Neural signals decoded to control robotic arm

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Researchers at the Korea Advanced Institute of Science and Technology have developed a mind-reading system that decodes neural signals from the brain during arm movement.

neural signals
Subjects were instructed to perform reach-and-grasp movements to designate the locations of the target in three-dimensional space. (a) Subjects A and B were provided the visual cue as a real tennis ball at one of four pseudo-randomised locations. (b) Subjects A and B were provided the visual cue as a virtual reality clip showing a sequence of five stages of a reach-and-grasp movement (Image: KAIST)

Described in Applied Soft Computing, the method can be used by a person to control a robotic arm through a brain-machine interface (BMI), which translates nerve signals into commands to control a machine.

Two main techniques monitor neural signals in BMIs, namely electroencephalography (EEG) and electrocorticography (ECoG).

EEG exhibits signals from electrodes on the surface of the scalp and is non-invasive, relatively cheap, safe and easy to use. EEG has low spatial resolution and detects irrelevant neural signals, which makes it difficult to interpret the intentions of individuals from the EEG.

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