Lessons Learned from the Initial Development of a Brain Controlled Assistive Device

The use of motor imagery to control a mounted robotic arm allows for designing an assistive device prototype that may enable individuals with disabilities to perform basic lifting and moving tasks. The design and implementation of a brain-computer interface robotic arm system that will allow disabled users to perform these tasks without the need for physical strain or prolonged periods of training are explored in this paper. The proposed integration encompasses an Emotiv EPOC X headset, six-axis DOFBOT robotic arm, BLE 5.0 adapter, and a Raspberry Pi development board. The key focuses of this design was to create a system that is modular, user-friendly, and fast to train. The construction and drawbacks of various prototype iterations of the system and the lessons learned throughout the project are discussed. These lessons are anticipated to provide useful insights into improved practices to be adopted into future technologies relying on mental imagery.