The invention discloses a clinical application-oriented cloud edge
hybrid AI artificial
spinal cord system and a control method, and relates to the technical field of neural
engineering and brain-computer interfaces. The
system comprises a neural
signal acquisition module, a multi-mode
perception fusion module, an edge real-
time control unit, a cloud intelligent training unit, a
nerve stimulation output module, a somatosensory feedback module, a clinical-level safety fusion module and a
wireless communication module. According to the invention, a core architecture of low-
delay real-
time control at an edge end less than or equal to 15ms, cloud individualized AI model training,
rehabilitation process dynamic
adaptation and networking non-inductive upgrading is adopted, the motion intention decoding accuracy is improved through multi-
modal sensing fusion, and the use security and data privacy are guaranteed through a clinical-level
security compliance system; the motion function of the patient with the
spinal cord transection injury can be reconstructed, the control strategy can be dynamically optimized according to the
rehabilitation process of the patient, and the lifelong iteration upgrading of the system is realized. The problems that in the prior art, pure
edge computing power is insufficient, pure cloud
delay is too high, individual
adaptation and clinical compliance core pain points are lacked are solved, the motion intention recognition accuracy is larger than or equal to 98%, clinical conversion can be directly achieved, the method is suitable for
rehabilitation of diseases such as
spinal cord injury, cerebral apoplexy and
cerebral palsy and
nerve function replacement, and the commercialized application prospect is wide.