Method and system for accurately evaluating individual Alpha frequency range
Through adaptive determination of the optimal time scale and multi-scale sliding window method, combined with denoising preprocessing and baseline correction, the problem of unstable Alpha frequency range evaluation in the prior art is solved, and the accuracy and stability of the evaluation are improved.
CN119719624APending Publication Date: 2025-03-28SHANGHAI NAOYUN TECHNOLOGY CO LTD
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Patent Information
- Application Number
- CN202411791178.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-06
- Publication Date
- 2025-03-28
AI Technical Summary
Technical Problem
Prior art When evaluating individual Alpha frequency ranges, improper time scale selection leads to unstable peak detection and makes it difficult to achieve universality and stability.
Method used
The optimal time scale is determined through adaptive determination, and the multi-scale sliding window method is used, combining denoising pre-processing and baseline correction, the peak frequency and range are calculated, and the band range is adjusted to improve frequency stability.
Benefits of technology
It improves the accuracy and stability of Alpha frequency range evaluation, reduces the impact of improper time scale selection on peak detection, and ensures the stability and reliability of the evaluation results.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention relates to the field of signal analysis, and discloses a method and system for accurately evaluating an individual Alpha frequency range, and the method comprises the steps: calculating a peak frequency average value and a mean square error sigma of all original electroencephalogram signal samples, and obtaining a first peak frequency average value; segmenting the original electroencephalogram signal sample according to a segmented window size, calculating a peak frequency of each segment, and then calculating an average value of the segmented peak frequencies to obtain a second average value of the peak frequencies; calculating a difference value between the first peak frequency average value and the second peak frequency average value, judging whether the peak frequency is stable or not, and if so, turning to the step 6; and if not, modifying the preset wave band range to be + / -2.5 Hz of the second peak frequency average value, and returning to the step 2. According to the invention, the accuracy of Alpha frequency range evaluation is improved.
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