Auditory sense attention characteristic extraction and recognition system and method based on middle latency auditory evoked potential

Abstract

The invention discloses an auditory sense attention characteristic extraction and recognition system and method based on middle latency auditory evoked potential. The system comprises an equipment control module, a data storage unit, a stimulus sound generating device, a data acquisition device and a data processing and analyzing module. The stimulus sound generating device, the data acquisition device and the data processing and analyzing module are connected with the equipment control module, and the data storage unit is connected with the equipment control module, the data acquisition device and the data processing and analyzing module. Effective event related potential can be induced, and the energy, variance, area, AR model coefficient and waveform peak value are calculated as characteristic values. Finally, classification is carried out through a mode recognition algorithm. The experimental result shows that the average accuracy of eight testees with an artificial neural network (ANN) as a classifier can reach 77.2%. The experimental scheme of the design is convenient, simple and effective.

Description

technical field [0001] The invention relates to the field of auditory cognition of auditory evoked potentials, in particular to a system and method for extracting and identifying auditory attention features based on medium latency auditory evoked potentials. Background technique [0002] Visual impairment has brought great troubles to patients' daily life, and often patients with limited vision have intact auditory systems. Assessment of auditory cognitive ability can provide an important basis for clinical disease diagnosis and cognitive science research. However, the research time based on the auditory brain-computer interface (BCI) is not very long, and the research time based on the visual BCI system is longer and more mature, and its paradigm also has great reference significance for the auditory BCI system. However, many visually impaired patients with locked-in syndrome cannot use the brain-computer interface system based on the visual paradigm. channels of communic...

AI Technical Summary

Problems solved by technology

[0007] 1. The induction time is long, for example, the induction time of the experimental paradigm of P300 needs about 300ms

[0008] 2. Based on the above four experimental paradigms, the system is relatively complex

The sound sequence is a single sound stream, and the subject needs to distinguish the target stimulus from the non-target stimulus, so there is a disadvantage that the subject needs to wait for the arrival of the target stimulus

[0009] 3. The above four experimental paradigms use more electrode sheets, which is very inconvenient for signal acquisition

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