A research team led by Chalmers University of Technology in Sweden announced on Mar. 19 that they have successfully decoded leg movements directly from the remaining nerves in people with above-knee amputations. The breakthrough was achieved using a combination of implantable neurotechnology and an artificial intelligence method based on the nervous system's own signaling patterns.
This development is significant because it could lead to prosthetic legs that feel and act more like natural limbs, giving amputees greater control and independence. Currently, most leg prostheses rely on mechanical systems and built-in sensors rather than direct user control, especially for those who have lost significant muscle tissue.
The study, published in Nature Communications, focused on interpreting nerve signals that remain active after amputation. Giacomo Valle, assistant professor at Chalmers and one of the study's senior authors, said: "When you tell your body to move, signals travel through the nerves to the muscles which carry out the action – even if the limb is no longer there. This means you can find all the information needed within those nerves. The major challenge is extracting that information and understanding the neural code behind it – and that's been the focus of our work." Valle also said: "If an implant can be connected directly to the remaining nerves, instead of through residual muscles, you can use exactly the same natural signals used to move your limbs. It greatly increases the potential to create prostheses with natural control, sensory feedback* and unprecedented resolution."
The researchers used ultrathin neural implants inserted into participants' sciatic nerve branches and applied a new AI-based technique called Spiking Neural Networks (SNNs) to interpret recorded nerve signals. Elisa Donati, professor at the University of Zurich and ETH Zürich and another senior author of the study, said: "Our study shows that decoding peripheral nerve** activity works best when it respects the language of the nervous system. Peripheral nerves communicate through discrete electrical impulses – or spikes – and spiking neural networks are therefore naturally suited to processing this type of signal. By aligning our computational models more closely with biology, we can extract movement intent efficiently, using compact models and relatively limited data. This is an important step towards low-power, fully implantable systems for more natural control of prosthetic limbs."
Valle explained further: "This is the first study to demonstrate that signals recorded directly from peripheral nerves can be used to accurately interpret intended leg movements in amputees. With this approach, we were able to map specific nerve signals to specific movements and predict, with high accuracy, which movements the participants were attempting." He added: "The study provides unique insight into how the nervous system transmits information. We've cracked the code of nerve communication and shown that it's possible to interpret detailed leg movements, even in amputations where most of the leg is gone. It was amazing to see how electrodes placed high up in what remains of a leg could decode attempts to wiggle the toes."
The technology allows for both motor control and restoring sensation using a single implantable device—a bidirectional system—rather than requiring multiple implants as before. Valle said: "Once electrodes are implanted inside the nerve, they can be used to communicate bidirectionally with the nervous system. So, for the first time, a single neurotechnology can provide both natural neural control and sensory feedback in the same implantable device."
The researchers describe their findings as proof-of-concept but plan next steps involving integration into real prosthetic legs for direct user testing. Valle concluded: "I believe these results could significantly influence the field. The next step is to integrate and test the technology into a prosthetic leg that can be controlled directly and that can return natural sensation."
