Neurostimulation artifact removal for implantable sensors improves signal clarity and decoding of motor volition

When we electrically stimulate the nerves of people with amputation, they can feel sensations on their missing limb, which we can use to provide them with feedback from their prosthetic hand. However, these electrical stimulations may also be picked up on the implanted sensors used to control the prosthesis. When this happens, these stimulations can sometimes cause the prosthesis to move uncontrollably or unpredictably. To address this issue, we developed and tested two stimulation artifact removal algorithms can learn to filter out these stimulations from the prosthesis control signals. In doing so, we demonstrated the ability to improve the quality of these control signals, as well as to improve the user’s ability to control their prosthetic hand simultaneously with nerve stimulation. Overall, this will improve our people’s experience when using sensory feedback at home to feel the objects they are interacting with, without having to sacrifice their control over their prostheses.