Vision-aided brain–machine interface training system for robotic arm control and clinical application on two patients with cervical spinal cord injury

Cited 5 time in Web of Science Cited 7 time in Scopus
Kim, Yoon Jae; Nam, Hyung Seok; Lee, Woo Hyung; Seo, Han Gil; Leigh, Ja-Ho; Oh, Byung-Mo; Bang, Moon Suk; Kim, Sungwan
Issue Date
BioMed Central
BioMedical Engineering OnLine. 2019 Feb 11;18(1):14
Brain machine interfaceSpinal cord injuryElectroencephalographyFunctional magnetic resonance image
While spontaneous robotic arm control using motor imagery has been reported, most previous successful cases have used invasive approaches with advantages in spatial resolution. However, still many researchers continue to investigate methods for robotic arm control with noninvasive neural signal. Most of noninvasive control of robotic arm utilizes P300, steady state visually evoked potential, N2pc, and mental tasks differentiation. Even though these approaches demonstrated successful accuracy, they are limited in time efficiency and user intuition, and mostly require visual stimulation. Ultimately, velocity vector construction using electroencephalography activated by motion-related motor imagery can be considered as a substitution. In this study, a vision-aided brain–machine interface training system for robotic arm control is proposed and developed.

The proposed system uses a Microsoft Kinect to detect and estimates the 3D positions of the possible target objects. The predicted velocity vector for robot arm input is compensated using the artificial potential to follow an intended one among the possible targets. Two participants with cervical spinal cord injury trained with the system to explore its possible effects.

In a situation with four possible targets, the proposed system significantly improved the distance error to the intended target compared to the unintended ones (p < 0.0001). Functional magnetic resonance imaging after five sessions of observation-based training with the developed system showed brain activation patterns with tendency of focusing to ipsilateral primary motor and sensory cortex, posterior parietal cortex, and contralateral cerebellum. However, shared control with blending parameter α less than 1 was not successful and success rate for touching an instructed target was less than the chance level (= 50%).

The pilot clinical study utilizing the training system suggested potential beneficial effects in characterizing the brain activation patterns.
Files in This Item:
Appears in Collections:
College of Medicine/School of Medicine (의과대학/대학원)Biomedical Engineering (의공학전공)Journal Papers (저널논문_의공학전공)
College of Engineering/Engineering Practice School (공과대학/대학원)Program in Bioengineering (협동과정-바이오엔지니어링전공)Journal Papers (저널논문_협동과정-바이오엔지니어링전공)
College of Medicine/School of Medicine (의과대학/대학원)Rehabilitation Medicine (재활의학전공)Journal Papers (저널논문_재활의학전공)
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.