Melissa Loomis from Ohio, US lost an arm in a terrible accident and her normal life went upside down. But, she had never imagined that one day, with the help of AI, she would be able to get an arm as good as a real one. In 2016, Loomis became the first amputee in the world to feel a sense of touch through a mind-controlled bionic arm. This is often considered one of the biggest events in the history of prosthesis. The history of prostheses dates back to the Egyptian era when the first functional prosthesis limb was used between 950 and 710 BC.

The white rigid back to the fingertip is covered with the black flexible 3D-printed skin. Machines can beat the world's best chess player, but they cannot handle a chess piece as well as an infant. This lack of robot dexterity is partly because artificial grippers lack the fine tactile sense of the human fingertip, which is used to guide our hands as we pick up and handle objects. Two papers published in the Journal of the Royal Society Interface give the first in-depth comparison of an artificial fingertip with neural recordings of the human sense of touch. The research was led by Professor of Robotics & AI (Artificial Intelligence), Nathan Lepora, from the University of Bristol's Department of Engineering Maths and based at the Bristol Robotics Laboratory.

Researchers from the University of Michigan (MI, USA) have developed a novel neuroprosthetic model involving muscle grafts with machine-learning algorithms, which allowed for ultra-precise movements in a prosthetic hand. This technology is considered to be a major advance in motor control for amputees and could significantly enhance quality of life for individuals with upper limb loss. Peripheral nerve interfaces control neuroprosthetics by registering nerve signals in the remaining limb and translating them into movements. This allows individuals who have lost limbs to intuitively control prosthetic replacements. However, one of the biggest challenges in mind-controlled prosthetics is establishing a strong and stable nerve signal to translate to the bionic limb that will allow for a range of precise and durable movements.

A sensor that picks up nerve signals from the spinal cord could let people control a prosthetic arm by simply imagining the movement they want to make. In tests using the sensor, which has to be surgically implanted, people were able to control a virtual arm on a screen with a larger range of movement than many existing prosthetics. Prosthetic arms currently on the market are usually controlled by the user flexing muscles in their arm or chest. But there is a limit to how many commands can be mapped onto these muscle movements, which makes it difficult to do more intricate manoeuvres like pinching two fingers together. A team led by Dario Farina, then at University Medical Centre Göttingen, Germany, instead developed a technique that interprets signals directly from motor neurons in the spinal cord.