Tag Archives: Stanisa Raspopovic

Bioinspired, biomimetic stimulation for the next generation of neuroprosthetics

ETH researchers have developed a prosthetic leg that communicates with the brain via natural signals. (Photograph: Keystone) Courtesy: ETH Zurich

A February 21, 2024 ETH Zurich press release by Ori Schipper (also on EurekAlert) announces a ‘nature-inspired’ or bioinspired approach to neuroprosthetics,

Prostheses that connect to the nervous system have been available for several years. Now, researchers at ETH Zurich have found evidence that neuroprosthetics work better when they use signals that are inspired by nature.

In brief

*Neuroprostheses are electro-​mechanical devices that are connected to the nervous system. As yet, these are unable to provide natural communication with the brain. Instead, they often evoke artificial, unpleasant sensations, similar to a feeling of tingles over the skin.
*This paraesthesia might be caused by overstimulation of the nervous system. ETH Zurich researchers together with colleagues in Germany, Serbia and Russia have proposed that neuroprosthetics should transmit biomimetic signals that are easier for the brain to understand.
*These new findings are relevant to arm and leg prostheses as well as various other aids and devices, including spinal implants and electrodes for brain stimulation. 

A few years ago, a team of researchers working under Professor Stanisa Raspopovic at the ETH Zurich Neuroengineering Lab gained worldwide attention when they announced that their prosthetic legs had enabled amputees to feel sensations from this artificial body part for the first time. Unlike commercial leg prostheses, which simply provide amputees with stability and support, the ETH researchers’ prosthetic device was connected to the sciatic nerve in the test subjects’ thigh via implanted electrodes.

This electrical connection enabled the neuroprosthesis to communicate with the patient’s brain, for example relaying information on the constant changes in pressure detected on the sole of the prosthetic foot when walking. This gave the test subjects greater confidence in their prosthesis – and it enabled them to walk considerably faster on challenging terrains. “Our experimental leg prosthesis succeeded in evoking natural sensations. That’s something current neuroprostheses are mainly unable to do; instead, they mostly evoke artificial, unpleasant sensations,” Raspopovic says.

This is probably because today’s neuroprosthetics are using time-​constant electrical pulses to stimulate the nervous system. “That’s not only unnatural, but also inefficient,” Raspopovic says. In a recently published paper, he and his team used the example of their leg prostheses to highlight the benefits of using naturally inspired, biomimetic stimulation to develop the next generation of neuroprosthetics.

Model simulates activation of nerves in the sole

To generate these biomimetic signals, Natalija Katic – a doctoral student in Raspopovic’s research group – developed a computer model called FootSim. It is based on data collected by collaborators in Canada, who recorded the activity of natural receptors, named mechanoreceptors, in the sole of the foot while touching different points on the feet of volunteers with a vibrating rod.

The model simulates the dynamic behaviour of large numbers of mechanoreceptors in the sole of the foot and generates the neural signals that shoot up the nerves in the leg towards the brain – from the moment the heel strikes the ground and the weight of the body starts to shift forward to the outside of the foot until the toes push off the ground ready for the next step. “Thanks to this model, we can see how semsory receptors from the sole, and the connected nerves, behave during walking or running, which is experimentally impossible to measure” Katic says.

Information overload in the spinal cord

To assess how closely the biomimetic signals calculated by the model correspond to the signals emitted by real neurons, Giacomo Valle – a postdoc in Raspopovic’s research group – worked with colleagues in Germany, Serbia and Russia on experiments with cats, whose nervous system processes movement in a similar way to that of humans. The experiments took place in 2019 at the Pavlov Institute of Physiology in St. Petersburg and were carried out in accordance with the relevant European Union guidelines.

The researchers implanted electrodes, connecting some to the nerve in the leg and some to the spinal cord to discover how the signals are transmitted through the nervous system. When the researchers applied pressure to the bottom of the cat’s paw, thereby evoking the natural neural response that occurs when a cat takes a step, the peculiar pattern of activity recorded in the spinal cord did indeed resemble the patterns that were elicited in the spinal cord when the researchers stimulated the leg nerve with biomimetic signals.

By contrast, the conventional approach of time-​constant stimulation of the sciatic nerve in the cat’s thigh elicited a markedly different pattern of activation in the spinal cord. “This clearly shows that the commonly used stimulation methods cause the neural networks in the spine to be flooded with information,” Valle says. “This information overload could be the reason for the unpleasant sensations or paraesthesia reported by some users of neuroprosthetics,” Raspopovic adds.

Learning the language of the nervous system

In their clinical trial with leg amputees, the researchers were able to show that biomimetic stimulation is superior to time-​constant stimulation. Their work clearly demonstrated how the signals that mimicked nature produced better results: not only were the test subjects able to climb steps faster, they also made fewer mistakes in a task that required them to climb the same steps while spelling words backwards. “Biomimetic neurostimulation allows subjects to concentrate on other things while walking,” Raspopovic says, “so we concluded that this type of stimulation is more naturally processed and less taxing on the brain.”

Raspopovic, whose lab forms part of the ETH Institute of Robotics and Intelligent Systems, believes that these new findings are not only relevant to the limb prostheses he and his team have been working on for over half a decade. He argues that the need to move away from unnatural, time-​constant stimulation towards biomimetic signals also applies to a whole series of other aids and devices, including spinal implants and electrodes for brain stimulation. “We need to learn the language of the nervous system,” Raspopovic says. “Then we’ll be able to communicate with the brain in ways it really understands.”

Here’s a link to and a citation for the paper,

Biomimetic computer-to-brain communication enhancing naturalistic touch sensations via peripheral nerve stimulation by Giacomo Valle, Natalija Katic Secerovic, Dominic Eggemann, Oleg Gorskii, Natalia Pavlova, Francesco M. Petrini, Paul Cvancara, Thomas Stieglitz, Pavel Musienko, Marko Bumbasirevic & Stanisa Raspopovic. Nature Communications volume 15, Article number: 1151 (2024) DOI: https://doi.org/10.1038/s41467-024-45190-6 Published: 20 February 2024

This paper is open access.

It was a bit of a surprise to see mention of some Canadian collaborators with regard to the earlier work featuring FootSim, a computer model Here’s a link to and a citation to that paper, this version is housed at ETH Zurich,

Modeling foot sole cutaneous afferents: FootSim by Natalija Katic, Rodrigo Kazu Siqueira, Luke Cleland, Nicholas Strzalkowski, Leah Bent, Stanisa Raspopovic, and Hannes Saal. Originally published in: iScience 26(1), DOI https://doi.org/10.1016/j.isci.2022.105874 Publication date: 2023-01-20 Permanent link: https://doi.org/10.3929/ethz-b-000591102

This paper too is open access.

Feeling with a bionic finger

From what I understand one of the most difficult aspects of an amputation is the loss of touch, so, bravo to the engineers. From a March 8, 2016 news item on ScienceDaily,

An amputee was able to feel smoothness and roughness in real-time with an artificial fingertip that was surgically connected to nerves in his upper arm. Moreover, the nerves of non-amputees can also be stimulated to feel roughness, without the need of surgery, meaning that prosthetic touch for amputees can now be developed and safely tested on intact individuals.

The technology to deliver this sophisticated tactile information was developed by Silvestro Micera and his team at EPFL (Ecole polytechnique fédérale de Lausanne) and SSSA (Scuola Superiore Sant’Anna) together with Calogero Oddo and his team at SSSA. The results, published today in eLife, provide new and accelerated avenues for developing bionic prostheses, enhanced with sensory feedback.

A March 8, 2016 EPFL press release (also on EurekAlert), which originated the news item, provides more information about Sorenson’s experience and about the other tests the research team performed,

“The stimulation felt almost like what I would feel with my hand,” says amputee Dennis Aabo Sørensen about the artificial fingertip connected to his stump. He continues, “I still feel my missing hand, it is always clenched in a fist. I felt the texture sensations at the tip of the index finger of my phantom hand.”

Sørensen is the first person in the world to recognize texture using a bionic fingertip connected to electrodes that were surgically implanted above his stump.

Nerves in Sørensen’s arm were wired to an artificial fingertip equipped with sensors. A machine controlled the movement of the fingertip over different pieces of plastic engraved with different patterns, smooth or rough. As the fingertip moved across the textured plastic, the sensors generated an electrical signal. This signal was translated into a series of electrical spikes, imitating the language of the nervous system, then delivered to the nerves.

Sørensen could distinguish between rough and smooth surfaces 96% of the time.

In a previous study, Sorensen’s implants were connected to a sensory-enhanced prosthetic hand that allowed him to recognize shape and softness. In this new publication about texture in the journal eLife, the bionic fingertip attains a superior level of touch resolution.

Simulating touch in non-amputees

This same experiment testing coarseness was performed on non-amputees, without the need of surgery. The tactile information was delivered through fine, needles that were temporarily attached to the arm’s median nerve through the skin. The non-amputees were able to distinguish roughness in textures 77% of the time.

But does this information about touch from the bionic fingertip really resemble the feeling of touch from a real finger? The scientists tested this by comparing brain-wave activity of the non-amputees, once with the artificial fingertip and then with their own finger. The brain scans collected by an EEG cap on the subject’s head revealed that activated regions in the brain were analogous.

The research demonstrates that the needles relay the information about texture in much the same way as the implanted electrodes, giving scientists new protocols to accelerate for improving touch resolution in prosthetics.

“This study merges fundamental sciences and applied engineering: it provides additional evidence that research in neuroprosthetics can contribute to the neuroscience debate, specifically about the neuronal mechanisms of the human sense of touch,” says Calogero Oddo of the BioRobotics Institute of SSSA. “It will also be translated to other applications such as artificial touch in robotics for surgery, rescue, and manufacturing.”

Here’s a link to and a citation for the paper,

Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans by Calogero Maria Oddo, Stanisa Raspopovic, Fiorenzo Artoni, Alberto Mazzoni, Giacomo Spigler, Francesco Petrini, Federica Giambattistelli, Fabrizio Vecchio, Francesca Miraglia, Loredana Zollo, Giovanni Di Pino, Domenico Camboni, Maria Chiara Carrozza, Eugenio Guglielmelli, Paolo Maria Rossini, Ugo Faraguna, Silvestro Micera. eLife, 2016; 5 DOI: 10.7554/eLife.09148 Published March 8, 2016

This paper appears to be open access.