US-Spine – Interfacing the human spinal cord with ultrasound

Human movement relies on the communication between the brain and the muscles via the nerves. Suppose this communication is limited or non-existent due to peripheral nerve trauma. In that case, performing daily tasks will be difficult or impossible. To simplify or enable communication, efforts have been put into recording biological signals from the limb to communicate with a robotic arm or machine, i.e., a neural interface.

A neural interface can rehabilitate people with spinal cord injuries, control upper limb prostheses, and assist people using exoskeletons. Today's neural interfaces are based on detecting spinal motoneuron activity with surface electromyography (EMG). However, surface EMG only detects superficial muscle activity and is biased towards subjects with characteristics rarely coinciding with most patient categories. Thus limiting their usefulness and applicability.

Therefore, we must shift the focus to other techniques that can provide a natural neural interface that overcomes such limitations. Preferably a technique that could potentially interface all motoneurons innervating the muscle.

This proposal aims to develop a neural interface between spinal motoneurons and 3D ultrafast ultrasound using local muscle movements as a proxy for identifying neural activity. For this purpose, methods will be developed, and the technology will be demonstrated using upper limb prostheses as a representative case study. The three specific objectives are:

1) To develop and evaluate a method that compensates probe shifts and tracks muscle deformation in ultrafast ultrasound imaging during muscle contractions.
2) To develop and evaluate a robust decomposition method of ultrafast ultrasound images for real-time motoneuron identification.
3) To evaluate the precision of the neural interface using standardised hand movements from healthy subjects and trans-radial amputees as a representative application scenario.