TY - JOUR
T1 - Gait Event Detection from Accelerometry Using the Teager-Kaiser Energy Operator
AU - Flood, Matthew William
AU - O'Callaghan, Ben P.F.
AU - Lowery, Madeleine M.
N1 - Funding Information:
Manuscript received November 16, 2018; revised April 4, 2019; accepted May 23, 2019. Date of publication May 28, 2019; date of current version February 19, 2020. This work was supported in part by the Science Foundation Ireland under Grant SFI/12/RC/2289 and in part by the European Research Council under Grant ERC-2014-CoG-646923. (Corresponding author: Matthew William Flood.) M. W. Flood is with the Neuromuscular Systems Research Group, School of Electrical and Electronic Engineering and the Insight Centre for Data Analytics, O’Brien Centre for Science, University College Dublin, Belfield D04 V1W8, Ireland (e-mail:,matthew.flood@ucdconnect.ie).
Publisher Copyright:
© 1964-2012 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - Objective: A novel method based on the application of the Teager-Kaiser Energy Operator is presented to estimate instances of initial contact (IC) and final contact (FC) from accelerometry during gait. The performance of the proposed method was evaluated against four existing gait event detection (GED) methods under three walking conditions designed to capture the variance of gait in real-world environments. Methods: A symmetric discrete approximation of the Teager-Kaiser energy operator was used to capture simultaneous amplitude and frequency modulations of the shank acceleration signal at IC and FC during flat treadmill walking, inclined treadmill walking, and flat indoor walking. Accuracy of estimated gait events were determined relative to gait events detected using force-sensitive resistors. The performance of the proposed algorithm was assessed against four established methods by comparing mean-absolute error, sensitivity, precision, and F1-score values. Results: The proposed method demonstrated high accuracy for GED in all walking conditions, yielding higher F1-scores (IC: >0.98, FC: >0.9) and lower mean-absolute errors (IC: <0.018s, FC: <0.039s) than other methods examined. Estimated ICs from shank-based methods tended to exhibit unimodal distributions preceding the force-sensitive resistor estimated ICs, whereas estimated gait events for waist-based methods had quasiuniform random distributions and lower accuracy. Conclusion: Compared with the established gait event detection methods, the proposed method yielded comparably high accuracy for IC detection, and was more accurate than all other methods examined for FC detection. Significance: The results support the use of the Teager-Kaiser Energy Operator for accurate automated GED across a range of walking conditions.
AB - Objective: A novel method based on the application of the Teager-Kaiser Energy Operator is presented to estimate instances of initial contact (IC) and final contact (FC) from accelerometry during gait. The performance of the proposed method was evaluated against four existing gait event detection (GED) methods under three walking conditions designed to capture the variance of gait in real-world environments. Methods: A symmetric discrete approximation of the Teager-Kaiser energy operator was used to capture simultaneous amplitude and frequency modulations of the shank acceleration signal at IC and FC during flat treadmill walking, inclined treadmill walking, and flat indoor walking. Accuracy of estimated gait events were determined relative to gait events detected using force-sensitive resistors. The performance of the proposed algorithm was assessed against four established methods by comparing mean-absolute error, sensitivity, precision, and F1-score values. Results: The proposed method demonstrated high accuracy for GED in all walking conditions, yielding higher F1-scores (IC: >0.98, FC: >0.9) and lower mean-absolute errors (IC: <0.018s, FC: <0.039s) than other methods examined. Estimated ICs from shank-based methods tended to exhibit unimodal distributions preceding the force-sensitive resistor estimated ICs, whereas estimated gait events for waist-based methods had quasiuniform random distributions and lower accuracy. Conclusion: Compared with the established gait event detection methods, the proposed method yielded comparably high accuracy for IC detection, and was more accurate than all other methods examined for FC detection. Significance: The results support the use of the Teager-Kaiser Energy Operator for accurate automated GED across a range of walking conditions.
KW - Accelerometry
KW - final contact
KW - gait event detection
KW - initial contact
KW - shank mounted
KW - Teager-Kaiser energy operator
KW - treadmill walking
KW - waist mounted
UR - http://www.scopus.com/inward/record.url?scp=85081046089&partnerID=8YFLogxK
U2 - 10.1109/TBME.2019.2919394
DO - 10.1109/TBME.2019.2919394
M3 - Article
C2 - 31150328
AN - SCOPUS:85081046089
SN - 0018-9294
VL - 67
SP - 658
EP - 666
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
IS - 3
M1 - 8723520
ER -