The flexibility and dexterity of human limbs rely on the processing of a vast quantity of signals within the sensory-motor networks in the brain and spinal cord, distilled into stimuli that govern the commands and movements. Hence, the use of assistive devices, such as robotic limbs or exoskeletons, is critically dependent on the processing of a large number of heterogeneous signals to mimic natural movements. This article provides a panoramic overview of the three paradigms for the control of bionic limbs based on mechatronic technology. Two of them have already been established in the literature, while the third one, advocated by this article, is an emerging approach, enabled by the latest developments in connectivity and computation. In the first paradigm, the bionic limbs rely on conventional control and are directly reconnected to the human sensory-motor system, which requires a large signal processing bandwidth. The second paradigm is based on semiautonomous limbs, endowed with context-aware processing and certain decision capability. Following the advances in wireless connectivity and cloud/edge processing, this article introduces a third paradigm of connected limbs.

A connected limb goes beyond replacement and toward augmentation of human motor skills, offering the possibility for remote interactions and interventions from medical professionals as well as updating the limb based on large-scale learning. Besides the generic use cases for connected limbs, we present early prototypes and results along with the associated signal processing challenges that emerge in distributed settings with communication latency and transmission impairments. The overall conclusion is that the concepts and uses of connected limbs promise an interesting new era for this assistive technology.