Median and Mean Frequency Analysis
Analysis of EMG signals in the frequency domain can provide useful insight into the nature of the EMG data. The frequency spectrum data may be used to generate other measures associated with EMG frequency analysis. Select an area of EMG data and use the Fast Fourier Transform function to perform a linear magnitude FFT on the selected data, then integrate the result to determine the median and mean frequency. AcqKnowledge® can be used to calculate these parameters after the EMG data has been collected. AcqKnowledge fully automates the frequency analysis process.
See Automated EMG Analysis and App Note 118 -EMG Frequency Signal Analysis for more information.
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Related Readings
Thongpanja, S. & Phinyomark, Angkoon & Limsakul, Chusak & Phukpattaranont, P.. (2015). Application of Mean and Median Frequency Methods for Identification of Human Joint Angles Using EMG Signal. Lecture Notes in Electrical Engineering. 339. 10.1007/978-3-662-46578-3_81.
Abstract: The analysis of surface electromyography (EMG) signals is generally based on three major issues, i.e., the detection of muscle force, muscle geometry, and muscle fatigue. Recently, there are not any techniques that can analyse all the issues. Mean frequency (MNF) and median frequency (MDF) have been successfully applied to be used as muscle force and fatigue indices in previous studies. However, there is the lack of consensus upon the effect of muscle geometry on the basis of varying joint angles. In this paper, the modification of MNF and MDF using a min-max normalization technique was proposed to provide a consistent relationship between feature value and joint angle across subjects… Keywords: Feature extraction, Frequency analysis, Muscle fatigue, Spectral analysis, Surface electromyography signal
Phinyomark, Angkoon & Thongpanja, S. & Hu, Huosheng & Phukpattaranont, P. & Limsakul, Chusak. (2012). The Usefulness of Mean and Median Frequencies in Electromyography Analysis. 10.5772/50639.
Abstract: Mean frequency (MNF) and median frequency (MDF) are two useful and popular frequency-domain features for electromyography analysis both in clinical and engineering applications. MNF and MDF are frequently used as the gold standard tool to detect fatigue in the target muscles using EMG signals. The effectiveness of MNF and MDF under many experimental conditions is presented and confirmed in this chapter…
Keywords: electromyography, muscle force, muscle geometry, muscle fatigue, human-computer interaction (HCI), ergonomics, occupational therapy, sport science
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