Factors Influencing Users’ Attitudes Towards Using Brain Computer Interface (BCI) for Non Medical Uses: An Application of the Technology Acceptance Model (TAM)

Abstract

Verbatim from Embry-Riddle Scholarly Commons. Not paraphrased, not summarized.

While brain-computer interfaces (BCI) are gaining popularity in assisting people with illnesses, there is also increased technical research on incorporating BCI into healthy people’s lives. So far, not much research has focused on user attitudes, although some research has pointed out privacy and trust issues. Understanding potential users’ attitudes, expectations, and concerns early in the technology development stage is crucial for the novelty's success. For this reason, this study aims to understand the general publics’ attitude towards BCI for nonmedical uses using the technology acceptance model (TAM). The study will offer insights into how external factors including technology optimism, familiarity, and perceived enjoyment influence perceived usefulness (PU), perceived ease of use (PEOU), and perceived trust affect BCI uses. It is hypothesized that each independent variable is positively correlated with the dependent variable in the proposed TAM. Two hundred participants between the ages of 20 and 50 were recruited to participate in the survey. The data were analyzed using structural equation modeling (SEM), including a series of goodness-of-fit (GOF) tests and path analysis. The path coefficient for each path is analyzed with a t-test and tested at a 95% confidence level. Suppose the p-value is determined to be lower than 0.05. In that case, the null hypotheses can be confidently rejected, suggesting the model accurately represents 95% of the variances of the positive correlation observed in the population.

Authors

• Wu, Yichin Embry-Riddle Aeronautical University
• Halawi, Leila Embry-Riddle Aeronautical University

Keywords

• Brain-computer interface
• Non-medical application
• User attitudes
• Technology acceptance model
• Structural equation modeling
• Operational Research