The interpretation of abdominal wall muscle recruitment strategies change when the electrocardiogram (ECG) is removed from the electromyogram (EMG)

Butler, Heather; Newell, Robyn; Hubley‐Kozey, Cheryl L.; Kozey, John W.

doi:10.1016/j.jelekin.2007.10.004

Cited by 54 publications

(38 citation statements)

References 32 publications

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“…version 7.3) were used to process the EMG and motion data separately. To remove ECG artefact the raw EMG signal was Wrst Wltered using a recursive Wfth-order Butterworth high pass Wlter at a cut-oV frequency of 30 Hz (Butler et al 2007b;Drake and Callaghan 2006;Zhou et al 2007). For each muscle site, the root mean square (RMS) amplitude was calculated during the lift phase.…”

Section: Data Processingmentioning

confidence: 99%

Activation amplitude patterns do not change for back muscles but are altered for abdominal muscles between dominant and non-dominant hands during one-handed lifts

2009

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It is assumed when lifting with the dominant hand that the relationship between contralateral and ipsilateral trunk muscle responses are similar to when lifting with the non-dominant hand. The purpose of this study was to quantify trunk muscle activation amplitude patterns during right- and left-handed lifts. Surface electromyography (EMG) and kinematic variables were recorded from 29 healthy subjects. Minimal trunk and pelvis motion was observed. Three principal patterns accounted for 95% of the variation in the EMG data indicating minimal variation in the pattern. Significant differences in scores captured different recruitment strategies for reach and hand. Selective and differential recruitment of back sites characterized lifts at greater distances from the body, whereas co-activation between internal oblique and back sites characterized lifts closer to the body. While the results showed no handedness effect for back muscles, the external oblique responded differently between right- and left-handed lifts. Specific recruitment strategies were used to account for subtle changes in reach and asymmetrical demands.

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Section: Data Processingmentioning

confidence: 99%

Activation amplitude patterns do not change for back muscles but are altered for abdominal muscles between dominant and non-dominant hands during one-handed lifts

2009

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“…The 30 Hz cutoff was expected to remove any possible electrocardiographic contaminations and artifacts [14]. Next, we full-wave rectified the EMG patterns before filtering them with a 6 Hz low-pass filter to finally generate linear envelopes.…”

Section: Outcome Measuresmentioning

confidence: 99%

Does upper-limb muscular demand differ between preferred and nonpreferred sitting pivot transfer directions in individuals with a spinal cord injury?

Gagnon¹,

Koontz²,

Brindle³

et al. 2009

JRRD

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Abstract-This study's main objective was to determine if upper-limb (UL) muscular demand was reduced when individuals with a spinal cord injury (SCI) performed a sitting pivot transfer (SPT) in the preferred direction compared with that in a nonpreferred direction. Fourteen individuals (mean +/-standard deviation age 47.0 +/-8.3 yr, height 1.80 +/-0.08 m, and weight 75.3 +/-11.3 kg) with SCI levels ranging from the sixth cervical to first sacral vertebra levels volunteered to participate in this study during the 2008 National Disabled Veterans Winter Sports Clinic. Surface electromyography (EMG) was used to record activity of the biceps, triceps, deltoid, pectoralis major, trapezius, and latissimus dorsi bilaterally during SPTs. These transfers were performed in each of the preferred and nonpreferred directions from the individuals' wheelchairs to a padded tub bench of even height. To quantify electromyographic muscular utilization ratio (MUR EMG ), we normalized EMG data recorded during the transfer tasks to values obtained during static maximum voluntary contraction and then multiplied this ratio by 100 to obtain a percentage MUR EMG (%MUR EMG ). The overall peak %MUR EMG and the area under the %MUR EMG curve were selected as primary outcome measures. Similar peak %MUR EMGs were found between the preferred and nonpreferred transfer directions for all muscles from which data were recorded (p = 0.053 to 0.961). The peak %MUR EMGs were also found to be similar between the leading and trailing ULs during the transfers in all muscles from which data were recorded (p = 0.125 to 0.838), except for the anterior deltoid, which was found to be solicited the most in the trailing UL (p = 0.008). Comparable areas under the %MUR EMG curves were calculated between the preferred and nonpreferred transfer directions for all muscles (p = 0.289 to 0.678) and between the leading and trailing ULs (p = 0.104 to 0.946). These results indicate that direction preference expressed by individuals with SCI when transferring between seats of even height is not explained by relative muscular demand differences.Key words: activities of daily living, elbow, electromyography, paraplegia, rehabilitation, shoulder, spinal cord injury, task analysis, task performance, tetraplegia, upper limb.Abbreviations: ANOVA = analysis of variance; C = cervical; EMG = electromyography, electromyographic; EMG max = maximum EMG value, EMG transfer = EMG data collected during transfers; HERL = Human Engineering Research Laboratories; MUR EMG = EMG muscular utilization ratio; %MUR EMG = percentage MUR EMG ; MVC = maximal voluntary contraction; SCI = spinal cord injury; SD = standard deviation; sEMG = surface EMG; SPT = sitting pivot transfer; UL = upper limb; VA = Department of Veterans Affairs; WUSPI = Wheelchair User's Shoulder Pain Index.

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“…The frequency content of trunk muscle EMG signals may provide information on fatigue development in these muscles. Unfortunately, trunk muscle EMG recordings are often contaminated by the electrocardiogram (ECG), which can hamper analysis (Butler et al, 2009) and may result in misinterpretations.…”

Section: Introductionmentioning

confidence: 99%

Removing ECG contamination from EMG recordings: A comparison of ICA-based and other filtering procedures

Willigenburg

Daffertshofer

Kingma

et al. 2012

Journal of Electromyography and Kinesiology

113

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Trunk muscle electromyography (EMG) is often contaminated by the electrocardiogram (ECG), which hampers data analysis and potentially yields misinterpretations. We propose the use of independent component analysis (ICA) for removing ECG contamination and compared it with other procedures previously developed to decontaminate EMG. To mimic realistic contamination while having uncontaminated reference signals, we employed EMG recordings from peripheral muscles with different activation patterns and superimposed distinct ECG signals that were recorded during rest at conventional locations for trunk muscle EMG. ICA decomposition was performed with and without a separately collected ECG signal as part of the data set and contaminated ICA modes representing ECG were identified automatically. Root mean squared relative errors and correlations between the linear envelopes of uncontaminated and contaminated EMG were calculated to assess filtering effects on EMG amplitude. Changes in spectral content were quantified via mean power frequencies. ICA-based filtering largely preserved the EMG's spectral content. Performance on amplitude measures was especially successful when a separate ECG recording was included. That is, the ICA-based filtering can produce excellent results when EMG and ECG are indeed statistically independent and when mode selection is flexibly adjusted to the data set under study.

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The interpretation of abdominal wall muscle recruitment strategies change when the electrocardiogram (ECG) is removed from the electromyogram (EMG)

Cited by 54 publications

References 32 publications

Activation amplitude patterns do not change for back muscles but are altered for abdominal muscles between dominant and non-dominant hands during one-handed lifts

Activation amplitude patterns do not change for back muscles but are altered for abdominal muscles between dominant and non-dominant hands during one-handed lifts

Does upper-limb muscular demand differ between preferred and nonpreferred sitting pivot transfer directions in individuals with a spinal cord injury?

Removing ECG contamination from EMG recordings: A comparison of ICA-based and other filtering procedures

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