Can background music help to relieve stress? An EEG analysis This study is designed to investigate the effect of music on the human subjects when they are under stress. Stroop colorword test is implemented to create stressful environment. Three different stroop tests, congruent, incongruent and mix exhibit low, high and moderate stress levels respectively. The participants performed the stroop tests with and without background music and their EEG was recorded. The participants were categorized into three stress groups based on the perceived stress scale questionnaire. Absolute alpha power from EEG is computed and analyzed. For congruent and mix stroop test higher alpha power is observed in the presence of music indicating a positive effect of music under low and moderate stress conditions. For incongruent case the alpha power is reduced in the presence of music indicating negative effect of the music under high stress. From ANOVA results a significant change is observed in resting state alpha power vs mix (p0.031) and a marginally significant change between resting state vs incongruent (p0.088) in the presence of music.

Using Virtual Reality to Examine the Correlation between Balance Function and Anxiety in Stance We study the interaction between balance function and anxiety in humans via a virtual reality based experimental setup, fundamentally designed to examine postural control and neurological feedback during balancedemanding height and perturbation shifts, while in quiet stance. In this work, sensory organization balance test (SOT) was utilized to quantify the balance function in subjects, and the salient features of the recorded electrocardiogram (EKG), electromyogram (EMG) and electroencephalography (EEG) signals described the subjectu0027s physiological anxietyrelated responses. Also, patientreported outcomes measurement information system (PROMIS) trait anxiety questionnaire was adopted to indicate the selfassessed trait anxiety scores by the subjects. Our statistical analysis indicates that subjects with higher SOT scores encounter a lower heart rate variability during baseline recording relative to the experimental trials and lower cocontraction index of the ankle dorsiflexion (during the experimental trials), suggesting a lower anxiety state. A similar trend was further observed via the selfreported PROMIS questionnaire responses, estimating anxiety experienced in daily life. Additionally, we utilize machine learning to describe the predictability of balance function states via the relative  alpha band power from the frontal channels of the recorded EEG signals as descriptive features characterizing anxiety. The discussed trends analytically demonstrate the potential for adopting balance function to anticipate anxiety, especially in stressful environments involving postural threats.