A brain computer interface is a device that allows those with motor or cognitive disabilities to control computers as well as other devices. BCIs translate brain signals with a variety sensors, recording techniques, signal-processing algorithm and machine learning. They can control a wide range of devices, from cursors on computer screens to robotic arms and wheelchairs.
Most BCIs measure activity from the scalp, such as electroencephalographic (EEG) or functional near-infrared imaging (fNIRS) signaling. The signals are captured by a sensor that detects the activity of neuronal neurons. Software then converts these signals into operating commands.
In a lot of BCI systems, the user is required to go through an iterative training process to master the ability to produce signals that are recognized by the system. For example an BCI designed to type letters requires users to imagine the movement of their left or right hand to create the desired movement image.
The most exciting BCI breakthroughs involve implantable or invasible systems that record directly on the neural tissue instead of the scalp. These devices are more precise than noninvasive BCIs but they require surgical intervention and carry some dangers.
Invasive BCIs are still in their early stages of research and it is essential that patients who undergo this procedure comprehend the dangers and benefits of this procedure. BCIs can detect neural signals containing sensitive health and behavioral information. Security and privacy of data is an additional issue. Some people object to the technology due to ethical reasons as they fear that others could hack into their minds and take control of them.
hive-eu.org/exploring-noninvasive-brain-stimulation-methods/
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