A Research Publication
Factors Influencing Users’ Attitudes Towards Using Brain Computer Interface (BCI) for Non-Medical Uses: An Application of the Technology Acceptance Model (TAM)
About this Project
This study originated during my Master's program as an academic assignment and has since been developed into a research project. Upon invitation from my instructor, we have submitted the abstract to the National Training Aircraft Symposium (NTAS). Currently, the research is in the data collection phase.
Background
About TAM
The Technology Acceptance Model (TAM), proposed by Fred Davis, offers a theoretical approach for understanding user behaviors. According to this model, perceived ease of use and usefulness determine system usage behavior. This model's ability to identify and explain technology acceptance determinants provides a theoretically sound basis for understanding users' behaviors.
About BCI
The human brain controls bodily functions, from cognition to motion, through billions of interconnected neurons. Brain-computer interfaces (BCIs) are the latest technological advancement in our daily lives, creating a direct neural connection between the brain and computer. Originally developed to aid those with motor deficits, BCIs remain in the developmental stage, with majorly only patients benefiting from their use. Non-medical applications include gaming, virtual reality (VR), and smart homes.
Problem
Problem Statement
As brain-computer interfaces (BCIs) continue to advance beyond medical applications, there remains a dearth of understanding regarding user attitudes towards this technology. This study aims to address this gap by examining external factors that may influence user attitudes towards using BCIs for non-medical purposes, utilizing the Technology Acceptance Model as a framework for analysis.
Literature Gap
Research into the medical applications of BCI has predominantly focused on technical aspects. Only a few studies have explored the user experience and mental state during and after using this technology, with mixed attitudes reported. For instance, researchers examined the relationship between fatigue, attention, and frustration in non-disabled participants using BCI. Meanwhile, studies that interviewed current BCI users for medical purposes found that users hold a positive attitude towards the technology.
Compared to BCI, research on voice-based digital assistance (VBDA) and virtual reality (VR) technology is more established, with numerous studies exploring user attitudes. Such research has identified key issues related to privacy, practicality, and safety concerns, which may also impact user acceptance of BCI.
Hypothesis
Our proposed hypothesis integrates the TAM and its precursor, the Theory of Planned Behavior (TPB), to leverage the strengths of each model while incorporating external factors. These external factors are selected based on previous research conducted in medical and non-medical fields related to brain-computer interfaces, as well as popular products such as voice-based digital assistants and virtual reality technology, that also utilized the TAM framework.
Our hypothesis posits that users' perception of the usefulness and ease of use of brain-computer interfaces (BCI) can be influenced by their level of technology optimism, familiarity with BCI, and perceived enjoyment of using the technology. Additionally, we propose that perceived usefulness can be influenced by perceived ease of use, and that both factors may affect users' perceived trust in BCI. Finally, we will investigate whether increased trust in the technology corresponds with a greater intention to use BCI.
Method
Background Info - Youtube Video
Prior to answering the survey questions, participants will be presented with an informative video about BCI that was specifically created to provide contextual background information in a neutral and unbiased manner.
Survey
Each of the factors are tested using 4-5 statements for users to rank: strongly disagree to strongly agree.
Sample question on technology optimism: BCI will be a dominating tool in the future in everyone’s daily life.
IRB-approved
Looking to get at least 100 responses, ideally 200
Reliability & Variability
While the reliability of this model has been tested and confirmed by numerous researchers over the years, our study aims to address potential variability and test the model's validity in practice once a sufficient amount of data has been collected.
