Biosensor Technologies for Augmented Brain-Computer Interfaces in the Next Decades

• Published in: Proceedings of the IEEE 2012-05, Vol.100 (Special Centennial Issue), p.1553-1566
• Main Authors: Liao, Lun-De, Lin, Chin-Teng, McDowell, Kaleb, Wickenden, Alma E., Gramann, Klaus, Jung, Tzyy-Ping, Ko, Li-Wei, Chang, Jyh-Yeong
• Format: Article
• Language: English
• Subjects: Applied sciences; Augmented brain-computer interface (ABCI); Biological and medical sciences; Biomedical imaging; biosensor; Biosensors; Biotechnology; Brain computer interfaces; Brain models; cognitive-state monitoring; Computer interfaces; Computerized, statistical medical data processing and models in biomedicine; Electrodes; electroencephalogram (EEG); Electroencephalography; Electronics; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; Hardware; human brain imaging; Image processing; Information, signal and communications theory; Input-output equipment; Medical management aid. Diagnosis aid; Medical sciences; Methods. Procedures. Technologies; Signal processing; Telecommunications and information theory; Various methods and equipments
• ISSN: 0018-9219; 1558-2256
• DOI: 10.1109/JPROC.2012.2184829

The study of brain-computer interfaces (BCIs) has undergone 30 years of intense development and has grown into a rich and diverse field. BCIs are technologies that enable direct communication between the human brain and external devices. Conventionally, wet electrodes have been employed to obtain unprecedented sensitivity to high-temporal-resolution brain activity; recently, the growing availability of various sensors that can be used to detect high-quality brain signals in a wide range of clinical and everyday environments is being exploited. This development of biosensing neurotechnologies and the desire to implement them in real-world applications have led to the opportunity to develop augmented BCIs (ABCIs) in the upcoming decades. An ABCI is similar to a BCI in that it relies on biosensors that record signals from the brain in everyday environments; the signals are then processed in real time to monitor the behavior of the human. To use an ABCI as a mobile brain imaging technique for everyday, real-life applications, the sensors and the corresponding device must be lightweight and the equipment response time must be short. This study presents an overview of the wide range of biosensor approaches currently being applied to ABCIs, from their use in the laboratory to their application in clinical and everyday use. The basic principles of each technique are described along with examples of current applications of cutting-edge neuroscience research. In summary, we show that ABCI techniques continue to grow and evolve, incorporating new technologies and advances to address ever more complex and important neuroscience issues, with advancements that are envisioned to lead to a wide range of real-life applications.