Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges

Abstract

Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of existing interventions, as well as allow novel methodologies and technological synergies. New approaches attempt to partially overcome long-term disability caused by spinal cord injury, using either invasive bridging technologies or noninvasive human-machine interfaces. Muscular dystrophies benefit from electromyography and novel sensors that shed light on underlying neuromotor mechanisms in people with Duchenne. Novel wearable robotics devices are being tailored to specific patient populations, such as traumatic brain injury, stroke, and amputated individuals. In addition, developments in robot-assisted rehabilitation may enhance motor learning and generate movement repetitions by decoding the brain activity of patients during therapy. This is further facilitated by artificial intelligence algorithms coupled with faster electronics. The practical impact of integrating such technologies with neural rehabilitation treatment can be substantial. They can potentially empower nontechnically trained individuals-namely, family members and professional carers-to alter the programming of neural rehabilitation robotic setups, to actively get involved and intervene promptly at the point of care. This narrative review considers existing and emerging neural rehabilitation technologies through the perspective of replacing or restoring functions, enhancing, or improving natural neural output, as well as promoting or recruiting dormant neuroplasticity. Upon conclusion, we discuss the future directions for neural rehabilitation research, diagnosis, and treatment based on the discussed technologies and their major roadblocks. This future may eventually become possible through technological evolution and convergence of mutually beneficial technologies to create hybrid solutions.

Keywords: artificial intelligence; brain–computer interfaces; exoskeleton; human–robot interaction; neural interfaces; neurological disability; neurorehabilitation; robotics.

Figure 1

Illustrated schematic overview of the contents of this article and their connections.

Figure 2

Multiple immersive man-machine interfaces and a combination of facilitating technologies have been demonstrated to have synergistic effect in promoting adaptive neuroplasticity in chronic complete spinal cord injury; figure modified from Donati et al. 2016 [58]). BMI, brain–machine interface; BWS, body weight support; EEG, electroencephalography; EMG, electromyography; Tact, tactile feedback; VR, virtual reality.

Figure 3

Human–robot interfaces (HRIs) are interfacing the human (brain, muscle, and nerves) with a device by acquiring biological signals, decoding them, and translating them to control commands for various assistive, rehabilitation, or prosthetic devices.

Figure 4

Convergence of key technologies will synergistically enable complex applications of neural rehabilitation and improve outcomes of patients with disabilities.