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Preparation of EMG data and derivation of steps taken during suppressive sonication

HK Hyun-Chul Kim
WL Wonhye Lee
JK Jennifer Kunes
KY Kyungho Yoon
JL Ji Eun Lee
LF Lori Foley
KK Kavin Kowsari
SY Seung-Schik Yoo
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The acquired EMG data were preprocessed using MATLAB R2019b (Mathworks, Natick, MA). First, signal noises including cardiorespiratory signal fluctuation were reduced using a high-pass filter of 20 Hz (via “highpass” MATLAB function with the steepness parameter of 0.95)68 and 60 Hz notch-filter. Then, full-wave rectification and Gaussian smoothing (with a temporal window of 44 ms) were applied18.

The number of steps taken per time segment, measured during treadmill walking, was computed from both hind limbs using MATLAB’s ‘findpeaks’ algorithm based on the preprocessed EMG signals. The video data were also cross-referenced to validate the number of steps. The averaged values of the number of steps from each hind limb were then calculated and compared across experimental conditions. For the ANOVA analysis, the missing data due to data exclusion were substituted using the “Series mean” approach in the SPSS software (IBM, Amrok, NY).

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