The core value of the brain-computer interface: Communication without action. People can communicate with the outside world and even control surrounding objects through the will of the brain without the need to move any part of the body.
What is a brain-computer interface?
The brain-computer interface uses brainwave electrical signals to communicate between humans and machines, allowing patients to control electric devices such as wheelchairs or robotic arms which can be used to grab objects. After the user visually observes the surrounding environment, the user concentrates on the action to be performed, and the generated electroencephalogram (EEG) is received by a non-invasive electrode patch placed on the surface of the head, which is then transmitted to the computer software. The computer processes the EEG signal generated, extracting the information received, decoding it, and performing the desired action on the object. The brain-computer interface provides the physically handicapped person with a way of using their thoughts to control the computer, replacing the keyboard, mouse, and voice input methods, all of which require actual movement of the body.
How does a brain-computer interface work?
Brain-computer interface technology can directly detect activities in the brain, including concentration, thinking, stress, etc. There are many potential benefits, but also risks for abuse. Software can adjust light sources and play stress-relieving music, but imagine a supervisor who monitors the concentration of employees, or even uses brain commands to control the stress level of employees.
Using the brain to directly control computers and machinery is an example of the use of a brain-computer interface. Brain-computer interfaces measure brain activity, extract characteristics of specific activities, and convert these characteristics into digital output signals that replace, restore, enhance, supplement or improve human function. The advantage of this is that it is free from the requirements of most interactive interfaces for sensory reception such as vision and hearing, and physical participation, so that more disabled people can participate in their use without burden. More functions of BCI are still in the experimental development stage, but the main application at present is to replace lost functions, such as communication and mobility.
In recent years, related research on the brain-computer interface has mainly focused on the acquisition of signals, as well as the processing and calculation of signals. EEG signals are collected by wireless dry electrodes attached to the scalp. Compared with connections to the cerebral cortex which collect information during surgery, external dry electrodes have the advantages of low invasiveness and a simple operation procedure. Research has led to algorithms that identify EEG signals and extract their features, reduce noise interference, adjust the actions of control devices, and improve reliability.
Since the measured EEG signal is the result of the superposition of the firing of multiple neurons, researchers must analyze the brainwave characteristics of the user's brain when performing different tasks, and find clues that can help interpret the user's intention. Among them, visual evoked-potential (VEP) and event-related potential (ERP) implies many brain wave features are related to brain activity and function. The independent component analysis can effectively separate the electromyographic signal (EMG) generated by blinking and background electromagnetic interference. With the development of machine learning technology, algorithms that can identify key EEG waveforms can more accurately analyze EEG signals and understand the user's will.
Three elements of the brain-computer interface: Signal Acquisition, Feature Extraction, Translation Algorithm.
Applications of brain-computer interface:
- Assist in the loss of physical function due to injury or disease, assist in communication or replace wheelchair operation.
- Restore the function of the body. Such as stimulating the muscles and nerves of paralyzed patients to restore bladder function.
- Improve physical function. Such as the rehabilitation of stroke patients.
- Increase mental function. Such as detecting stress or improving poor concentration of students by detecting their brain activity and monitoring their mental state.
- As a research tool for brain function.
Industries where the brain-computer interface is applied include communication and control for health and neurofeedback, assistive technology and home control, security and protection, entertainment and games, finance, scientific research, etc. It is expected that with the development of this technology, in addition to enhancing the value of the IT industry, it can help improve and enhance medical care services.