A neural decoding method and device for upper limb movement direction

Abstract

The invention discloses a method and device for neural decoding of upper limb movement direction based on Riemannian metric, which extracts EEG signal feature information from nerve signals of upper limb movement direction in the process of motor tasks through Riemannian metric; Electrical signatures are used to identify the direction of upper limb movement. The present invention establishes an upper limb motion intention analysis model based on the EEG signal characteristic information based on the Riemann metric, so that the analysis model can obtain stable motion intention analysis performance in the state of cognitive concentration and cognitive distraction, which is very helpful for rehabilitation and assistance. important. At the same time, it provides a new idea for the study of upper limb motion decoding, and provides a basis for further research on human-computer collaborative interaction.

Description

technical field [0001] The invention belongs to the technical field of neuroscience, in particular to a method and device for neural decoding of upper limb motion direction based on Riemannian metrics. Background technique [0002] Motion intention analysis is an important research content in the field of human-machine collaboration. By detecting and analyzing human motion intentions, especially the motion direction intentions of the upper limbs, the human-computer interaction system can better cooperate and assist humans. In the field of rehabilitation medicine, the analysis of motion intentions can enable rehabilitation equipment to actively provide positive feedback to rehabilitation patients, thereby more effectively assisting them in sports rehabilitation training; in the field of industrial production, the analysis of motion intentions can enable industrial robots to understand workers. intention, so as to cooperate with workers to complete the task, reduce the worklo...

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Problems solved by technology

[0004] However, in the current research on motor intention decoding, most of them focus on the decoding of motor intention in the case of people performing a single task of sports, without taking into account the situation of multi-tasking and the state of concentration on motor tasks. Effect on decoding result

In an actual human-computer interaction system, when a person performs a specified motion task, he or she will inevitably be distracted by external factors or other tasks, resulting in distraction, which will affect the completion of the motion task, thus affecting the performance of the motion task. Decoding of motor intentions can make a difference

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