ences. The work reported here suggests that signal detection theory can provide useful techniques for separating the effects of strategic processes from physiological processes. Although our work has not gone that far, it seems plausible that with the development of an adequate body of research, these tools could result in an empirically tractable account of strategic effects on movement control. Also, the use of a decision criteria measure would provide a basis for the comparison of results across studies. Once research is able to isolate the effects of the physiological and strategic processes, then the work on developing models of movement control that incorporate individual differences can begin in earnest.
So what does this methodological argument about how to approach understanding the causes of age-related differences in movement control have to say about real world problems faced by older adults? Obviously, there are many everyday situations where poorer movement control skills can have significant impact on performance. Two examples are driving a car and using a computer. In both cases, older adults must compensate for declining abilities to maintain acceptable (and in driving, safe) performance. In both of these cases, either training or redesign interventions could be used to improve performance. Yet for the interventions to be most effective, one must understand the causes of declining performance. If a primary cause of poorer performance is related to increased perceptual noise, augmenting feedback could improve performance. If increased motor noise is a primary cause of the age-related difference in performance, one could use changes in the gain ratio of the control system to compensate. The key is that one must understand the causes of age-related declines in performance before optimal design or training solutions can be developed.
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