Phase characteristic extraction method for brain waves of compound imaginary movements of lower limbs

Abstract

The invention belongs to the field of bioengineering and computers, relating to a phase characteristic extraction method for brain waves of compound imaginary movements of lower limbs. The method comprises the following steps of: 1, collecting and preprocessing signals of brain waves of compound imaginary movements of lower limbs; 2, decomposing oscillation mode of brain waves of compound imaginary movements of lower limbs; 3, identifying characteristic oscillation mode; 4, extracting and identifying coordinate characteristic in functional areas; and 5, identifying mode identification. The method takes the unstability of the brain wave signals into consideration adequately, and has the maximum rate of identification of 87.8% which is obviously enhanced compared with 82.3% of the traditional method.

Description

Phase Feature Extraction Method of Compound Lower Limb Imagery Action EEG technical field The invention belongs to the fields of biomedical engineering and computers, and relates to a method for extracting phase features of EEG with complex imaginary actions of lower limbs. Background technique Brain-computer interface (Brain-Computer Interface, BCI) is to establish a direct information exchange and control channel between the human brain and computers or other electronic devices that does not depend on conventional brain output pathways (peripheral nerves and muscle tissue). A new human-computer interaction system. The earliest EEG signals applied to the brain-computer interface system are mainly spontaneous EEG signals, such as alpha (α) waves in EEG. However, this type of EEG signal mode is single, and it is impossible to truly achieve "consciousness control action", which seriously restricts the development of brain-computer interface systems. In recent years, schola...

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Problems solved by technology

However, it is extremely difficult to extract phase synchronization features of imaginary action potentials of the lower limbs. The main reason is that the functional area of ​​the cerebral cortex mapped by the movement of the lower limbs is a relatively narrow area in the parietal sulcus, and its spatial structure is already very differentiated. In addition, the EEG signals extracted by scalp electrodes have great dispersion and aliasing, which is not conducive to the acquisition and identification of source signals. This factor also makes it extremely difficult to extract energy features from EEG through simple lower limb movements.

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