Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-28T10:04:37.577Z Has data issue: false hasContentIssue false

An Elemental Resource for the Human-Task Interface

Published online by Cambridge University Press:  10 March 2009

George V. Kondraske
Affiliation:
University of Texas at Arlington

Abstarct

The elemental resource model (ERM) attempts to provide a quantitative and straightforward framework for characterizing the human system, tasks, and their interface. It evolved in large part from the general systems performance theory (GSPT), which was developed first and independently. Resource constructs are used exclusively for modeling the abstract idea of system performance and for subsequent measurement of performance resource capacities. Resource economic principles provide a cause-and-effect description of the human-task interface. While argued to have immediate utility, it also provides the motivation to consider coordinated, collaborative, long-term developments that could facilitate effective decision making and technology utilization in rehabilitation.

Type
Special Section: Technology and Disability
Copyright
Copyright © Cambridge University Press 1995

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Behbehani, K., Kondraske, G. V., & Richmond, J.Investigation of upper extremity visuomotor control performance measures. IEEE Transactions on Biomedical Engineering, 1988, 35, 518–25.Google Scholar
2.Bendell, A., Disney, J., & Pridmore, W. A.Taguchi methods: Applications in world industry. London: IFS Publishers, 1988.Google Scholar
3.Bunge, M.Levels and reduction. American Journal of Physiology, 1977, 233, R75–R82.Google ScholarPubMed
4.Carollo, J. J., & Kondraske, G. V. The prerequisite resources for walking: Characterization using a task analysis strategy. In Leinberger, J. (ed.), Proceedings of the Ninth Annual IEEE Engineering in Medicine and Biology Society Conference, 1987, 357.Google Scholar
5.Carr, B.Head/neck control performance measurement and task interface model. M.S. thesis. Arlington: University of Texas at Arlington, 1989.Google Scholar
6.Chaffin, D. B., & Andersson, G. B. J.Occupational biomechanics. New York: John Wiley and Sons, 1984.Google Scholar
7.Fleischman, E. A., & Quaintance, M. K.Taxonomies of human performance. Orlando, FL: Academic Press, 1984.Google Scholar
8.Frisch, H. P. Man/machine interaction dynamics and performance analysis. In Proceedings of the NATO-Army-NASA Advanced Study Institute on Concurrent Engineering Toolsand Technologies for Mechanical System Design. New York: Springer- Verlag, 1993.Google Scholar
9.Gardner, H.The mind’s new science: A history of cognitive revolution. New York: Basi Books, Inc., 1985.Google Scholar
10.Gottlieb, G. L., Corcos, D. M., & Agarwal, G. C.Strategies for the control of voluntary movements with one mechanical degree of freedom. Behavioral and Brain Science, 1989, 12, 189250.Google Scholar
11.Hemami, H.Modeling, control, and simulation of human movement. CRC Critical Reviews in Bioengineering, 1988, 13, 134.Google Scholar
12.Jafari, M.Modeling and measurement of human speech performance toward pathology pattern recognition. Dissertation. Arlington, TX: The University of Texas at Arlington, 1989.Google Scholar
13.Jafari, M., Wong, K. H., Behbehani, K., & Kondraske, G. V.Performance characterization of human pitch control system: An acoustic approach. Journal of the Acoustical Society of America, 1989, 85, 1322–28.CrossRefGoogle ScholarPubMed
14.Jiang, B. C., & Ayoub, M. M.Modeling of maximum acceptable load of lifting by physical factors. Ergonomics, 1987, 30, 529–38.Google Scholar
15.Kondraske, G. V.A non-contacting human tremor sensor and measurement system. IEEE transactions on instrumentation and measurement, 1986, IM-35(2), 201–06.Google Scholar
16.Kondraske, G. V.A PC-based performance measurement laboratory system. Journal of Clinical Engineering, 1990, 15, 467–77.CrossRefGoogle Scholar
17.Kondraske, G. V. A working model for human system-task interfaces. In Bronzino, J. (ed.), The biomedical engineering handbook. Boca Ration: CRC Press, in press, 1995.Google Scholar
18.Kondraske, G. V. Experimental evaluation of an elemental resource model for human performance. In Harris, G. & Walker, C. (eds), Proceeding of the Tenth Annual IEEE Engineering in Medicine and Biology Society Conference, 1988, 1612–13.CrossRefGoogle Scholar
19.Kondraske, G. V. Human performance measurement and task analysis. In Enders, A. (ed.), Technology for independent living sourcebook, 2nd ed.Washington, DC: RESNA, 1988.Google Scholar
20.Kondraske, G. V. Human performance: Science or art? In Foster, K. (ed.), Proceedings of the Thirteenth Northeast Bioengineering Conference, 1987, 4447.Google Scholar
21.Kondraske, G. V.Looking at the study of human performance. SOMA: Engineering for the human body (ASME), 1987, 2, 50.Google Scholar
22.Kondraske, G. V. Measurement tools and processes in rehabilitation engineering. In Bronzino, J. (ed.), The biomedical engineering handbook. Boca Raton, FL: CRC Press, 1995, in press.Google Scholar
23.Kondraske, G. V. Neuromuscular performance: Resource economics and product-based composite indices. In Proceedings of the Eleventh Annual IEEE Engineering in Medicine and Biology Society Conference, 1989. 1045–46.Google Scholar
24.Kondraske, G. V. Quantitative measurement and assessment of performance. In Smith, R. V. & Leslie, J. H. (eds.), Rehabiltation engineering. Boca Raton, FL: CRC Press, 1990, 101–25.Google Scholar
25.Kondraske, G. V.The HPI shorthand notation system for human system parameters, Technical Report 92–001R VI.5. Arlington: University of Texas at Arlington Human Performance Institute, 1993.Google Scholar
26.Kondraske, G. V. Workplace design: An elemental resource approach to task analysis and human performance measurements. In Proceedings of the International Conference of the Association for the Advancement of Rehabilitation Technology, 1988, 608–11.Google Scholar
27.Kondraske, G. V., & Beehler, P. J.Applying general systems performance theory and the elemental resource model to gender-related issues in physical education and sport. Women in Physical Education and Sport Journal, in press, 1994.Google Scholar
28.Kondraske, G. V., Beehler, P. J., Behbehani, K., et al. Measuring human performance: Concepts, methods, and application examples. SOMA: Engineering for the Human Body (ASME), 1988, 613.Google Scholar
29.Kondraske, G. V., & Khoury, G. J. Telerobotic system performance measurement: Motivation and methods. In Cooperative Intelligent Robotics in Space III. SPIE. 1992, 161–72.CrossRefGoogle Scholar
30.Kondraske, G. V., & Standridge, R. Robot performance: Conceptual strategies. In Conf Digest IEEE Midcon/88 Technical Conference, Dallas, 359–62.Google Scholar
31.Matheson, L. N. Integrated work hardening. In Mayer, T., Mooney, V., & Gatchel, R. (eds.), Contemporary conservative care for painful spinal disorders. Philadelphia: Lea & Febiger, 1991, 346–63.Google Scholar
32.Maxwell, K. J., & Kondraske, G. V.A dynamic visual information meter for characterizing demands on human visual information processing resources, Technical Report TR92004R, Arlington: University of Texas at Arlington Human Performance Institute, 1992.Google Scholar
33.Mayer, T. G., & Gatchel, R. J.Functional restoration for spinal disorders: The sports medicine approach. Philadelphia: Lea & Febiger, 1988, 6677.Google Scholar
34.Meister, D.Conceptual aspects of human performance. Baltimore: Johns Hopkins University Press, 1989.Google Scholar
35.Moray, N.Where is capacity limited? A survey and model. Acta Psychologica, 1967, 27, 8492.CrossRefGoogle Scholar
36.National Research Council. Quantitative modeling of human performance in complex dynamic systems. Washington, DC: National Academy Press, 1990.Google Scholar
37.Navon, D., & Gopher, D.On the economy of the human processing system. Psychologic Reviews, 1979, 86, 214–53.Google Scholar
38.Neel, A.Theories of psychology: a handbook, Cambridge, MA: Schenkman Publishing Co., 1977.Google Scholar
39.Parnianpour, M., & Marras, W.S.Development of clinical protocols based on ergonomics evaluation in response to American Disability Act. In Rehabilitation Engineering Center Proposal to National Institute on Disability and Rehabilitation Research, Ohio State University, 1993.Google Scholar
40.Schoner, G., & Kelso, J. A. S.Dynamic pattern generation in behavioral and neural systems. Science, 1988, 239, 1513–20.Google Scholar
41.Turner, J. D.Integrated ergonomic system software development: Final report, contract No. NASA-30872. Boston, MA: Cambridge Research Associates, 1990.Google Scholar
42.Turvey, M. T., Shaw, R. E., & Mace, W. Issues in the theory of action: Degrees of freedom, coordinative structures, and coalitions. In Requin, J.(ed.), Attention and performance VII. Hillsdale, NJ: Lawrence Earlbaum Assoc., 1978.Google Scholar
43.Vasta, P.An investigation of the non-linear causal resource analysis method for task analysis and prediction of human performance. M.S. thesis. Arlington. University of Texas at Arlington, 1992.Google Scholar
44.Vasta, P., & Kondraske, G. V. Human performance engineering computer based design and analysis tools. In Bronzino, J. (ed.), The biomedical engineering handbook. Boca Raton: CRC Press, in press, 1995.Google Scholar
45.Vasta, P., & Kondraske, G. V.Standard conventionsfor kinematic and structural parameters for the ‘Gross Total Human’ link model, Technical Report 92–003R V1.0. Arlington: University of Texas at Arlington Human Performance Institute, 1992.Google Scholar
46.Vasta, P. J., & Kondraske, G. V. Performance prediction of an upper extremity reciprocal task using non-linear causal resource analysis. Proceedings, 16th Annual Engineering in Medical and Biology Society Conference, 1994.Google Scholar
47.Waddell, G.A new clinical model for the treatment of low back pain. Spine, 1987, 12, 632–46.Google Scholar
48.Weismer, G., & Liss, J. M. Reductionism is a dead-end in speech research, In Moore, C. A.Yorkston, K. M. & Beukelman, D. R. (eds.), Dysarthria and apraxia of speech. Baltimore: Paul H. Brookes Publishing Co., 1991.Google Scholar
49.Wickens, C. D.Engineering psychology and human performance. Columbus, OH: Charles E. Merrill Publishing Co., 1984.Google Scholar
50.World Health Organization (WHO). International classification of impairments, disabilities, and handicaps. WHO Chronicle. 1980. 34, 376.Google Scholar
51.Yen, S. S., & Kondraske, G. V. Shape measurement based on human perception. Conference Digest IEEE Midcon/90 Tech Conference, Dallas, 1990, 428–31.Google Scholar
52.Yen, S. S., & Kondraske, G. V.Machine shape perception: Object recognition based on need-driven resolution flexibility and convex-hull carving. In Proceedings of the conference on Intelligent Robots Computer Vision X: Algorithms Techniques, SPIE, 1992, 1607, 176–87.Google Scholar