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They may be movements able-bodied people take for granted, but a robotic hand has been programmed to give a thumbs-up, scoop objects and pinch.

And, not only can it carry out this unprecedented range of movement with ease, each motion is controlled using brainwaves of the wearer.

Over the past two years, a quadgriplegic has used the hand to give high-fives to researchers, feed herself chocolate and now give a thumbs-up using simply her thoughts. 

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The University of Pittsburgh's hand connects to the brain using electrodes and lets the wearer control it using their thoughts. The 7D model of the hand could grasp and high-five. The new 10D model can now abduct fingers (top left and right), scoop, pinch (bottom left) and extend the thumb (bottom right)

Jan Scheuermann, 55, from Pittsburgh has been paralysed from the neck down since 2003 due to a neurodegenerative condition.

She signed up to the University of Pittsburgh's study in 2012, and was fitted with two quarter-inch electrode grids.

Each electrode has 96 contact points covering regions of her brain that are responsible for right arm and hand movements.

After the electrode grids in Ms Scheuermann's brain were connected to a computer, creating a brain-machine interface, the contact points picked up pulses of electricity that were fired between the neurons.

Computer algorithms were then used to decode these firing signals and identify the patterns associated with a particular arm movement, such as raising the arm or turning the wrist.

The researchers used a virtual reality computer program to calibrate Ms Scheuermann's control over the robotic arm.  

University of Edinburgh presents its robotic hand

Jan Scheuermann (pictured using the arm) has been paralysed from the neck down since 2003. She signed up to the Pittsburgh study in 2012, and was fitted with two quarter-inch electrode grids. Each electrode has 96 contact points covering regions of her brain that are responsible for right arm and hand movements

Computer algorithms were used to decode brain signals and identify the patterns associated with a particular arm movement. The researchers then used a virtual reality computer program to calibrate Ms Scheuermann's control over the robotic arm (pictured)

Following this training, Ms Scheuermann was able to make the robotic arm reach for objects, as well as move in a number of directions, and flex and rotate the wrist, simply thinking about the movements.

It also enabled recently her to high-five the researchers and feed herself chocolate.

The previous hand was called 7D, but the latest, more advanced model is known as 10D.

The 10D has extra dimensions that come from four types of hand movements - finger abduction, scoop, thumb extension and a pinch.

This range of motions means Ms Scheuermann is more able to pick up, grasp and move more objects, more precisely than before.

The 10D has extra dimensions that come from four types of hand movements - finger abduction, scoop, thumb extension and a pinch.This range of motions means Ms Scheuermann is more able to pick up, grasp and move more objects, and more precisely, than before (example objects used in the study are pictured)

Woman with quadriplegia feeds herself chocolate using...

It is hoped these results, published in the Journal of Neural Engineering, can build on previous demonstrations and eventually allow robotic arms to restore natural arm and hand movements in people with upper limb paralysis.

Co-author of the study Dr Jennifer Collinger said: '10D control allowed Jan to interact with objects in different ways, just as people use their hands to pick up objects depending on their shapes and what they intend to do with them.

'We hope to repeat this level of control with additional participants and to make the system more robust, so that people who might benefit from it will one day be able to use brain-machine interfaces in daily life.

'We also plan to study whether the incorporation of sensory feedback, such as the touch and feel of an object, can improve neuroprosthetic control.'

Ms Scheuermann added: 'This has been a fantastic, thrilling, wild ride, and I am so glad I've done this.

'This study has enriched my life, given me new friends and co-workers, helped me contribute to research and taken my breath away. For the rest of my life, I will thank God every day for getting to be part of this team.'

'SIGN ME UP, I WANT TO DO THAT!'

Jan Scheuermann, 55, signed up to the University of Pittsburgh's study in 2012 and has nicknamed the arm Hector

In 1996, Jan Scheuermann was a 36-year-old mother of two, running a party business. 

One day she noticed her legs seemed to drag behind her.

Within two years, her legs and arms progressively weakened to the point that she required a wheelchair, as well as an attendant to assist her with dressing, eating, bathing and other day-to-day activities.

In 1998 she was diagnosed with spinocerebellar degeneration, in which the connections between the brain and muscles slowly, and inexplicably, deteriorate.

In February 2012, after screening tests to confirm that she was eligible for the study, Dr Elizabeth Tyler-Kabara from the University of Pittsburgh placed two quarter-inch square electrode grids with 96 tiny contact points each in the regions of Ms Scheuermann's brain that would normally control right arm and hand movement.

Two days after the operation, the team hooked up the two terminals that protrude from Ms Scheuermann's skull to the computer. 

Within a week, Ms Scheuermann could reach in and out, left and right, and up and down with the arm, which she named Hector, giving her 3D control that had her high-fiving with researchers.

Within three months she also could flex the wrist back and forth, move it from side to side and rotate it clockwise and counter-clockwise, as well as grip objects.

In a study task, called the Action Research Arm Test, Ms Scheuermann guided the arm from a position four inches above a table to pick up blocks and tubes of different sizes, a ball and a stone and put them down on a nearby tray.

She also picked up cones from one base to restack them on another a foot away, another task requiring grasping, transporting and positioning of objects with precision.