Calculating sample entropy from isometric torque signals: methodological considerations and recommendations
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Calculating sample entropy from isometric torque signals : methodological considerations and recommendations. / Raffalt, Peter C.; Yentes, Jennifer M.; Freitas, Sandro R.; Vaz, João R.
In: Frontiers in Physiology, Vol. 14, 1173702, 2023.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Calculating sample entropy from isometric torque signals
T2 - methodological considerations and recommendations
AU - Raffalt, Peter C.
AU - Yentes, Jennifer M.
AU - Freitas, Sandro R.
AU - Vaz, João R.
N1 - Publisher Copyright: Copyright © 2023 Raffalt, Yentes, Freitas and Vaz.
PY - 2023
Y1 - 2023
N2 - We investigated the effect of different sampling frequencies, input parameters and observation times for sample entropy (SaEn) calculated on torque data recorded from a submaximal isometric contraction. Forty-six participants performed sustained isometric knee flexion at 20% of their maximal contraction level and torque data was sampled at 1,000 Hz for 180 s. Power spectral analysis was used to determine the appropriate sampling frequency. The time series were downsampled to 750, 500, 250, 100, 50, and 25 Hz to investigate the effect of different sampling frequency. Relative parameter consistency was investigated using combinations of vector lengths of two and three and tolerance limits of 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, and 0.4, and data lengths between 500 and 18,000 data points. The effect of different observations times was evaluated using Bland-Altman plot for observations times between 5 and 90 s. SaEn increased at sampling frequencies below 100 Hz and was unaltered above 250 Hz. In agreement with the power spectral analysis, this advocates for a sampling frequency between 100 and 250 Hz. Relative consistency was observed across the tested parameters and at least 30 s of observation time was required for a valid calculation of SaEn from torque data.
AB - We investigated the effect of different sampling frequencies, input parameters and observation times for sample entropy (SaEn) calculated on torque data recorded from a submaximal isometric contraction. Forty-six participants performed sustained isometric knee flexion at 20% of their maximal contraction level and torque data was sampled at 1,000 Hz for 180 s. Power spectral analysis was used to determine the appropriate sampling frequency. The time series were downsampled to 750, 500, 250, 100, 50, and 25 Hz to investigate the effect of different sampling frequency. Relative parameter consistency was investigated using combinations of vector lengths of two and three and tolerance limits of 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, and 0.4, and data lengths between 500 and 18,000 data points. The effect of different observations times was evaluated using Bland-Altman plot for observations times between 5 and 90 s. SaEn increased at sampling frequencies below 100 Hz and was unaltered above 250 Hz. In agreement with the power spectral analysis, this advocates for a sampling frequency between 100 and 250 Hz. Relative consistency was observed across the tested parameters and at least 30 s of observation time was required for a valid calculation of SaEn from torque data.
KW - motor control
KW - muscle contraction
KW - nonlinear analysis
KW - regularity
KW - time series
U2 - 10.3389/fphys.2023.1173702
DO - 10.3389/fphys.2023.1173702
M3 - Journal article
C2 - 37324377
AN - SCOPUS:85162012210
VL - 14
JO - Frontiers in Physiology
JF - Frontiers in Physiology
SN - 1664-042X
M1 - 1173702
ER -
ID: 367292333