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Despite the widespread adoption of Virtual Reality (VR) technology, cybersickness remains a barrier for some users. This research investigates head movement patterns as a novel physiological marker for cybersickness detection. Unlike traditional markers, head movements provide a continuous, non-invasive measure that can be easily captured through the sensors embedded in all commercial VR headsets. We used a publicly available dataset from a VR experiment involving 75 participants and analyzed head movements across six axes. An extensive feature extraction process was then performed on the head movement dataset and its derivatives, including velocity, acceleration, and jerk. Three categories of features were extracted, encompassing statistical, temporal, and spectral features. Subsequently, we employed the Recursive Feature Elimination method to select the most important and effective features. In a series of experiments, we trained a variety of machine learning algorithms. The results demonstrate a 76% accuracy and 83% precision in predicting cybersickness in the subjects based on the head movements. This study contribution to the cybersickness literature lies in offering a preliminary analysis of a new source of data and providing insight into the relationship of head movements and cybersickness., Comment: 18 pages, 3 Figures, 3 Tables

We develop a constrained bimatrix game framework that can be used to model many practical problems in many disciplines, including jamming in packetized wireless networks. In contrast to the widely used zero-sum framework, in bimatrix games it is no longer required that the sum of the players' utilities to be zero or constant, thus, can be used to model a much larger class of jamming problems. Additionally, in contrast to the standard bimatrix games, in constrained bimatrix games the players' strategies must satisfy some linear constraint/inequality, consequently, not all strategies are feasible and the existence of the Nash equilibrium (NE) is not guaranteed anymore. We provide the necessary and sufficient conditions under which the existence of the Nash equilibrium is guaranteed, and show that the equilibrium pairs and the Nash equilibrium solution of the constrained game corresponds to the global maximum of a quadratic program. Finally, we use our game theoretic framework to find the optimal transmission and jamming strategies for a typical wireless link under power limited jamming., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

We employ a game theoretic approach to formulate communication between two nodes over a wireless link in the presence of an adversary. We define a constrained, two-player, zero-sum game between a transmitter/receiver pair with adaptive transmission parameters and an adversary with average and maximum power constraints. In this model, the transmitter's goal is to maximize the achievable expected performance of the communication link, defined by a utility function, while the jammer's goal is to minimize the same utility function. Inspired by capacity/rate as a performance measure, we define a general utility function and a payoff matrix which may be applied to a variety of jamming problems. We show the existence of a threshold such that if the jammer's average power exceeds this threshold, the expected payoff of the transmitter at Nash Equilibrium (NE) is the same as the case when the jammer uses its maximum allowable power all the time. We provide analytical and numerical results for transmitter and jammer optimal strategies and a closed form expression for the expected value of the game at the NE. As a special case, we investigate the maximum achievable transmission rate of a rate-adaptive, packetized, wireless AWGN communication link under different jamming scenarios and show that randomization can significantly assist a smart jammer with limited average power.

We formulate the interaction between the communicating nodes and an adversary within a game-theoretic context. We show that earlier information-theoretic capacity results for a jammed channel correspond to a pure Nash Equilibrium (NE). However, when both players are allowed to randomize their actions (i.e., coding rate and jamming power) new mixed Nash equilibria appear with surprising properties. We show the existence of a threshold ($J_{TH}$) such that if the jammer average power exceeds $J_{TH}$, the channel capacity at the NE is the same as if the jammer was using its maximum allowable power, $J_{Max}$, all the time. This indicates that randomization significantly advantages powerful jammers. We also show how the NE strategies can be derived, and we provide very simple (e.g., semi-uniform) approximations to the optimal communication and jamming strategies. Such strategies are very simple to implement in current hardware and software.