Abstract Summary
The pairing of Virtual Reality technology with Physiological Sensing has gained much interest in clinical settings and beyond: from developing novel methods for diagnosis of perception and cognition impairments, biofeedback for anxiety treatment, to enhancing everyday practices such as self-guided meditation. However, conducting this type of research does not come without challenges. For example, accessing the equipment for recording data from the user and synchronizing physiological response data with the stimuli or interactive environment are not trivial tasks, and generating virtual content in response to the user’s real-time data is costly and complex. This paper presents Galea, a device for multi-modal signal acquisition able to measure the physiological response of a user when experiencing virtual content, enabling behavioral, affective computing , and human-computer interaction research and applications to access data from the Parasympathetic nervous system and Sympathetic nervous system simultaneously. We present a primer on detectable human physiology as an input source for Physiological Computing from the perspective of the signals available through our device…
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Contributions and Responsibilities
- Help design experiment to measure steady-state visually evoked potentials (SSVEP) in virtual reality.
- Process and filter electroencephalogram (EEG) data optimally using MNE and Scipy.
- Build experimental protocol with Lab Streaming Layer to integrate the signal inference pipeline with the Virtual Reality maze game and SSVEP experiment.
- Interpret experimental results using Canonical Correlation Analysis statistics to acheive 90 percent accuracy in SSVEP classification.
- Implement Logistic Regression to predict visually evoked potentials in real-time with higher accuracy, allowing users to interact with the Maze game hands-free.
- Visualize and measure noise levels of electromyogram (EMG), electrooculogram (EOG), electrodermal activity (EDA), and EEG.
Virtual Presentation at IEEE VR 2022