In this paper different estimation techniques are evaluated for the assessment of electromechanical delay (EMD). The following techniques are compared for benchmarking purposes: envelope estimation and thresholding, with different subjective combinations of filters and thresholds, and a double threshold statistical detector (DTD). Performances are compared in terms of bias, standard deviation and erroneous detections of the estimations. DTD showed higher robustness and repeatability of results, guaranteed by the objective settings based on the statistical characteristics of the algorithm.
In this paper different estimation techniques are evaluated for the assessment of Electromechanical Delay (EMD). The following techniques are compared for benchmarking purposes: envelope estimation and thresholding, with different subjective combinations of filters and thresholds, and a double threshold statistical detector (DTD). Performance are compared in terms of bias, standard deviation and erroneous detections of the estimations. DTD showed higher robustness and repeatability of results, guaranteed by the objective settings based on the statistical characteristics of the algorithm.
Conforto, S., Mathieu, P.a., Schmid, M., Bibbo, D., Florestal, J.r., D'Alessio, T. (2006). How Much Can We Trust the Electromechanical Delay Estimated by Using Electromyography?. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (pp.1256-1259). NEW YORK : IEEE [10.1109/IEMBS.2006.259335].
How Much Can We Trust the Electromechanical Delay Estimated by Using Electromyography?
CONFORTO, SILVIA;SCHMID, Maurizio;BIBBO, DANIELE;
2006-01-01
Abstract
In this paper different estimation techniques are evaluated for the assessment of electromechanical delay (EMD). The following techniques are compared for benchmarking purposes: envelope estimation and thresholding, with different subjective combinations of filters and thresholds, and a double threshold statistical detector (DTD). Performances are compared in terms of bias, standard deviation and erroneous detections of the estimations. DTD showed higher robustness and repeatability of results, guaranteed by the objective settings based on the statistical characteristics of the algorithm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
