Improved maximum frequency estimation with application to instantaneous mean frequency estimation of surface...

Area of Science:

• Signal Processing
• Biomedical Engineering
• Time-Frequency Analysis

Background:

• Accurate estimation of signal frequency content is crucial in various scientific and engineering fields.
• Existing methods for maximum frequency estimation, such as the threshold-crossing method (TCM), can be limited by noise.
• Improving frequency estimation is essential for reliable analysis of signals like surface electromyography (sEMG).

Purpose of the Study:

• To enhance the accuracy of maximum-frequency estimation for bandlimited signals corrupted by additive white noise.
• To compare the performance of modified existing methods with a novel proposed method.
• To evaluate the impact of these frequency estimation methods on instantaneous mean-frequency (IMNF) estimation.

Main Methods:

• Modification of the threshold-crossing method (TCM) and the hybrid method for time-frequency representations.
• Introduction and implementation of a novel running-block threshold method (RBTM).
• Assessment of methods using detection probability (sensitivity) and application to synthesized sEMG data with white noise.

Main Results:

• The running-block threshold method (RBTM) demonstrated improved maximum-frequency estimation compared to the threshold-crossing method (TCM).
• All three tested methods showed improvement in instantaneous mean-frequency (IMNF) estimation when applied to noisy synthesized sEMG.
• The RBTM provided the most accurate instantaneous mean-frequency (IMNF) estimate among the evaluated methods.

Conclusions:

• The running-block threshold method (RBTM) offers a superior approach for maximum-frequency estimation in noisy signals.
• Accurate maximum-frequency estimation is vital for improving the reliability of instantaneous mean-frequency (IMNF) calculations.
• The RBTM shows significant potential for applications requiring precise frequency analysis of biomedical signals.