Brain-computer interface system based on clinic brain-electrical signal control machine hand movement and application thereof

Abstract

The invention discloses a brain-computer interface system based on clinic brain-electrical signal control machine hand movement. The brain-computer interface system comprises a signal collection module, a brain-electrical signal feature extraction and decoding module, a machine hand control module and a peripheral module, wherein the signal collection module is used for pretreating collected clinic brain-electrical signals and inputting the pretreated signals into the brain-electrical signal feature extraction and decoding module; the brain-electrical signal feature extraction and decoding module is used for extracting the features of the pretreated brain-electrical signals; the machine hand control module is used for classifying the features of the pretreated brain-electrical signals and sending classification labels to machine hands to complete gesture movement; and the peripheral module is used for supervising and feeding back a task executed by the machine hands. The invention also discloses an application method of the brain-computer interface system. High-precision online machine hand gesture control can be realized by utilizing the clinic cortical brain-electrical signals with relatively high temporal-spatial resolution and small invasion degree.

Description

technical field [0001] The invention belongs to the technical field of brain-computer interface, and in particular relates to a brain-computer interface system and an application thereof for controlling the movement of a manipulator based on clinical cortical EEG signals. Background technique [0002] Brain-computer interface is a new type of technology that allows users to directly control effectors (muscles, mice, keyboards, etc.) in real time by only using computing systems to analyze brain activity signals and convert them into control instructions. The clinical application and implementation of this technology can greatly help paralyzed patients or physically disabled people rebuild their motor functions. According to statistics from the China Disabled Persons' Federation, as of 2010, there were 24.72 million people with physical disabilities in China, most of whom were upper limb dysfunction and amputated or missing fingers. Therefore, the clinical application of brai...

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Problems solved by technology

Clinically, the cortical EEG signal has been used for long-term localization of refractory epilepsy lesions, and has mature related electrode implantation technology and postoperative intervention technology, but there are few related applications in the field of brain-computer interface

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