posted on 2021-05-14, 13:15authored byEvan D. Crotty, Laura-Anne M. Furlong, Kevin Hayes, Andrew J. Harrison
Objective. Accurate identification of surface electromyography (EMG) muscle onset is vital when
examining short temporal parameters such as electromechanical delay. The visual method is
considered the ‘gold standard’ in onset detection. Automatic detection methods are commonly
employed to increase objectivity and reduce analysis time, but it is unclear if they are sensitive enough
to accurately detect EMG onset when relating them to short-duration motor events. Approach. This
study aimed to determine: (1)if automatic detection methods could be used interchangeably with
visual methods in detecting EMG onsets(2)if the Teager–Kaiser energy operator(TKEO) as a
conditioning step would improve the accuracy of popular EMG onset detection methods. The
accuracy of three automatic onset detection methods: approximated generalized likelihood ratio
(AGLR), TKEO, and threshold-based method were examined against the visual method. EMG signals
from fast, explosive, and slow, ramped isometric plantarflexor contractions were evaluated using each
technique. Main results. For fast, explosive contractions, the TKEO was the best-performing automatic
detection method, with a low bias level(4.7 ± 5.6 ms) and excellent intraclass correlation coefficient
(ICC) of 0.993, however with wide limits of agreement (LoA) (−6.2 to +15.7 ms). For slow, ramped
contractions, the AGLR with TKEO conditioning was the best-performing automatic detection
method with the smallest bias(11.3 ± 32.9 ms) and excellent ICC(0.983) but produced wide LoA
(−53.2 to +75.8 ms). For visual detection, the inclusion of TKEO conditioning improved inter-rater
and intra-rater reliability across contraction types compared with visual detection without TKEO
conditioning. Significance. In conclusion, the examined automatic detection methods are not sensitive
enough to be applied when relating EMG onset to a motor event of short duration. To attain the
accuracy needed, visual detection is recommended. The inclusion of TKEO as a conditioning step
before visual detection of EMG onsets is recommended to improve visual detection reliability.
Funding
Using the Cloud to Streamline the Development of Mobile Phone Apps