A comprehensive assessment of Brain Computer Interfaces: Recent trends and challenges
Introduction
The ability to bridge the communication gap between man and machines through Man-Machine Communication Interfaces has led to the innovative use of human-computer Interaction systems. Moreover, BCI (Brain Computer Interface), a widely accepted Human-Computer Interaction system, has gained high popularity among the neuro-scientific community. This organization of man-machine interface for communication has been illustrated in Fig. 1.
BCI or brain-machine interface (BMI) is an effective device for communication between users and systems. It is an integration of hardware and software systems to facilitate interaction between humans and their surroundings. This interaction is achieved by using the control signals arising due to the cerebral activity (Van Erp et al., 2012). In general, a non-muscular channel is created to convey the intentions of the user to external devices (for instance, computers, assistive devices, neural prostheses, speech synthesizers) for controlling action. The emergence of BCI is usually associated with the development of effective communication channels in biomedical applications. The prime objective is to deliver communication capabilities to rigorously immobilized people. For instance, completely paralyzed or locked-in individuals with neurological neuromuscular disorders (amyotrophic lateral sclerosis, brain stem stroke, spinal cord injury) are usually considered as prospective users. The developments in BCI have led to the creation of assistive devices which assist in the motor restoration and rehabilitation (Rao and Scherer, 2010; Bi et al., 2013). Thus, BCI validates its proficiency in improving the quality of life along with the reduction in the cost of intensive care (Kögel et al., 2020).
Moreover, owing to the promising prospects of BCIs, the research community has widened the focus of BCI applications among healthy users as well with the emphasis on non-medical applications (Blankertz et al., 2010a; Tan and Nijholt, 2012). The expediency of BCIs in increasing the accuracy of human-computer interaction systems has led to their involvement in several sectors (industrial sector, educational sector, safety and security, entertainment sector, to name a few). Thus, BCI, still in its early stage, is an emerging multidisciplinary area which involves the participation of researchers from many disciplines. Regardless of the day-to-day advancements and fruitful recognition of BCI, some of the pitfalls and challenges are yet to be overcome. Concerns associated with the user acceptability of modern technology have been raised and still exist. Some laboratory restricted BCI-based applications need further exploration and investigation. To broaden the applicability of BCIs, enhanced ease in usage along with the reduction in preparatory-time, training time and calibration time is required (Blankertz et al., 2010a).
Under the framework of the above discussion, an attempt has been made to explore the literature recognized in the area of BCI technology. The recent trends, applications, challenges and future prospects linked with BCI technology have been reviewed. This narrative literature review encompasses recent developments in BCIs based on a methodical search strategy. It covers a general overview of the BCI technology and sheds light on different aspects of BCIs including their applications. Contrary to the existing reviews, this review also suggests some critical directions to follow to improve the performance of BCIs while maintaining quantifiable viability. This review is also intended to provide guidelines for the acceleration of future developments, especially in the context of maturation of BCIs. Furthermore, this review underscores the challenges associated with the BCI technology.
The roadmap of this review is as follows: Section 2 describes the method followed for performing this review. Section 3 presents a detailed overview of BCIs, which describes the details of various steps involved in a standard BCI system. Thereafter, the classification of BCI systems on various grounds has been presented. Various neuroimaging methods (employed in the signal acquisition step), control signals (that determine user intentions) in BCI, feature extraction and feature selection approaches along with some well-known classification techniques are studied. Section 4 offers a brief description of various medical as well as non-medical applications of BCIs. Then, various procedural, non-technical and, approachability and serviceability challenges associated with BCI technology are discussed in Section 5. Section 6 presents the prospects in BCI technology for enhancing its broad and extensive utilization. Finally, our conclusions are presented in Section 7.
Section snippets
Methods
For this review, a comprehensive literature search was performed from a number of databases using generic search terms such as “brain computer interfaces”, “BCI”, etc. The following databases were chosen for the literature search based on the high number of results: IEEE Explore, ScienceDirect, PubMed, Google Scholar and Web of Science. The following keywords (and their combinations) were adopted for the literature search: brain computer interface, BCIs, neuroimaging methods, feature
BCI: an overview
BCI, an artificial intelligence system, recognizes specific patterns of signals arising due to brain activity. This is carried out through five successive stages. These stages comprise of signal acquisition stage, preprocessing or signal enhancement stage, feature extraction and selection stage, feature classification stage and the control interface (or graphical user interface) stage (Khalid et al., 2009). Fig. 3 presents the schematic of an overall BCI system. As shown in Fig. 3, in the
Applications
BCIs find application in wide-ranging areas of medical as well as non-medical domains. Some of these application areas and their recent advancements have been elucidated in Table 11.
Challenges to BCI
Several challenges are encountered while establishing an efficient and uninterruptable passage for communication via signals from the human brain. These significant and substantial challenges can be grouped into three categories as illustrated in Fig. 8. An in-depth and profound discussion of these challenges has been elucidated as under.
Prospects
The development and exploration of BCI technology validates to be a multidisciplinary approach that demands the unified and cohesive efforts of numerous engineers from various domains and specializations of Engineering, computer experts, mathematical masterminds, psychologists, neurological virtuosos and intellectuals of clinical restoration and therapy. The prevailing and available works on BCI technology have merely focused on the apprehensions of the advancements in signal acquisition and
Conclusions
This article presents a broad review of the essential characteristics of the BCI system. The applications of BCI technology along with various challenges and possible solutions have been discussed. Some future prospects associated with BCI technology are also addressed. A number of applications have been recognized with phenomenal prospective for further advancements in BCI technology. This review recommends the practical usage of BCI technology for outside the laboratory settings. In addition,
Ethical approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Availability of data and materials
Not applicable.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Declaration of Competing Interest
The authors report no declarations of interest.
Acknowledgements
None.
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