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

Willigenburg, Nienke W.; Daffertshofer, Andreas; Kingma, Idsart; Dieën, Jaap H. van

doi:10.1016/j.jelekin.2012.01.001

Cited by 113 publications

(82 citation statements)

References 13 publications

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“…A better approach would be reduction of the artifact by computational or blanking techniques. 16,17 In summary, recording of CW-EMG using methods similar to those routinely used to record chin and anterior tibial EMG was clinically useful for classification of apnea in our patients. There was a high degree of agreement with RIP effort belt signals.…”

Section: Discussionmentioning

confidence: 77%

Use of Chest Wall Electromyography to Detect Respiratory Effort during Polysomnography

Berry

Ryals

Girdhar

et al. 2016

Journal of Clinical Sleep Medicine

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Study Objectives: To evaluate the ability of chest wall EMG (CW-EMG) using surface electrodes to classify apneas as obstructive, mixed, or central compared to classification using dual channel uncalibrated respiratory inductance plethysmography (RIP). Methods: CW-EMG was recorded from electrodes in the eighth intercostal space at the right mid-axillary line. Consecutive adult clinical sleep studies were retrospectively reviewed, and the first 60 studies with at least 10 obstructive and 10 mixed or central apneas and technically adequate tracings were selected. Four obstructive and six central or mixed apneas (as classified by previous clinical scoring) were randomly selected. A blinded experienced scorer classified the apneas on the basis of tracings showing either RIP channels or the CW-EMG channel. The agreement using the two classification methods was determined by kappa analysis and intraclass correlation. Results: The percentage agreement was 89.5%, the kappa statistic was 0.83 (95% confidence interval 0.79 to 0.87), and the intraclass correlation was 0.83, showing good agreement. Of the 249 apneas classified as central by RIP, 26 were classified as obstructive (10.4%) and 7 as mixed (2.8%) by CW-EMG. Of the 229 events classified as central by CW-EMG, 7 (3.1%) were classified as obstructive and 6 (2.6%) as mixed by RIP. Conclusions: Monitoring CW-EMG may provide a clinically useful method of detection of respiratory effort when used with RIP and can prevent false classification of apneas as central. RIP can rarely detect respiratory effort not easily discernible by CW-EMG and the combination of the two methods is more likely to avoid apnea misclassification. Keywords: apnea, diaphragmatic EMG, polysomnography, respiratory effort Citation: Berry RB, Ryals S, Girdhar A, Wagner MH. Use of chest wall electromyography to detect respiratory effort during polysomnography.

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Section: Discussionmentioning

confidence: 77%

Use of Chest Wall Electromyography to Detect Respiratory Effort during Polysomnography

Berry

Ryals

Girdhar

et al. 2016

Journal of Clinical Sleep Medicine

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“…EMG was filtered offline with a band-pass filter (1-400 Hz) before independent component analysis was used for electrocardiography removal [64]. For each participant, one or two independent components were removed.…”

Section: Functional Muscle Networkmentioning

confidence: 99%

Network structure of the human musculoskeletal system shapes neural interactions on multiple timescales

Kerkman

Daffertshofer

Gollo

et al. 2017

Preprint

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Human motor control requires the coordination of muscle activity under the anatomical constraints imposed by the musculoskeletal system. Interactions within the central nervous system are fundamental to motor coordination, but the principles governing functional integration remain poorly understood. We used network analysis to investigate the relationship between anatomical and functional connectivity amongst 36 muscles. Anatomical networks were defined by the physical connections between muscles and functional networks were based on intermuscular coherence assessed during postural tasks. We found a modular structure of functional networks that was strongly shaped by the anatomical constraints of the musculoskeletal system. Muscle networks exhibited a multilayer architecture with functional interactions at distinct timescales. Changes in postural tasks were associated with a frequency-dependent reconfiguration of the coupling between functional modules. Combined, these findings suggest these spectral modes may signify a coordinative structure for flexibly organising muscle activity during postural control. More broadly, our multi-level network approach to the motor system offers a unique window into the coordinated neural circuitry that generates synergistic input to muscles in different behaviours.not peer-reviewed)

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“…EMG signals were amplified with a 16-channel amplifier (Porti, TMS International B.V., Enschede, the Netherlands) and sampled at 2,000 Hz. All signals were filtered offline with a bidirectional, second-order, bandpass (30-400 Hz) Butterworth filter to remove heart rate (HR) artefacts (Drake & Callaghan, 2006;Marker & Maluf, 2014;Willigenburg, Daffertshofer, Kingma, & Van Die€ en, 2012). We root mean square (RMS) converted the filtered signal using a 100-millisecond moving window with 99.5-millisecond overlap.…”

Section: Muscle Activitymentioning

confidence: 99%

Influence of Posture Variation on Shoulder Muscle Activity, Heart Rate, and Perceived Exertion in a Repetitive Manual Task

Luger

Mathiassen

Bösch

et al. 2017

IISE Transactions on Occupational Ergonomics and Human Factors

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OCCUPATIONAL APPLICATIONS In repetitive work, more physical variation is believed to reduce the risk of eventually developing musculoskeletal disorders. We investigated the extent to which workstation designs leading to more variation in upper arm postures during a pick-and-place task influenced outcomes of relevance to musculoskeletal disorder risk, including muscle activity, cardiovascular response, and perceived exertion, measured through the maximal acceptable work pace. Posture variation to the extent obtained in our experiment had only minor effects on these outcomes, and considerably less impact than a moderate change in working height. Apparently, substantial manipulations of the workstation or of the work task will be needed to accomplish variation to an extent that can significantly change outcomes of relevance to occupational musculoskeletal disorders and, thus, represent a potential for reduction in musculoskeletal disorder risk.TECHNICAL ABSTRACT Background: Repetitive light assembly work is associated with an increased risk for developing work-related musculoskeletal disorders. More exposure variation, for instance by redesigning the workstation, has been proposed as an effective intervention. Purpose: We investigated the effect of upper arm posture variation in a 1-hour repetitive pick-and-place task on shoulder muscle activity, heart rate, and perceived exertion, measured on the Borg CR-10 scale and in terms of maximal acceptable work pace (MAWP). This is an Open Access article distributed under the terms of the Creative Commons AttributionNonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. ), while trapezius activity (78% RVE) and perceived exertion (Borg CR-10) tended to be higher. Conclusions: Our results indicate that posture variation to the extent achieved in the current experiment leads to less effects on muscle activity and perceived exertion than a moderate change in working height. 2472-5838

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

Cited by 113 publications

References 13 publications

Use of Chest Wall Electromyography to Detect Respiratory Effort during Polysomnography

Use of Chest Wall Electromyography to Detect Respiratory Effort during Polysomnography

Network structure of the human musculoskeletal system shapes neural interactions on multiple timescales

Influence of Posture Variation on Shoulder Muscle Activity, Heart Rate, and Perceived Exertion in a Repetitive Manual Task

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