Over the past decades, dynamic interceptive actions such as catching a ball or hitting a projectile have received a great deal of attention within research on human behavior in the domains of psychology, human movement science, sport science, and performance analysis (Davids, Araújo, Vilar, Renshaw, & Pinder, 2013). Dynamic interceptive actions have proven popular methodological vehicles in psychological research because they yield insights into the intertwined and complex relationship between processes of cognition, perception, and action during performance in complex environments (Davids, Savelsbergh, Bennett, & van der Kamp, 2002; Panchuk, Davids, Sakadjian, MacMahon, & Parrington, 2013). Coordinating movements during such interceptive actions demands precise information, predicated on perceptual expertise. Successful interception of an object involves moving an effector (e.g., a hand or a foot) into the right place at the right time, and skilled athletes can satisfy these rigorous task constraints with an extraordinary degree of precision. For example, elite batters in the sport of cricket can hit projected balls with a margin of timing error of 2 to 3 ms (Regan, 1997). The speed constraints of many ball sports lead performers toward the intrinsic limitations of their visuo-motor systems, indicating that they cannot completely rely on ball flight information alone to coordinate interceptions. It has been argued that information emerging prior to ball flight—from the actions of a pitcher or bowler, for example—is pertinent for successful interception in fast ball sports (Pinder, Davids, Renshaw, & Araújo, 2011a; Pinder, Renshaw, & Davids, 2009). Advanced information sources are exemplified by visual information from the movement kinematics of another person’s actions used to project an object such as a ball (with a throw, kick, or hit) toward a catcher. Coordination of interceptive actions, under rigorous time constraints especially, encompasses the process of visual anticipation—that is, the ability to make accurate predictions from partial or incomplete advance sources of visual information (Poulton, 1957).
Van der Kamp, Rivas, van Doorn, and Savelsbergh (2008) proposed that skilled performers can regulate interceptive actions by coupling them to different sources of information that become partially available at different times in dynamic performance contexts, such as prior to and after the point of ball projection. Through this process, skilled catchers take advantage of the informational richness of the performance environment (from sources of advanced visual information, including the orientation of a thrower’s hand, or from ball flight trajectory) to functionally adapt their interceptive behaviors. These ideas emphasize the importance of the relationship between a performer and a specific performance environment, considered crucial in research from an ecological dynamics perspective (Davids & Araújo, 2010).
A common methodology for studying visual anticipation processes and interceptive actions involves presentation of video-projected images of an individual’s actions (e.g., a cricketer bowling a ball or a tennis player hitting a serve toward an observer). Images of action can be manipulated as a source of advanced visual information to examine how participants might use visual anticipation processes under different task constraints. For example, this type of methodology allows decision-making and gaze behaviors to be examined using controlled systematic experimental designs. A point of contention is that participants’ simulated behavioral responses to the presentation of information have typically been somewhat reductionist, tending to rely on verbal, written, button-pressing, or micromovement responses (e.g., Jackson & Mogan, 2007; Müller, Abernethy, & Farrow, 2006; Rowe, Horswill, Kronvall-Parkinson, Poulter, & McKenna, 2009). An important issue with these designs concerns the decoupling of perception and action in experimental work (Dicks, Button, & Davids, 2010; Panchuk et al., 2013).
A significant challenge for researchers in psychology has been to design experimental task constraints for studying dynamic actions that are representative of a performance environment from which one is sampling (Brunswik, 1956). Representative experimental designs examine psychological processes at the level of the performer–environment relationship, ensuring that the perceptual information available to regulate actions is typical of a specific performance environment (Brunswik, 1956; for a detailed review, see Pinder, Davids, Renshaw, & Araújo, 2011b). Pinder et al. (2011b) highlighted two critical features, functionality of the research and action fidelity, in a theoretical framework for representative experimental designs. Functionality of the task constraints enables performers to regulate actions with information sources that are representative of a performance environment. Therefore, when researchers design experiments, they should ensure that key perceptual variables, available in a performance environment to regulate their actions, are maintained in experimental task constraints, so that behaviors examined can be generalized to a specific performance environment. For example, catching a ball from a thrower requires information from the thrower’s movement kinematics, prior to ball flight, for successful interception. The implication is that, when catching behaviors are studied, these kinematic perceptual variables must be included in an experimental task. This type of functionality must be combined with action fidelity, which enables the performer to organize the same action that would be required in actual performance environments. High levels of action fidelity are observed when a performer’s response remains similar in experimental and actual performance conditions (Pinder et al., 2011b).
In psychology experiments, it is very difficult to maintain both functionality and fidelity, resulting in a representative experimental design. Using a "live" thrower or bowler to project an object implies having the same individual available to perform the projection action throughout extended periods of experimental data collection, which can lead to a number of issues such as validity, costs, time demands, or potential repetitive strain injury. A "live" performer could also introduce unintended variability into the projection action (Schorer, Baker, Fath, & Jaitner, 2007), making independent variables hard to control across experimental conditions or participants. Some of these limitations can be overcome by using traditional ball projection machines, so that stable ball flight trajectories can be maintained over trials without incurring injury risk, costs, or inordinate time demands on skilled individuals to “deliver” the ball to participants (e.g., bowling or pitching a ball). Yet the use of this type of ball projection technology can introduce a series of new limitations associated with the removal of advanced perceptual information from a thrower’s actions (for a more detailed review, see Pinder, Renshaw, Davids & Kerhervé 2011c). Recently, d’Avella, Cesqui, Portone, & Lacquaniti (2011) developed advancements in projection technology enabling a controlled range of different ball trajectories (varying distance, height, and flight duration). Although significant, this apparatus still neglected the availability of advanced visual information sources, despite acknowledging the importance of these sources of information when studying behavior during catching performance (Cesqui, d’Avella, Portone, & Lacquaniti, 2012).
Here, we describe a detailed methodological approach for resolving these potential problems and maintaining perception–action coupling when performance of dynamic interceptive actions, such as ball catching, is studied. We describe the methodology behind the design of a custom-built, inexpensive, integrated ball projection technology, which provides visual information on advanced movement kinematics of a throwing action, prior to ball projection, when catching behaviors are studied.
Integrated projection systems such as the apparatus described here may have a significant future in sport performance development programs and in experimental research projects. We discuss the merits of such a system, consider potential limitations, and elucidate relationships with other emerging technologies, to enable investigation and practice of dynamic interceptive actions. As well as its low cost, the methodology and apparatus presented here also support further integration with other experimental equipment typically used for studying human movement behaviors, such as a VICON camera system, digital projection systems, eye movement registration systems (e.g., ASL), electromyography (EMG), and force platforms, enabling interceptive actions to be studied comprehensively.