The Application of Biosignal Feedback for Reducing Cybersickness from Exposure to a Virtual Environment

Abstract

We examined the efficacy of a new method to reduce cybersickness. A real-time cybersickness detection system was constructed with an artificial neural network whose inputs were the electrophysiological signals of subjects in a virtual environment. The system was equipped with a means of feedback; it temporarily provided a narrow field of view and a message about navigation speed deceleration, both of which acted as feedback outputs whenever electrophysiological inputs signaled the occurrence of cybersickness. This system is named cybersickness relief virtual environment (CRVE). Forty-seven subjects experienced the VR for 9.5 min twice in CRVE and non-CRVE conditions. The results indicated that the frequency of cybersickness and simulator sickness questionnaire scores were lower in the CRVE condition than in the non-CRVE condition. Subjects also showed a higher net increase in tachyarrhythmia from the baseline period to the virtual navigation period in the CRVE condition compared to the non-CRVE condition. These results suggest that a CRVE condition may be a countermeasure against cybersickness.

Ramps are better than stairs to reduce cybersickness in applications based on a HMD and a Gamepad

“…Traditional methods to reduce cybersickness include: alternative sensory feedback [10], moving platforms [3,1] and rest frames [15]. We discard these methods because we considered them too complex, expensive or invasive for the expected kind of users.…”

Identifying Relationships between Physiological Measures and Evaluation Metrics for 3D Interaction Techniques

“…Kim et al [16] presented a study about the use of physiological measures to reduce cybersickness in immersive VEs. Their approach proposed a system based on 11 physiological signals, which detected the cybersickness and automatically reduced the user's field of view and slowed the travel velocity in the VE.…”

“…The estimate duration to finish this stage is eight minutes. According to Kim et al [16], this period is also important to stabilize the physiological responses before next stages.…”

“…The above times, defined to complete the training and experiment stages, are based on Lin et al [17][18] [19][20] and Brogni et al [7][8] works, whereas the interval to rest between stages is based on Kim et al [16].…”

“…According to Malik et al [22], the physiological monitoring provides information about the user's physiological balance, and its measures are associated with stress. Researches in the Virtual Reality (VR) area have been using this type of measurement to assess the user's physical and mental effort on the 2D games [17][18] [19] [20] and to evaluate presence and user comfort in immersive virtual environments (VEs) [7][8] [16][23] [24]. However, there are no studies about the relationship between physiological measures and metrics focused on the evaluation of the quality of ITs.…”