Data-Driven Transducer Design and Identification for Internally-Paced Motor Brain Computer Interfaces: A Review

Abstract

Brain-Computer Interfaces (BCIs) are systems that establish a direct communication pathway between the users' brain activity and external effectors. They offer the potential to improve the quality of life of motor-impaired patients. Motor BCIs aim to permit severely motor-impaired users to regain limb mobility by controlling orthoses or prostheses. In particular, motor BCI systems benefit patients if the decoded actions reflect the users' intentions with an accuracy that enables them to efficiently interact with their environment. One of the main challenges of BCI systems is to adapt the BCI's signal translation blocks to the user to reach a high decoding accuracy. This paper will review the literature of data-driven and user-specific transducer design and identification approaches and it focuses on internally-paced motor BCIs. In particular, continuous kinematic biomimetic and mental-task decoders are reviewed. Furthermore, static and dynamic decoding approaches, linear and non-linear decoding, offline and real-time identification algorithms are considered. The current progress and challenges related to the design of clinical-compatible motor BCI transducers are additionally discussed.

Identifying Thematics in a Brain‐Computer Interface Research

“…Apart from short-term monitoring, the use of implanted semi-invasive systems has been the long-term use of ECoG. Cortical electrical stimulation (CES) systems have been investigated for a variety of motor functions such as hand movement [ 35 , 48 ] and for nonmotor applications to enhance auditory visual and language systems has been the focus of research [ 49 ]. ECoGs provide long term constant and stable signal acquisition systems and therefore have the potential for addressing chronic conditions [ 48 ].…”

“…Cortical electrical stimulation (CES) systems have been investigated for a variety of motor functions such as hand movement [ 35 , 48 ] and for nonmotor applications to enhance auditory visual and language systems has been the focus of research [ 49 ]. ECoGs provide long term constant and stable signal acquisition systems and therefore have the potential for addressing chronic conditions [ 48 ]. However, there are significant risks with the use ECoGs due to their invasive nature; these risks include epi- and subdural hematoma, cerebral infarcts, increase of intracranial pressure, and brain edema [ 28 , 47 , 49 , 50 ].…”