Investigating the Feasibility of Statistically Measuring Anxiety using Wireless Electromyography Sensor via Wireless Personal Communication

Abstract

Anxiety and stress result in a disorder that can deteriorate a child’s integrative progress socially, emotionally and cognitively. If not measured, they can lead to undesirable prolonged effects of depressive disorders. Although anxiety and stress can be due to many different reasons but there is still a need of some experimental procedure for quantifying it. In this paper we have investigated such a feasibility to measure anxiety using electromyography sensors. The subjects were children, male and female and were taken from the two different age groups between 4 and 6 years and between 8 and 10 years. The data was collected on 16 subjects using repeated measure design. It was then statistically analyzed to finally provide a generalized linear model for measuring anxiety. The procedure proposed in this research requires an EMG sensor to be placed on the subject’s frontalis muscles and the muscular movements are the quick responses to the stress stimulus. This is easy to implement and is also cost effective. Analysis showed significant difference in EMG activity between stresses and unstressed states. The obtained statistical model thus provided a true measure of anxiety with linear coefficients that are statistically significant at 95% confidence interval (CI).

Keywords

• Anxiety
• Stress
• Electromyography
• Sensor
• Personal Communication
• Confidence Interval