Imperial researchers have decoded the signals between hand movements and the brain, paving the way for more natural-feeling prosthetics.
In the study, published in Science Robotics, researchers unpicked the connections between hand movement patterns and the control patterns from motoneurons in the spinal cord. They were able to decipher these patterns using technology that picks up electrical signals from the muscles as they contract. They then applied the same patterns to the actuators of a soft robotic hand so that it could mimic a person's natural movement and control.
The researchers' goal was to find an alternative to the current model of prosthetic limbs, which are often abandoned by users because they do not respond in a 'natural' way to their movement and control needs.
They tested the innovative design in real-time scenarios with three prosthesis users. The trials showed that users could control the prosthetic in a more intuitive way compared to current models, enabling them to perform tasks like gripping and manipulating objects with ease.
"The combination of bioengineering and robotic technology has opened the door to a new era of prosthetics." Professor Dario Farina Chair in Neurorehabilitation Engineering, Department of Bioengineering
Professor Dario Farina, from Imperial College London's Department of Bioengineering, said: "Our innovative approach of combining bioengineering and robotic technology has opened the door to a new era of prosthetics. The increased freedom and independence limbs like our soft robotic hand offer could be transformational for the millions of people around the world who rely on such technology."
Professor Farina collaborated with Professor Antonio Bicchi at the Italian Institute of Technology in Genoa, on the project 'Natural BionicS', funded by the European Research Council.
Decoding synergies of spinal motoneurons and movement
The study focused on 'synergies', which in this context refer to the coordinated patterns of muscle activity and joint movements that the body uses to perform tasks. When we move, different muscles and joints should work together in a well-organised way to produce smooth and effective motions. For example, when you reach for an object, your arm, hand, and fingers all move in a coordinated manner to grasp it. This coordination is not random; it follows specific patterns, or 'synergies', that the brain and nervous system have organised and that can be decoded.
The researchers found that the synergies at the level of spinal motoneurons and those at the level of hand behaviours are linked, which means the way we hold or move our hands can be traced back to certain patterns in our nervous system. These patterns can be detected by reading the electrical signals created by activity in the spinal cord nerve cells that control muscle movements. By decoding these signals, scientists can identify which specific groups of nerve cells are responsible for different hand movements.
For the central nervous system to recognise a bionic limb as 'natural', it is essential for the prosthesis to interact with the environment in the same way a human limb would. Plus, it is the combination of novel synergy based control and postural synergy based prosthetic hand that enables us to mimic human dexterity. This led the researchers to combine the theory of sensorimotor synergies and robotic technology in their design of a bionic hand that can be controlled using the same patterns.
Mimicking human dexterity
The bionic hand was also designed with two degrees of actuation that controlled a much greater number of degrees of freedom. The actuations controlled two postures or synergies that could be linearly combined to obtain an infinite number of postures in a two-dimensional space. This combination resulted in a prosthesis that closely mimics the functionality and fluidity of a human limb, allowing for more natural movement and coordinated control.
Co-first author and Research Associate at Imperial's Department of Bioengineering Dr Deren Barsakcioglu said: "Our research aims to create prosthetic hands that not only look natural but also feel intuitive to use. By integrating design elements inspired by natural hand postures with control systems that decode synergistic neural signals, we're taking an important step toward enhancing everyday quality of life for users."
In the future, researchers believe this could lead to prosthetics that feel even more natural and the findings could even pave the way for integrating humans with robotic parts in new ways, benefiting a wide range of applications beyond prosthetics.
Read the full paper in Science Robotics here.
