Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=21669791
&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215
Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\21669791
.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117 Integr+Comp+Biol
2008 ; 48
(2
): 283-93
Nephropedia Template TP
gab.com Text
Twit Text FOAVip
Twit Text #
English Wikipedia
Variation in EMG activity: a hierarchical approach
#MMPMID21669791
German RZ
; Crompton AW
; Thexton AJ
Integr Comp Biol
2008[Aug]; 48
(2
): 283-93
PMID21669791
show ga
Recordings of naturally occurring Electromyographic (EMG) signals are variable.
One of the first formal and successful attempts to quantify variation in EMG
signals was Shaffer and Lauder's (1985) study examining several levels of
variation but not within muscle. The goal of the current study was to quantify
the variation that exists at different levels, using more detailed measures of
EMG activity than did Shaffer and Lauder (1985). The importance of accounting for
different levels of variation in an EMG study is both biological and statistical.
Signal variation within the same muscle for a stereotyped action suggests that
each recording represents a sample drawn from a pool of a large number of motor
units that, while biologically functioning in an integrated fashion, showed
statistical variation. Different levels of variation for different muscles could
be related to different functions or different tasks of those muscles. The
statistical impact of unaccounted or inappropriately analyzed variation can lead
to false rejection (type I error) or false acceptance (type II error) of the null
hypothesis. Type II errors occur because such variation will accrue to the error,
reducing power, and producing an artificially low F-value. Type I errors are
associated with pseudoreplication, in which the replicated units are not truly
independent, thereby leading to inflated degrees of freedom, and an underestimate
of the error mean square. To address these problems, we used a repeated measures,
nested multifactor model to measure the relative contribution of different
hierarchical levels of variation to the total variation in EMG signals during
swallowing. We found that variation at all levels, among electrodes in the same
muscle, in sequences of the same animal, and among individuals and between
differently named muscles, was significant. These findings suggest that a single
intramuscular electrode, recording from a limited sample of the motor units,
cannot be relied upon to characterize the activity of an entire muscle.
Furthermore, the use of both a repeated-measures model, to avoid
pseudoreplication, and a nested model, to account for variation, is critical for
a correct testing of biological hypotheses about differences in EMG signals.
free
free
free
