TY - GEN
T1 - A physiologically and biomechanically approximate model for surface electromyography amplitude estimation
AU - Choi, Changmok
AU - Lee, Hae Dong
AU - Kim, Jung
PY - 2011
Y1 - 2011
N2 - Surface electromygraphy (sEMG) provides information of the neural drive to the muscle, so muscle force estimation by sEMG is of high relevance in biomechanical studies and in bionic applications. Even though mean absolute value (MAV) has been widely used for sEMG amplitude estimation due to the probabilistic nature of sEMG, but it has been used without any comprehensive physiological justification. A physiologically and biomechanically approximate model for the force estimation would enable a clear understanding of the relationships between sEMG and the force, and it can be used as sEMG amplitude estimation method. We proposed a new sEMG amplitude estimation method comprising two procedures: MUAP (motor unit action potential) event detection and muscle force indication using a biomechanical muscle model. The estimation performances were evaluated with nine subjects and compared with MAV. The performance (R 2) of the proposed method (0.94 ± 0.03) outperformed it of MAV (0.90 ± 0.02). The method we proposed should be widely applicable to quantitatively analysis muscle activities by sEMG.
AB - Surface electromygraphy (sEMG) provides information of the neural drive to the muscle, so muscle force estimation by sEMG is of high relevance in biomechanical studies and in bionic applications. Even though mean absolute value (MAV) has been widely used for sEMG amplitude estimation due to the probabilistic nature of sEMG, but it has been used without any comprehensive physiological justification. A physiologically and biomechanically approximate model for the force estimation would enable a clear understanding of the relationships between sEMG and the force, and it can be used as sEMG amplitude estimation method. We proposed a new sEMG amplitude estimation method comprising two procedures: MUAP (motor unit action potential) event detection and muscle force indication using a biomechanical muscle model. The estimation performances were evaluated with nine subjects and compared with MAV. The performance (R 2) of the proposed method (0.94 ± 0.03) outperformed it of MAV (0.90 ± 0.02). The method we proposed should be widely applicable to quantitatively analysis muscle activities by sEMG.
UR - http://www.scopus.com/inward/record.url?scp=84055200378&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84055200378&partnerID=8YFLogxK
U2 - 10.1109/IEMBS.2011.6091015
DO - 10.1109/IEMBS.2011.6091015
M3 - Conference contribution
C2 - 22255238
AN - SCOPUS:84055200378
SN - 9781424441211
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 4086
EP - 4089
BT - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
T2 - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Y2 - 30 August 2011 through 3 September 2011
ER -