Towards Rehabilitation Robotics: Off-the-Shelf BCI Control of Anthropomorphic Robotic Arms

Abstract

Advances in neural interfaces have demonstrated remarkable results in the direction of replacing and restoring lost sensorimotor function in human patients. Noninvasive brain-computer interfaces (BCIs) are popular due to considerable advantages including simplicity, safety, and low cost, while recent advances aim at improving past technological and neurophysiological limitations. Taking into account the neurophysiological alterations of disabled individuals, investigating brain connectivity features for implementation of BCI control holds special importance. Off-the-shelf BCI systems are based on fast, reproducible detection of mental activity and can be implemented in neurorobotic applications. Moreover, social Human-Robot Interaction (HRI) is increasingly important in rehabilitation robotics development. In this paper, we present our progress and goals towards developing off-the-shelf BCI-controlled anthropomorphic robotic arms for assistive technologies and rehabilitation applications. We account for robotics development, BCI implementation, and qualitative assessment of HRI characteristics of the system. Furthermore, we present two illustrative experimental applications of the BCI-controlled arms, a study of motor imagery modalities on healthy individuals' BCI performance, and a pilot investigation on spinal cord injured patients' BCI control and brain connectivity. We discuss strengths and limitations of our design and propose further steps on development and neurophysiological study, including implementation of connectivity features as BCI modality.

Brain Functional Networks Study of Subacute Stroke Patients With Upper Limb Dysfunction After Comprehensive Rehabilitation Including BCI Training

“…Therefore, it is necessary to develop therapeutic approaches focused on skill learning to promote plasticity, involving enhanced activity of the motor cortex (10). Brain computer interface (BCI) systems allow the brain signals to provide both physical assistance and recovery following central nervous system injury by providing users with brain statedependent sensory feedback via functional electrical stimulation, virtual reality environments, or robotic systems (11)(12)(13)(14). BCI systems can also be used to detect real-time primary motor cortex activation, i.e., the intention to move.…”

Wireless Brain-Robot Interface: User Perception and Performance Assessment of Spinal Cord Injury Patients

“…Ethical Approval and Recruitment. The institutional bioethics committee approved the experimental protocol [12,31] and all subjects filled and signed an informed consent form prior to their participation. Criteria for participation included clinical diagnosis and radiological documentation of SCI (evaluated by ASIA Impairment Scale (AIS) [33] and/or neurological examination reporting the condition) or healthy participants [31].…”

“…As both the interface's and robotics' development have been thoroughly described before [12,32], we will briefly explain the system's technical characteristics here, emphasizing wireless capabilities. The Emotiv EPOC is an easily applied wireless 14-saline feltelectrode EEG system (Emotiv, USA), capable of detecting brain activity at a bandwidth of 0.2-43 Hz, employing digital notch filters at 50 Hz and 60 Hz and built-in digital 5th order Sinc filter.…”

“…Even though affordable, power-autonomous, full-body robotic exoskeletons are yet to materialize, disabled patients now have a variety of product options, some commercially available: manipulator arms mounted on robotic wheelchairs [20,21], dexterous robotic prosthetics which can acquire their control signals directly from the patient's nervous system [1,22], and adaptations of aforementioned BCI technology specifically for robotic rehabilitation [23][24][25]. Unfortunately, research in optimal interfaces for Human-Robot Interaction (HRI) is often overlooked in medical robotics development [12], with a potentially significant impact on user acceptance and the validation success rate for new technologies [26]. User perception and overall satisfaction with a robot's technological interface has equal importance to hardware/software design and quality standards, something that holds particularly true in robotic-assisted rehabilitation.…”

“…In our previous work we have presented our progress towards developing 8-DoF anthropomorphic robotic arms, controlled by wireless off-the-shelf BCI, for AT and rehabilitation applications [12]. We have accounted for development of the robotic arms and electronics, for implementation of the BCI control module, and we have presented pilot experimental applications of the Brain-Robot Interface (BRI) on healthy and disabled individuals [29,30].…”