Robust Method for Estimating Motor Unit Firing-pattern Statistics
Overview
Medical Informatics
Affiliations
An error-filtered estimation (EFE) algorithm for estimating the mean and standard deviation of a set of time intervals between consecutive motor unit firing times (inter-pulse intervals (IPIs)) is described. As the input IPI data are filtered and only valid IPIs are used to estimate mean and standard deviation values, the EFE algorithm provides accurate estimates even when the data defining the train of motor unit firing times are only partially complete or have several erroneous firing times. The algorithm has been evaluated using both simulated and real motor unit firing time data, and has been found to provide accurate and unbiased mean and standard deviation estimates, even when up to 70% of the IPI data are incorrect.
Exact inter-discharge interval distribution of motor unit firing patterns with gamma model.
Navallas J, Porta S, Malanda A Med Biol Eng Comput. 2019; 57(5):1159-1171.
PMID: 30685857 PMC: 6476863. DOI: 10.1007/s11517-018-01947-y.
Validating motor unit firing patterns extracted by EMG signal decomposition.
Parsaei H, Nezhad F, Stashuk D, Hamilton-Wright A Med Biol Eng Comput. 2010; 49(6):649-58.
PMID: 21042949 DOI: 10.1007/s11517-010-0703-1.
Ling S, Conwit R, Ferrucci L, Metter E Arch Phys Med Rehabil. 2009; 90(7):1237-40.
PMID: 19577038 PMC: 5496096. DOI: 10.1016/j.apmr.2008.09.565.
Decomposition of indwelling EMG signals.
Nawab S, Wotiz R, De Luca C J Appl Physiol (1985). 2008; 105(2):700-10.
PMID: 18483170 PMC: 2519944. DOI: 10.1152/japplphysiol.00170.2007.
Adaptive certainty-based classification for decomposition of EMG signals.
Rasheed S, Stashuk D, Kamel M Med Biol Eng Comput. 2006; 44(4):298-310.
PMID: 16937171 DOI: 10.1007/s11517-006-0033-5.