and steady state Visual Evoked Response Potentials (VERP) were observed. The stimulus presentation device provided both the evoking stimulus (flickering or pulsing lights) and a video task display. The steady state stimulus was modulated by a complex, ten frequency, sum-of-sines, wave. The transient VERP was the time-locked average of the EEG to a series of narrow light pulses (pulse width of 10 msec). The Fourier transform of the averaged pulses had properties that approximate band limited white noise, i.e., a flat spectrum over the frequency region spanned by the 10 summed sines. The Fourier transform of both the steady state and the transient evoked potentials resulted in transfer that are equivalent and therefore comparable. To investigate the effects of task loading on evoked potentials, a grammatical reasoning task was provided. Results support the relevancy of continued application of a systems engineering approach for describing neurosensory functioning.
A collection of technical papers are presented that cover modeling pilot interaction with automated digital avionics systems and guidance and control algorithms for contour and nap-of-the-earth flight. The titles of the papers presented are as follows: (1) Automation effects in a multiloop manual control system; (2) A qualitative model of human interaction with complex dynamic systems; (3) Generalized predictive control of dynamic systems; (4) An application of generalized predictive control to rotorcraft terrain-following flight; (5) Self-tuning generalized predictive control applied to terrain-following flight; and (6) Precise flight path control using a predictive algorithm.
A cognitive theory is presented that has relevance for the definition and assessment of situational awareness in the cockpit. The theory asserts that maintenance of situation awareness is a constructive process that demands mental resources in competition with ongoing task performance. Implications of this perspective for assessing and improving situational awareness are discussed. It is concluded that the goal of inserting advanced technology into any system is that it results in an increase in the effectiveness, timeliness, and safety with which the system's activities can be accomplished. The inherent difficulties of the multitask situation are very often compounded by the introduction of automation. To maximize situational awareness, the dynamics and capabilities of such technologies must be designed with thorough respect for the dynamics and capabilities of human information-processing.
The focus here is on the development of a dynamic strength model for humans. Our model is based on empirical data. The shoulder, elbow, and wrist joints are characterized in terms of maximum isolated torque, position, and velocity in all rotational planes. This information is reduced by a least squares regression technique into a table of single variable second degree polynomial equations determining the torque as a function of position and velocity. The isolated joint torque equations are then used to compute forces resulting from a composite motion, which in this case is a ratchet wrench push and pull operation. What is presented here is a comparison of the computed or predicted results of the model with the actual measured values for the composite motion.
An extended Fitt's law paradigm reaction time (RT) task was used to evaluate the effects of acceleration on human performance in the Dynamic Environment Simulator (DES) at Armstrong Laboratory, Wright-Patterson AFB, Ohio. This effort was combined with an evaluation of the standard CSU-13 P anti-gravity suit versus three configurations of a 'retrograde inflation anti-G suit'. Results indicated that RT and error rates increased 17 percent and 14 percent respectively from baseline to the end of the simulated aerial combat maneuver and that the most common error was pressing too few buttons.
New and innovative software technology is presented that provides a cost effective bridge for smoothly transitioning prototype software, in the field of planning and scheduling, into an operational environment. Specifically, this technology mixes the flexibility and human design efficiency of dynamic data typing with the rigor and run-time efficiencies of static data typing. This new technology provides a very valuable tool for conducting the extensive, up-front system prototyping that leads to specifying the correct system and producing a reliable, efficient version that will be operationally effective and will be accepted by the intended users.
Our research focuses on the problem of recovering from perturbations in large-scale schedules, specifically on the ability of a human-machine partnership to dynamically modify an airline schedule in response to unanticipated disruptions. This task is characterized by massive interdependencies and a large space of possible actions. Our approach is to apply the following: qualitative, knowledge-intensive techniques relying on a memory of stereotypical failures and appropriate recoveries; and quantitative techniques drawn from the Operations Research community's work on scheduling. Our main scientific challenge is to represent schedules, failures, and repairs so as to make both sets of techniques applicable to the same data. This paper outlines ongoing research in which we are cooperating with United Airlines to develop our understanding of the scientific issues underlying the practicalities of dynamic, real-time schedule repair.
At the highest level, the fundamental question addressed by this research is how to aid human operators engaged in dynamic fault management. In dynamic fault management there is some underlying dynamic process (an engineered or physiological process referred to as the monitored process - MP) whose state changes over time and whose behavior must be monitored and controlled. In these types of applications (dynamic, real-time systems), a vast array of sensor data is available to provide information on the state of the MP. Faults disturb the MP and diagnosis must be performed in parallel with responses to maintain process integrity and to correct the underlying problem. These situations frequently involve time pressure, multiple interacting goals, high consequences of failure, and multiple interleaved tasks.
Human operators of complex dynamic systems can experience difficulties supervising advanced control automation. One remedy is to develop intelligent aiding systems that can provide operators with context-sensitive advice and reminders. The research reported herein proposes, implements, and evaluates a methodology for activity tracking, a form of intent inferencing that can supply the knowledge required for an intelligent aid by constructing and maintaining a representation of operator activities in real time. The methodology was implemented in the Georgia Tech Crew Activity Tracking System (GT-CATS), which predicts and interprets the actions performed by Boeing 757/767 pilots navigating using autopilot flight modes. This report first describes research on intent inferencing and complex modes of automation. It then provides a detailed description of the GT-CATS methodology, knowledge structures, and processing scheme. The results of an experimental evaluation using airline pilots are given. The results show that GT-CATS was effective in predicting and interpreting pilot actions in real time.
We present a theoretical framework for relating continuous partial differential equation (PDE) models of excitable media to discrete cellular automata (CA) models on a randomized lattice. These relations establish a quantitative link between the CA model and the specific physical system under study. We derive expressions for the CA model's plane wave speed, critical curvature, and effective diffusion constant in terms of the model's internal parameters (the interaction radius, excitation threshold, and time step). We then equate these expressions to the corresponding quantities obtained from solution of the PDEs (for a fixed excitability). This yields a set of coupled equations with a unique solution for the required CA parameter values. Here we restrict our analysis to "trigger" wave solutions obtained in the limiting case of a two-dimensional excitable medium with no recovery processes. We tested the correspondence between our CA model and two PDE models (the FitzHugh-Nagumo medium and a medium with a "sawtooth" nonlinear reaction source) and found good agreement with the numerical solutions of the PDEs. Our results suggest that the behavior of trigger waves is actually controlled by a small number of parameters.
The frequency of ventricular premature beats (VPBs) has been related to the risk of mortality. However, little is known about the temporal pattern of occurrence of VPBs and its relationship to autonomic activity. Hence, we applied a general correlation measure, mutual information, to quantify how VPBs are generated over time. We also used mutual information to determine the correlation between VPB production and heart rate in order to evaluate effects of autonomic activity on VPB production. We examined twenty subjects with more than 3000 VPBs/day and simulated random time series of VPB occurrence. We found that mutual information values could be used to characterize quantitatively the temporal patterns of VPB generation. Our data suggest that VPB production is not random and VPBs generated with a higher value of mutual information may be more greatly affected by autonomic activity.