Online cranial nerve spike potential signal detection method, device and system based on adaptive threshold

An adaptive threshold and signal detection technology, applied in the field of brain nerve signal processing, can solve problems such as weak anti-interference ability of large-value noise, long calculation time, and weak neural signal extraction ability, etc., to achieve the effect of improving accuracy

Active Publication Date: 2021-07-02
ZHEJIANG UNIV
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Problems solved by technology

This method has weak anti-interference ability to large-value noise, and the ability to extract different neural signals is not strong
However, in order to combat the strong n

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  • Online cranial nerve spike potential signal detection method, device and system based on adaptive threshold
  • Online cranial nerve spike potential signal detection method, device and system based on adaptive threshold
  • Online cranial nerve spike potential signal detection method, device and system based on adaptive threshold

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[0023] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and do not limit the protection scope of the present invention.

[0024] In order to realize online real-time high-accuracy detection of different cranial nerve spike signals in an embedded processing system with limited computing resources, the embodiment provides an online cranial nerve spike signal detection method, device and system based on an adaptive threshold.

[0025] figure 1 It is a flow chart of an online brain nerve spike signal detection method based on an adaptive threshold provided by the embodiment. Such as figure 1 As shown, the online cranial nerve spike signal detection method provided by the embodiment includes t...

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Abstract

The invention discloses an online cranial nerve spike potential signal detection method, device and system based on an adaptive threshold, and the method comprises the steps: 1, determining an initial position, screening cranial nerve signals from the initial position according to an initialized signal minimum value and a signal difference value, obtaining a test sample, and determining a test period according to the length of the test sample; 2, taking the standard deviation of the first test sample in each test period as a noise band threshold value of each test period; 3, for each cranial neural signal in the test period, determining an adaptive threshold of the cranial neural signal according to the noise band threshold and a previous section of historical cranial neural signal until the current cranial neural signal; and 4, screening a reference brain neural signal point according to the brain neural signal and the corresponding adaptive threshold, and extracting a spike potential signal according to the reference brain neural signal point. Therefore, the detection accuracy is improved while the online detection calculation consumption is reduced.

Description

technical field [0001] The invention relates to the technical field of cranial nerve signal processing, in particular to an online cranial nerve spike signal detection method, device and system based on an adaptive threshold. Background technique [0002] In the field of brain neural signal processing technology, online processing of real-time sampled high-throughput signals is generally required. In neuroelectrophysiological experiments, a single electrode usually records the activity of more than one neuron, and due to the influence of noise signals such as myoelectric activity and electromagnetic interference, it is necessary for the spike signal detection algorithm to have strong anti-interference ability and low algorithm complexity And it can be calculated in real time, without using global information, and can process brain nerve signals online. [0003] The existing high-accuracy cranial nerve signal processing methods are mostly offline methods, common single-thres...

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Application Information

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IPC IPC(8): A61B5/372A61B5/388
CPCA61B5/7235A61B5/72A61B5/7203
Inventor 田翔陈耀武黄利高翔
Owner ZHEJIANG UNIV
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