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The availability of force feedback is a powerful addition to a virtual environment. By sensing the position of the fingers relative to a virtual object, such as a simulated rubber ball, the system can introduce force cues as the user closes his or her hand around the virtual object. With suitable sensors and actuators, the object can be made to feel stiff or spongy by systematically manipulating the characteristics of the force cues as a function of the position and motion of the fingers relative to the position of the object. In this manner, it is possible to create haptic images of virtual objects (a further defining characteristic of VEs).
Some Psychological Considerations
Because human beings are an essential component of all synthetic environment (SE) systems, there are very few areas of psychology that are not relevant to the design, use, and evaluation of SE systems. For example, if the system under consideration is a virtual environment (VE) system that is intended to provide realistic simulations, then all the issues relevant to the identification of the effective stimulus in real environments, as well as the issues that focus on how equivalent perceptions or responses can be achieved with more simply synthesized artificial stimuli, must be examined. If it is a VE system that is intended to maximize information transfer to the user and incorporates special distortions for this purpose, or if it is a teleoperator system that incorporates a non-anthropomorphic telerobot, then all the issues relevant to the perception of, adaptation to, and learning about altered perceptual cue systems must be considered. In addition, to the extent that the system can be thought of as an extension of traditional manual control systems, many of the concepts and findings relevant to such systems are likely to be applicable. Further issues arise in connection with higher-level processes related to learning and the formation of problem-solving strategies and cognitive models, as well as with the effects of SE experience on affect, motivation, personality, etc. A similarly broad range of issues is generated when one scans across the various application areas of SE systems
The topics covered in this chapter—which represent only a minute sample of all relevant topics—were chosen to illustrate some of the types of issues that need to be considered. Although the topic of discomfort
obviously contains elements outside the domain of psychology, it is included here for convenience.
Resolution, Illusions, And Information Transfer
Perhaps the most obvious kinds of knowledge about human perception and performance that are needed to design cost-effective SE systems concern the resolution of the human's input and output systems and the way in which effective resolving power is changed as these systems are integrated with SE interface systems having various kinds of displays and controls. (The term resolution refers here to the ability to separate out and independently sense different signals as well as to detect small changes in isolated signals.) Given such knowledge, one can then examine implications for task performance for various types of tasks, and the cost-performance trade-offs for these tasks.
Knowledge of normal human resolving power on the input side, i.e., the sensory side, allows one to predict the display resolution beyond which finer resolution could not be perceived and would therefore be wasted. A similar statement holds for the output, i.e., control, side. Although knowledge of human resolving power in vision and audition is incomplete, it is sufficiently advanced to provide designers of SE systems with solid background for design choices. Areas in which current knowledge is considerably less adequate include both the input (sensory) side and the output (motor) side of the haptic system, as well as the ways in which performance is degraded when displays and controls (in any of the modalities) with less-than-human resolution are used. Information on resolution for specific modalities (e.g., vision) is provided in the chapters concerned with these modalities.
A further and related set of issues that is important to consider in the design of SE systems concerns perceptual illusions. Generally speaking, a given perception is thought of as illusory to the extent that it appears to be generated by a stimulus configuration that is different from the actual one. VEs themselves can be regarded as integrated sets of illusions. Detailed study of both intrasensory and intersensory illusions is important because, in many cases, the existence of illusions enables SE system design to be simplified and therefore to increase its cost-effectiveness. At the opposite end of the spectrum, the occurrence of unexpected illusions can seriously interfere with the expected performance of the system. Elicitation of motion sickness often involves the occurrence of illusions concerning the position, orientation, and movements of various portions of the body
It is possible to regard certain types of illusions, such as the illusion of continuous motion that can be generated by sequences of static images at
rates of 30 Hz, merely as reflections of imperfect sensory resolution and therefore to assume that studies of resolution will automatically include studies of illusions. However, other types of illusions, such as the Muller-Lyer illusion, are more appropriately characterized in terms of response bias and therefore cannot be regarded in this manner. Thus, it is necessary to consider illusions as a separate issue from resolution.
Much of the past work on illusions has focused on the visual channel and on the implications of these illusions for theories of visual perception and cognition. However, some results, such as the continuous motion illusion just cited, clearly have direct implications for SE design. Other illustrative results relevant to SE design include those on the dominance of vision over audition and haptics in cases of intermodality conflict (e.g., as evidenced in the ventriloquist effect) and on the use of auditory stimuli to improve the perception of events that are represented primarily in the visual or haptic domains (as in the use of sound effects). Material on illusory effects for vision can be found in Howard and Templeton (1966); for audition in Bregman (1990); and for haptics in Loomis and Lederman (1986), Hogan et al. (1990), and Fasse et al. (1990).
It should also be noted that relatively little work has been done on sensorimotor illusions associated with whole-body movements. The factors involved in these illusions, which usually involve the perception of body movement, support surface stability, and visual field stability, are likely to be of considerable importance in SE designs that include voluntary locomotion through virtual space. Further material on these kinds of illusions can be found in Chapter 6.
Finally, it should be noted that the merging of data from different sources in augmented-reality systems is likely to lead to a whole new set of illusory effects that will require study. Relatively little is known about the effects of different merging techniques (even if one restricts one's attention solely to the merging of visual images).
Issues related to information transfer rates tend to be very complex because such rates depend not only on basic resolving power, but also on factors related to learning, memory, and perceptual organization. With respect to information transfer rate, an SE system can be thought of as consisting of a human operator, an artificial machine (a computer or telerobot), and a two-way communication link consisting of displays that send information from the machine to the human operator and controls that send information from the human operator to the machine. One of the main goals in such systems is to optimize the efficiency of communication in both directions. For many purposes, it is useful to characterize the imperfections in the communication channels in terms of statistical variability (noise), to include in this noise both channel noise and noise internal to the human and/or the machine, and to measure the efficiency of the communication by the information transfer rate. Crudely speaking, the information transfer is defined as the information gain resulting from the communication, which in turn can be defined as ''how much more the receiving system knows about the state of the transmitting system after the communication signal is received than before it is received." The information transfer rate is then defined simply as the rate at which information is transferred. Within this context, a good human-machine interaction technique is one in which the information transfer rate is high and the amount of training required to achieve this high rate is low. Extensive background on the use of information theory concepts in characterizing human performance is available in Quastler (1955), Garner (1962, 1974), Sheridan and Ferrell (1974), Stelmach (1978), and Rasmussen (1986).
In general, in order to get high information rates into the human operator via displays or out of the human operator via controls, the human operator must be very familiar with the information coding scheme employed. Perhaps some of the coding schemes with which individuals are most familiar are those related to language. Estimates of maximum information transfer rates involving language reception and transmission in various modalities have been presented by Reed and Durlach (1994). The results indicate that maximum rates for reading English (vision), listening to spoken English (hearing), and observing the signs in American Sign Language are all roughly the same and lie in the range 60-70 bits/s. Reception of language in the haptic domain (by means of Grade 2 Braille, the feeling of signs in sign language, or by the Tadoma method, in which certain deaf and blind individuals receive speech tactually by placing one's hand on the face of the talker and monitoring the mechanical actions of the speech articulation system) shows maximum rates of roughly one-half those obtained via the visual and auditory channels.
The maximum output rate for the motor actions of the speech articulators in speech production is estimated to be roughly the same as the maximum rate for listening to speech (60 bits/s) and for the motor actions of the hands in typing to be roughly 20 bits/s. To the extent that (1) the assumptions that underlie these results are valid (in particular, that the estimate of 1.4 bits of information per letter for sentence length segments of speech is reasonable) and (2) these results provide an upper bound on the information transfer rates that can be achieved in communicating between human operator and machine in SE systems, the amount by which the results achieved with a given SE system fall below these rates provides a measure of the room for improvement. It should also be noted that the figure of 20 bits/s appears to provide an upper bound on the rate that can be achieved in simple discrete spatial tracking tasks (e.g., one in which the transmitted signal consists of lighting up a randomly selected square in a checkerboard array presented on a visual display and the correct response consists of touching the lit square with a finger or directing one's gaze at the lit square).
Unfortunately, although there are a number of general statements that can be made about the properties of a good coding system (e.g., it should be well matched to the properties of the sensory or motor system involved, it should make use of perceptually high-dimensional stimuli or responses, it should have cognitive properties that make it easy to learn, etc.), there is no theory available that enables one to make reliable predictions of performance as a function of the detailed coding scheme and detailed training procedures employed.