Mental Workload Assessment: Primary, Secondary and Subjective Methods, Study notes of English Language

Download Mental Workload Assessment: Primary, Secondary and Subjective Methods and more Study notes English Language in PDF only on Docsity! Hancock Mental Workload 1 MENTAL WORKLOAD Instructor: Dr. Peter Hancock Lecture Overview Just how hard are you working right now? I am assuming that you’re reading these lecture notes and looking to understand the information they contain. The action of reading takes some effort and if I look at your eyes I could tell they were moving, but other than that I would have some rather severe difficulties in measuring the demands currently imposed on you and your reaction to them. But this is not so for physical work! Here, I can use all the methods of physics, biochemistry, biomechanics, indeed even ergonomics and the like to ask simple and soluble questions about your current physical workload and your muscular response. And herein lies the problem. Traditional work measurement in Industrial Engineering and Ergonomics has been predominantly about physical effort where the muscle is the engine of action. Now, when we move on to the brain as the major source of work we deal with a very different form of measurement challenge. What might be surprising to the uninitiated is that the brain takes about a third of the resting metabolic energy produced by the body, and this can increase during especially intense mental work. Thus, although specific signals within the brain are faint and difficult to distinguish, the mass action of the brain itself is extensive. As we shall see, recent brain imaging techniques each try to evaluate certain aspects of this mass action and use various indicators to achieve this aim. However, the four primary methods of mental workload assessment have held sway for the last two decades and continue to dominate, even as these new techniques emerge. Thus, we shall here deal with these four techniques, but with your awareness that brain measurement technologies are a volatile and changing enterprise in which new developments are constantly emerging. Hancock Mental Workload 2 Primary Task Performance If one wishes to know how well an individual is performing cognitive work, the first and most obvious method is to measure their outcome efficiency – in short, their primary task performance. In many practical situations, these measures, which emerge from the very origin of time and motion studies, are the sole representation that the assessor requires. For example, in piece work, the rate of production combined with the rate of item rejection is used to calculate the remuneration for the individual. The faster and more accurately the individual works, the higher the pay level and presumably, the higher the level of cognitive demand. However, this remains an issue for employers. For example, what if an individual is highly productive in cognitive work but is working with much spare capacity? Does this mean the employer could get more out of that individual? What happens when the cognitive work is creative and not repetitive? How many great ideas equals a number of units of rote work? These are difficult questions to answer and actually underlie the intrinsic contract that work creates between the worker and the employer. No wonder the question mental of workload is not one of scientific definition and interest alone. However, the fundamental shortfall of primary task measures is that they reflect work as is being presently accomplished. Let’s suppose we are trying to use primary task measures to assess a critical process. We know that if we impose too much cognitive load on the individual (say 25 aircraft on an air-traffic controller), they will not be able to accomplish the task and catastrophe may follow. However, this failure is non-linear (see Hancock & Warm, 1989), and so as we add aircraft we will not see the failure coming if primary task performance is all that we have. In essence, primary task reflections are good for the present moment but can be very dangerous if we want to use them to predict future cognitive performance limits. In some cases, the process is not one that will suffer excessively from this handicap, in other processes it is the difference between life and death. Thus, while primary Hancock Mental Workload 5 through which to derived mental workload values. Becoming more and more popular as techniques evolve in sophistication and reliability, physiological measures are currently in vogue. As indicated by Hancock, Meshkati and Robertson (1985), one can either measure reflections in the peripheral or the central nervous system. The degree to which one gets accurate and reliable data often depends upon the proximity of the measurement (both physically and systemically) to the site of action. That is, measuring memory demands may be done via toe-nail growth rate, but this is a remote site and has poor resolution. It is much better to examine brain activation in the memory- stimulated regions. In class we shall discuss several such measurement techniques. I would ask you to identify one and be prepared to talk about its relative advantages and disadvantages. Application Areas Understanding mental workload and being able to provide a reliable and accurate measure of this form of workload on an individual basis may be a very satisfying scientific achievement. However, the realization of such a goal goes well beyond the realm of academics. There are an almost limitless vista of potential applications and here we consider two recent and highly pertinent examples, with your recognition that there are many, many others. Earlier in our class, we talked about human interaction with automated and semi-automated systems. One of the major advances in that realm was the idea of adaptive human-machine systems. This conception seeks to understand the state of the machine and the state of the human and then reconcile these respective states with the on-going needs of the combined human-machine system toward some mutual goal. Obviously, to accomplish this goal we need to know about the machine and need to be able to express this status in human terms. However, we also need to be able to capture the operator state and express their situation in machine terms (largely quantitative assessment). Accurate mental workload measures are thus absolutely vital here. Hancock Mental Workload 6 In a more recent conceptual advance, Parasuraman (2003) has suggested the possibility of generalizing this basic conception by tying together the principles of ergonomics with those of neuroscience. This neuron-ergonomics initiative takes the idea of direct connections between brain and machine to the next level. Here, the diagnostic capabilities of modern neuroscience are matched to the machine mediation of ergonomics to allow direct brain control of complex systems while permitting the recursive loop of direct brain input from the external environment. This is a particularly exciting development and mental workload assessment, as the measure of mass action, holds much promise to help push such ideas forward. In class, we will also consider other practical uses of reliable workload measures. Current Learning Objectives After the evident change in the ‘currency’ of work, from ergs to bytes, the comparable change in work measurement has gone from assessment of muscular action to the comprehension of mental or cognitive load. As is clear from our present lecture, the brain poses many more problems for such assessment compared to the muscle and we have had to search for an adapt any number of methodologies to achieve this goal. Following the present lecture, you should now understand the four major methods of such assessment and be able to draw from a number of examples in each method. You should understand the importance of mental workload assessment together with a number of barriers that prevent our complete comprehension at present., Finally, you should now be familiar with some recent brain imaging and assessment techniques which hold particular future promise and you should be cognizant of the advanced uses that such measures can be put to including adaptive automation systems and neuroergonomics applications. Hancock Mental Workload 7 LECTURE READINGS Hancock, P.A. & Meshkati, N. (Eds.). (1988). Human mental workload. Amsterdam: North-Holland. Hancock, P.A., Meshkati, N., & Robertson, M.M. (1985). Physiological reflections of mental workload. Aviation, Space, and Environmental Medicine, 56, 1110-1114. Hancock, P.A., & Chignell, M.H. (1988). Mental workload dynamics in adaptive interface design. IEEE Transactions on Systems, Man, and Cybernetics, 18, 647-658. Hancock, P.A., & Szalma, J.L. (2003). The future of Neuroergonomics. Theoretical Issues in Ergonomic Science, 4 (1), 238-249. Meshkati, N., Hancock, P.A., & Rahimi, M. (1989). Techniques of mental workload assessment. In: J. Wilson (Ed.). Evaluation of human work: practical ergonomics methodology. (pp. 605-627) London: Taylor and Francis. Meshkati, N., Hancock, P.A., Rahimi, M., & Dawes, S.M. (1995). Techniques of mental workload assessment. In: J. Wilson and E.N. Corlett, (Eds.). Evaluation of human work: A practical ergonomics methodology. (pp. 749-782) (Second Edition), London: Taylor and Francis. Parasuraman, R. (2003). Neuroergonomics: Research and practice. Theoretical Issues in Ergonomic Science, 4 (1), 5-20. Wickens, C.D. (1984). Processing resources in attention. In: R, Parasuraman and D.R. Davies (Eds.). Varieties of attention. (pp. 63-102), Orlando: Academic Press.