Psychophysiology has a long tradition within human factors (Boucsein & Backs, 2000) and has especially contributed to the present understanding of mental workload (Gaillard & Kramer, 2000). Mental workload is often considered to reflect the costs associated with a person's expenditure of limited-capacity information-processing resources to keep task performance within specification and thus is a function of both the person's abilities and the task demands on his or her abilities (Gopher & Donchin, 1986). Many methods of assessing mental work-load have been proposed, each with its own advantages and disadvantages (O'Donnell & Eggemeier, 1986; Tsang & Wilson, 1997). Psychophysiological methods have been used to assess mental workload in domains such as aviation because measurement of responses such as heart rate usually does not interfere with task performance and because psychophysiological responses are sometimes more sensitive to task demands than are performance measures (Kramer & Weber, 2000). The present study examined whether a new approach to the analysis and interpretation of cardiac psychophysiological responses that has been useful for assessing mental workload in the aviation domain is also useful for simulated driving.
By far, the most popular cardiac response used by the human factors community is heart rate (Wilson & Eggemeier, 1991). The heart is dually innervated by the sympathetic and parasympathetic branches of the autonomic nervous system (ANS), and these two branches have opposing effects on heart rate: sympathetic activation increases heart rate, whereas parasympathetic activation decreases heart rate. In the classic model of ANS function (e.g., Cannon, 1959), sympathetic and parasympathetic activity are reciprocally coupled--that is, sympathetic activation occurs concomitantly with parasympathetic inhibition and vice versa. According to the classic model, heart rate change in response to varying task demands would always be the result of some unknown combination of reciprocal change in both autonomic branches.
However, Backs (1995) reviewed studies from the aviation domain that used heart rate as an index of pilot mental workload and found many instances in which heart rate did not change in a manner consistent with the classic ANS model. He suggested that a newer model of ANS function proposed by Berntson, Cacioppo, and Quigley (1991, 1995) could better account for the observed heart rate results. The Berntson et al. model of autonomic space subsumes the classic model of ANS function and instead proposes multiple "modes of autonomic control" (1991, p. 459)." The modes of autonomic control can be represented as a two-dimensional "autonomic space" (see Figure 1), which can be illustrated by axes plotting parasympathetic activity on the ordinate and sympathetic activity on the abscissa. Vectors on the positive diagonal represent the classic coupled reciprocal modes of autonomic control (sympathetic activation with parasympathetic inhibition, or the reverse). Vectors on the negative diagonal represent coupled nonreciprocal modes of control (coactivation and coinhibition), in which the sympathetic and parasympathetic branches increase or decrease together. Vectors parallel to one axis represent uncoupled modes of control, in which activity in one branch changes but activity in the other branch does not. Table 1 presents the autonomic control mode taxonomy and the effects of change along each mode of autonomic control on heart rate.
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Backs (1995) described two important limitations in using heart rate to make inferences about mental workload, which are evident in Table 1. Both limitations exist because heart rate alone is uninformative about the psychological-physiological mapping responsible for the response. The first is that sensitivity can be limited because heart rate may not change with varying task demands, even though sympathetic and parasympathetic activity may change greatly. The second limitation is that equivalent heart rate changes can occur as the result of many different patterns of neural input, which therefore limits the diagnosticity of heart rate in localizing the effects of task demands to specific information-processing resources.
Knowledge of the underlying mode of autonomic control can potentially overcome both of the inferential limitations with heart rate because different control modes may reflect distinct psychological-physiological mappings (Berntson et al., 1991). Sensitivity can increase because change in task demand that fails to significantly elicit heart rate change may be detectable in autonomic space. This increase in sensitivity will especially occur when the mode of autonomic control is one of the coupled nonreciprocal modes, coactivation or coinhibition.
Similarly, diagnosticity can increase because a given heart rate response to changes in task demands may be attributable to control modes that reflect the engagement of specific processing resources. Increased heart rate can occur as a result of reciprocally coupled sympathetic activation, uncoupled sympathetic activation, uncoupled parasympathetic inhibition, coactivation (in which sympathetic activation exceeds parasympathetic activation), of coinhibition (in which parasympathetic inhibition exceeds sympathetic inhibition). Research suggests that different task manipulations elicit different modes of autonomic control for heart rate (Backs, 2001). For example, increasing task difficulty in a visual-manual tracking task by increasing the order of control or by increasing the memory load of a secondary memory task will both result in increased heart rate. However, the two manipulations elicit different modes of control as determined by factor analysis of multiple cardiovascular measures: Increasing the order of control from velocity to acceleration elicits uncoupled parasympathetic inhibition, whereas increasing the memory load of the secondary task elicits uncoupled sympathetic activation (Backs, 1995, 1998).
However, noninvasive measures of the underlying sympathetic and parasympathetic activity are needed to identify the autonomic control modes for heart rate. Pre-ejection period (PEP) obtained from the impedance cardiogram and respiratory sinus arrhythmia (RSA) obtained from heart rate variability have been validated as measures of sympathetic and parasympathetic cardiac innervation, respectively, in dual pharmacological blockade studies (Cacioppo et al., 1994). PEP and RSA were used in the present study to assess cardiac ANS activity.
The present research examined whether the autonomic control mode approach assessed driver mental workload during simulated driving better than did heart rate. Driving difficulty was manipulated by varying the curvature of the road driven (sharper curves have a greater workload) and whether or not the road was occluded (greater workload) while driving. Performance, subjective, and physiological measures have all been found to differ across curves of different radii (Godthelp, 1986; Richter, Wagner, Heger, & Weise, 1998; Tsimhoni & Green, in press; Tsimhoni, Yoo, & Green, 1999). Driving performance deteriorates, subjective difficulty increases, and heart rate generally increases as the degree of curvature increases.
Visual occlusion is a technique used to assess the visual demand of driving (Senders, Kristofferson, Levison, Dietrich, & Ward, 1967). Briefly, the logic of the visual occlusion technique is that the more difficult the driving situation (the sharper the curve, the narrower the road, etc.), the more the driver needs to look at the road. There are at least 10 ways this can be achieved (Green, 2001), which involve various combinations of drivers closing their eyes, blocking their view of the scene with goggles, of, in a simulator, blanking the …