A Novel Adaptive Physio-Behavioral Method for Optimizing Performance: Using Grip Force for Augmenting Driver Training

Abstract

The quest to remove the human factor from the equation of system performance led to the ironies of automation. Adaptive automation is an alternative approach, which aims to harmoniously integrate the person and the system, to fully utilize the maximum potential of each of the parties. Adaptive systems to the user's state offer significant advantages, such as reducing workload and improving performance. In the application of adaptive automation capabilities in driving, the existing methods suffer from practical limitations and shortcomings, which make it difficult to realize these capabilities. Among these shortcomings are large delays between the relevant event and the appearance of the physiological signs of stress in various measures, as well as the intrusiveness of the measurement means and their disturbance to the driver. Grip force is a physiological-behavioral measure of stress, which has relatively small delays and which can be easily integrated into operational means in a way that does not disturb the user. Here, we describe a series of studies highlighting an innovative method for capitalizing on stress, optimizing the driver's performance according to the psychological stress, which is measured unobtrusively according to the grip force. While stress is one of the aspects that has significant implications for the driver's performance and safety, an optimal level of stress is conducive for performance.We established an adaptive method for measuring and deciphering the psychological stress of the operator according to the grip force, in a variety of environments, tasks and means of operation. These included five studies, with a total of 157 participants, using driving, tele-driving, driving in a simulator, and computer games. Operation means used in these studies are steering wheels and joysticks. Diverse stress manipulations targeted social and performance aspects during the experiments, while strictly adhering to the rules of ethics to avoid any harm to the participants. Being a novel index of stress, grip force was validated according to skin conduction, heart rate and heart rate variability, as well as self reported stress.A detailed inspection was conducted of the time window, required for the recognition of stress according to grip force data. A 2 to 5 second time window was found proper. Various transfer functions were found useful for the translation of grip force to the stress level. Finally, a method for calculating the current stress level is described, overcoming interpersonal variability with fast automatic calibration. Applying the principles of the method in a real-time training environment showed an improvement in the training efficiency measures compared to traditional non-adaptive training methods. In simulated environments, those who trained with this grip force-based stress-adaptive method achieved a higher level of expertise in performing the task, in a shorter training time than those who trained with other methods. Leveraging stress to augment driver performance, both during training and during real-time driving, holds the potential to improve road safety and save human lives. Applications of this method in other fields, such as aviation and remote medicine are discussed including recommendations for appropriate intervention methods.

Keywords: Adaptive Automation, Grip Force, Performance. Stress, Driving

DOI: 10.54941/ahfe1005236