Soft sensory-neuromorphic system for closed-loop neuroprostheses

Abstract Prosthetic devices designed to assist individuals with damaged or missing body parts have made significant strides, particularly with advancements in machine intelligence and bioengineering. Initially focused on movement assistance, the field has shifted towards developing prosthetics that function as seamless extensions of the human body. During this progress, a key challenge remains the reduction of interface artifacts between prosthetic components and biological tissues. Soft electronics offer a promising solution due to their structural flexibility and enhanced tissue adaptability. However, achieving full integration of prosthetics with the human body requires both artificial perception and efficient transmission of physical signals. In this context, synaptic devices have garnered attention as next-generation neuromorphic computing elements because of their low power consumption, ability to enable hardware-based learning, and high compatibility with sensing units. These devices have the potential to create artificial pathways for sensory recognition and motor responses, forming a “sensory-neuromorphic system” that emulates synaptic junctions in biological neurons, thereby connecting with impaired biological tissues. Here, we discuss recent developments in prosthetic components and neuromorphic applications with a focus on sensory perception and sensorimotor actuation. Initially, we explore a prosthetic system with advanced sensory units, mechanical softness, and artificial intelligence, followed by the hardware implementation of memory devices that combine calculation and learning functions. We then highlight the importance and mechanisms of soft-form synaptic devices that are compatible with sensing units. Furthermore, we review an artificial sensory-neuromorphic perception system that replicates various biological senses and facilitates sensorimotor loops from sensory receptors, the spinal cord, and motor neurons. Finally, we propose insights into the future of closed-loop neuroprosthetics through the technical integration of soft electronics, including bio-integrated sensors and synaptic devices, into prosthetic systems.