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Methodological variance associated with normalization of occupational upper trapezius EMG using submaximal reference contractions
Högskolan i Gävle, Centrum för belastningsskadeforskning. Department of Kinesiology, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada ; Liberty Mutual Research Institute for Safety, Hopkinton, USA.ORCID-id: 0000-0003-2939-0236
Högskolan i Gävle, Centrum för belastningsskadeforskning.ORCID-id: 0000-0003-1443-6211
Liberty Mutual Research Institute for Safety, Hopkinton, USA.
Ansvarig organisation
2009 (Engelska)Ingår i: Journal of Electromyography & Kinesiology, ISSN 1050-6411, E-ISSN 1873-5711, Vol. 19, nr 3, s. 416-427Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Objectives: To quantify the variance introduced to trapezius electromyography (EMG) through normalization by submaximal reference voluntary exertions (RVE), and to investigate the effect of increased normalization efforts as compared to other changes in data collection strategy on the precision of occupational EMG estimates. Methods: Women performed four RVE contractions followed by 30 minutes of light, cyclic assembly work on each of two days. Work cycle EMG was normalized to each of the RVE trials and seven exposure parameters calculated. The proportions of exposure variance attributable to subject, day within subject, and cycle and normalization trial within day were determined. Using this data, the effect on the precision of the exposure mean of altering the number of subjects, days, cycles and RVEs during data collection was simulated. Results: For all exposure parameters a unique component of variance due to normalization was present, yet small: less than 4.4% of the total variance. The resource allocation simulations indicated that marginal improvements in the precision of a group exposure mean would occur above three RVE repeats for EMG collected on one day, or beyond two RVEs for EMG collected on two or more days.

Ort, förlag, år, upplaga, sidor
2009. Vol. 19, nr 3, s. 416-427
Nyckelord [en]
Exposure Variability, Variance Components, Assembly work, Trapezius, EMG
Nationell ämneskategori
Arbetsmedicin och miljömedicin
Identifikatorer
URN: urn:nbn:se:hig:diva-1958DOI: 10.1016/j.jelekin.2007.11.004ISI: 000265508900007PubMedID: 18155593Scopus ID: 2-s2.0-62649167005OAI: oai:DiVA.org:hig-1958DiVA, id: diva2:118620
Tillgänglig från: 2008-06-11 Skapad: 2008-06-11 Senast uppdaterad: 2018-03-13Bibliografiskt granskad
Ingår i avhandling
1. Bias and Precision in Biomechanical Exposure Assessment: Making the Most of our Methods
Öppna denna publikation i ny flik eller fönster >>Bias and Precision in Biomechanical Exposure Assessment: Making the Most of our Methods
2017 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Background: Insufficient exposure assessment is a suggested contributing factor to the current lack of clearly characterised relationships between occupational biomechanical risk factors and musculoskeletal disorders. Minimal attention has been paid to the potential bias of measurement tools from expected true values (i.e. accuracy) or between measurement tools, and empirical data on the magnitudes of variance contributed by methodological factors for measurement tool precision are lacking.

Aim: The aim of this thesis was to quantify aspects of bias and precision in three commonly employed biomechanical risk factor assessment tools - inclinometry, observation, and electromyography (EMG) - and provide recommendations guiding their use. Methods: Upper arm elevation angles (UAEAs) were assessed using inclinometers (INC) and by computer-based posture-matching observation, and bias relative to true angles was calculated. Calibration models were developed for INC data, and their efficacy in correcting measurement bias was evaluated. The total variance of trapezius and erector spinae (ES) EMG recordings during cyclic occupational work was partitioned into biological and methodological sources, including the variance uniquely attributable to sub-maximal normalisation. Using algorithms to estimate the precision of a group mean, the efficacy of different trapezius EMG study designs was evaluated. Using precision criteria, the efficacy of different normalisation methods was assessed for ES EMG recordings.

Results and Discussion: Inclinometer measured UAEAs were biased from true angles, with increasing bias at higher angles. In contrast, computer based posture-matching observations were not biased from true angles. Calibration models proved effective at minimizing INC data bias. The dispersion of estimates between- and within- observers at any given set angle underlined the importance of repeated observations when estimating UAEAs. For EMG, a unique but relatively small component of the total variance was attributable to the methodological process of normalisation. Performing three repeats of the trapezius EMG normalisation task proved optimal at minimizing variance for one-day EMG studies, while two repeats sufficed for multi-day EMG studies. A prone normalisation task proved superior for maximizing normalised lumbar ES EMG precision.

Conclusion: Key aspects of measurement tool accuracy, bias between tools, and tool precision were quantified, and recommendations were made to guide future research study design.

Ort, förlag, år, upplaga, sidor
Uppsala: Acta Universitatis Upsaliensis, 2017. s. 90
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1329
Nyckelord
measurement strategy, accuracy, inclinometry, electromyography, EMG, upper arm, shoulder, low back, lumbar, thoracic
Nationell ämneskategori
Arbetsmedicin och miljömedicin
Identifikatorer
urn:nbn:se:hig:diva-23952 (URN)978-91-554-9902-0 (ISBN)
Disputation
2017-06-02, Krusenstjernasalen, Biblioteket, Kungsbäcksvägen 47, Gävle, 13:00 (Engelska)
Opponent
Handledare
Forskningsfinansiär
Forte, Forskningsrådet för hälsa, arbetsliv och välfärd, 2009-1761
Tillgänglig från: 2017-05-23 Skapad: 2017-05-02 Senast uppdaterad: 2018-03-13Bibliografiskt granskad

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Jackson, Jennie AMathiassen, Svend Erik

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