Potential role of noise to improve intracortical microstimulation in tactile neuroprostheses

Exploring user perspectives on a robotic arm with brain-machine interface: A qualitative focus group study

Brain-machine Interface (BMI) is a system that translates neuronal data into an output variable to control external devices such as a robotic arm. A robotic arm can be used as an assistive living device for individuals with tetraplegia. To reflect users' needs in the development process of the BMI robotic arm, our team followed an interactive approach to system development, human-centered design, and Human Activity Assistive Technology model. This study aims to explore the perspectives of people with tetraplegia about activities they want to participate in, their opinions, and the usability of the BMI robotic arm. Eight people with tetraplegia participated in a focus group interview in a semistructured interview format. A general inductive analysis method was used to analyze the qualitative data. The 3 overarching themes that emerged from this analysis were: 1) activities, 2) acceptance, and 3) usability. Activities that the users wanted to do using the robotic arm were categorized into the following 5 activity domains: activities of daily living (ADL), instrumental ADL, health management, education, and leisure. Participants provided their opinions on the needs and acceptance of the BMI technology. Participants answered usability and expected standards of the BMI robotic arm within 7 categories such as accuracy, setup, cost, etc. Participants with tetraplegia have a strong interest in the robotic arm and BMI technology to restore their mobility and independence. Creating BMI features appropriate to users' needs, such as safety and high accuracy, will be the key to acceptance. These findings from the perspectives of potential users should be taken into account when developing the BMI robotic arm.