OVERVIEW

 

 

 

 

 

 

 

HISTORY

Brain computer interfaces were first researched in the 1970s at the University of California, Los Angeles.[1] Since then, the research has been focussed on using BCIs in neuro-prosthetic applications. This has been possible due to the cortical plasticity of the brain, which allows new connections to be formed between neurons, throughout the lifetime of a human being.[2] This is an advantageous quality in neuro-prosthetic applications as the brain can adapt to receiving signals from implanted prostheses over time due to new connections being formed in the neural network.

 

 

 

 

 

 

 

 

 

 

CLOSED LOOP BCI

1. Electrodes are placed on the user’s scalp that pick up EEG signals. The

acquired signals are in the scale of microvolts and need to be amplified. *

 

2. Once amplified, the signals are conditioned to eliminate noise which

    exists in the range of 50-60Hz. [4]

 

3. A notch filter is used to attenuate the signal and a bandpass filter

    removes irrelevant frequencies.

 

4. The signal is then discretized by an analogue-to-digital (A/D) converter.

    The signal can then be accepted by a computer system or an embedded

    DSP (digital signal processor). [5]

 

5. The computer processes the digital signal to extract features from it that help determine the user’s intention           (original though process). Since there are a finite number of user intentions in relation to a device, such as turn     left or right, go forward or backward for a wheelchair, these features can be classified into one of these                     categorized intentions.

 

6. Once the user intention is determined, an output signal is applied to the external device that produces                     movement, e.g. the wheelchair makes a left turn.

 

7. The user makes a qualitative judgement of the performance of the device, closing the feedback loop of the            system. The output, being the performance of the device, is ‘fed back’ as the input of the system so that the user    can alter their thoughts to meet desired performance, e.g. reaching an exact position or location. [6]

 

 

OPEN-LOOP BCI

A feedback loop may not exist depending on the application of the BCI, i.e. the kind of medical device it is connected to. However, incorporating a feedback loop proves to be very useful as the user can foresee, with practice, how the wheelchair will respond to a certain thought/input. The user can also learn to alter thoughts to achieve the best performance. The computer can also be trained in interpreting EEG signals to meet desired performance and it remains a high priority for BCI researchers to incorporate this as a way of making patients’ transition into using a BCI easier. [6]

 

An example of an open-loop BCI system is the cochlear implant where a feedback loop doesn't exist. Electrodes are placed strategically so that damaged nerves are bypassed and the user is able to detect soundwaves through an external device. The cochlear implant is discussed here.

 

* Amplifying the input signal increases its resolution so that the right ‘user intention’ is determined by the computer system. It also increases the signal-to-noise ratio.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References

1. Vidal, Jean-Jacques. "Toward direct brain-computer communication." Annual review of Biophysics and Bioengineering 2.1 (1973): 157-180.

2. Vidal, Jacques J. "Real-time detection of brain events in EEG." Proceedings of the IEEE 65.5 (1977): 633-641.

3. Figure 2: https://commons.wikimedia.org/wiki/File:EEG_Recording_Cap.jpg

4. Chapter 8 (Quantitative EEG-Based Brain-Computer Interface) of Quantitative EEG Analysis Methods and Clinical Applications by Shanbao Tong, Nitish Vyomesh Thakor.

5. Nicolas-Alonso, Luis Fernando, and Jaime Gomez-Gil. "Brain computer interfaces, a review." Sensors 12.2 (2012): 1211-1279.

6. How stuff works: Brain Computer Interface. http://computer.howstuffworks.com/brain-computer-interface.htm

7. National Science Foundation Video: Brain-Computer Interface - Mysteries of the Brain. https://www.youtube.com/watch?v=7t84lGE5TXA