BCI, or what is commonly known as Brain-Computer Interface is an emerging group of technologies which can also be presented as brain-machine interfaces (BMI), or mind-machine interfaces (MMI). In the recently published book of research, Introduction to Neural Engineering for Motor Rehabilitation (2013) by Dario Farina, Winnie Jensen and Metin Akay, the summary on the chapter covering BCI’s provides an excellent definition of BCI’s and the current applications they are being used in.
“A BCI monitors the user’s brain activity, extracts specific features from the brain signals that reflect the intent of the subject, and translates them into action. BCI Technology offers a natural way to augment human capabilities by providing a new interaction link with the outside world and, thus it is particularly relevant as an aid for patients with severe neuromuscular disabilities.” (Millan, p. 237).
A BCI used on a patient may monitor quite a few different signals which can include, electrical, magnetic and metabolic. It is important for those studying the effectiveness of BCI’s to have the varying levels of these signals available at all times. Magnetic fields within the brain can be recorded with (MEG), or what is also known as magnetoencephalography while brain metabolic activity, which are measured by changes in blood flow to the brain can be witnessed with positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and near-infared spectroscopy (NIRS). (Millan, p., 239). However, electrical brain activity can be measured more accurately and using both invasive and non-invasive procedures.
History of BCI Research
The notion of brain-computer interaction did not become a full-fledged research focus and the object of grants until 1973 at UCLA. That research headed by Jacques J. Vidal and pursued by DARPA, ushered in a new era of technology for humans: linking human brains with the interfaces and operating systems of computers.
In a recent article , “Researchers at the University at Buffalo and elsewhere are helping to advance technology that allows people to control robots with their minds. UB isn’t focused on world domination, but rather applying these brain-computer interface (BCI) devices to manufacturing, medicine and other fields.”
BCI technologies have so many possibilities with each advancing year, and it comes to show that our thoughts really can control objects, computers, robots, among other things that we may want to control with our thoughts. You are thinking expensive right? Well, the sticker shock is not as rough as one might think. The device used in the article referenced above, retails for $750 and fits on your head pretty much like a normal cap. Personalized BCI interfaces such as this will become more commonplace by the end of this decade. There are a total of 14 sensors that are connected to help the software recognize your thought patterns. This has come quite a ways, even from the mid 1990′s when BCI interfaces were quite bulky, much more expensive and essentially were not available for retail purchase. Each succeeding year will see decreases in price, decreases in the number of and surface area of sensors, increases in sensitivity and more robust interactive software and hardware. The potential uses are profound:
“For example, it could help paraplegic patients to control assistive devices, or it could help factory workers perform advanced manufacturing tasks”. The device begins to learn your synapse patterns within a few days and can complete simple tasks, such as demonstrated by the graduate student in the video from the link above. BCI technologies also have the potential to remove repetitious and tedious tasks, while we control a robot through BCI to complete that task for us, the future of multitasking!
“The devices can also leverage the worker’s decision-making skills, such as identifying a faulty part in an automated assembly line, while also improving workers safety and productivity.” It is just a matter of time until BCI technologies become widely available especially with the converging sciences of nanotechnology, biotechnology, cognitive science, information technology and synthetic biology.
Currently, with BCI, the feedback to the software of the computer is the only direction in which the input goes. The next stage of research the rest of this decade will be focusing on is getting feedback to go both directions. For example, say you think of an action for the robot to complete and when you visually see it happen, the movement is not as smooth as you would’ve liked. In near-future BCI the robot, or artificial intelligence will help direct you to think in a manner to get the exact moment you are seeking and the speed of which it can learn complex actions and behaviors will decrease. Essentially, it will aid in manifesting your subconscious. Multi-tasking indeed!
The more our brains get intertwined with computers the more ‘uploaded’ we essentially are. This leads to the next article.