On the Calculation of Sample Entropy Using Continuous and Discrete Human Gait Data
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On the Calculation of Sample Entropy Using Continuous and Discrete Human Gait Data. / McCamley, John D.; Denton, William; Arnold, Andrew; Raffalt, Peter C.; Yentes, Jennifer M.
In: Entropy, Vol. 20, No. 10, 764 , 2018.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - On the Calculation of Sample Entropy Using Continuous and Discrete Human Gait Data
AU - McCamley, John D.
AU - Denton, William
AU - Arnold, Andrew
AU - Raffalt, Peter C.
AU - Yentes, Jennifer M.
PY - 2018
Y1 - 2018
N2 - Sample entropy (SE) has relative consistency using biologically-derived, discrete data >500 data points. For certain populations, collecting this quantity is not feasible and continuous data has been used. The effect of using continuous versus discrete data on SE is unknown, nor are the relative effects of sampling rate and input parameters m (comparison vector length) and r (tolerance). Eleven subjects walked for 10-minutes and continuous joint angles (480 Hz) were calculated for each lower-extremity joint. Data were downsampled (240, 120, 60 Hz) and discrete range-of-motion was calculated. SE was quantified for angles and range-of-motion at all sampling rates and multiple combinations of parameters. A differential relationship between joints was observed between range-of-motion and joint angles. Range-of-motion SE showed no difference; whereas, joint angle SE significantly decreased from ankle to knee to hip. To confirm findings from biological data, continuous signals with manipulations to frequency, amplitude, and both were generated and underwent similar analysis to the biological data. In general, changes to m, r, and sampling rate had a greater effect on continuous compared to discrete data. Discrete data was robust to sampling rate and m. It is recommended that different data types not be compared and discrete data be used for SE.
AB - Sample entropy (SE) has relative consistency using biologically-derived, discrete data >500 data points. For certain populations, collecting this quantity is not feasible and continuous data has been used. The effect of using continuous versus discrete data on SE is unknown, nor are the relative effects of sampling rate and input parameters m (comparison vector length) and r (tolerance). Eleven subjects walked for 10-minutes and continuous joint angles (480 Hz) were calculated for each lower-extremity joint. Data were downsampled (240, 120, 60 Hz) and discrete range-of-motion was calculated. SE was quantified for angles and range-of-motion at all sampling rates and multiple combinations of parameters. A differential relationship between joints was observed between range-of-motion and joint angles. Range-of-motion SE showed no difference; whereas, joint angle SE significantly decreased from ankle to knee to hip. To confirm findings from biological data, continuous signals with manipulations to frequency, amplitude, and both were generated and underwent similar analysis to the biological data. In general, changes to m, r, and sampling rate had a greater effect on continuous compared to discrete data. Discrete data was robust to sampling rate and m. It is recommended that different data types not be compared and discrete data be used for SE.
KW - range of motion
KW - joint angle
KW - gait
KW - complexity
KW - regularity
U2 - 10.3390/e20100764
DO - 10.3390/e20100764
M3 - Journal article
C2 - 30853788
VL - 20
JO - Entropy
JF - Entropy
SN - 1099-4300
IS - 10
M1 - 764
ER -
ID: 209466875