A psychophysical study to determine maximum acceptable efforts for a thumb abduction task with high duty cycles

Potvin (2012, 'Predicting Maximum Acceptable Efforts for Repetitive Tasks: An Equation Based on Duty Cycle', Human Factors: The Journal of the Human Factors and Ergonomics Society, 54 (2), 175-188) developed an equation using psychophysical data to estimate maximum acceptable efforts (MAEs...

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Veröffentlicht in:Ergonomics 2015-01, Vol.58 (1), p.118-127
Hauptverfasser: Sonne, Michael W., Potvin, Jim R.
Format: Artikel
Sprache:eng
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Zusammenfassung:Potvin (2012, 'Predicting Maximum Acceptable Efforts for Repetitive Tasks: An Equation Based on Duty Cycle', Human Factors: The Journal of the Human Factors and Ergonomics Society, 54 (2), 175-188) developed an equation using psychophysical data to estimate maximum acceptable efforts (MAEs) as a function of duty cycle (DC). However, only ∼6% of the data featured DCs ≥ 0.50. The purpose of this study was to evaluate the MAE equation in the high DC range. We tested a repetitive thumb adduction task with DCs of 0.50, 0.70 and 0.90, at frequencies of both 2 and 6 per minute (n = 6 conditions). Participants were trained for 2 hours and tested for 1 hour on each condition. The MAE decreased with increasing DC, and MAEs at 2/min were higher than those at 6/min. When these current six means were added to the original psychophysical studies, the root-mean squared difference of the MAE equation decreased from 7.23% to 7.05% maximum voluntary contraction. The values from our study are also consistent with those demonstrating physiological evidence of fatigue during both continuous isotonic and high DC tasks. Practitioner Summary: The maximum acceptable effort (MAE) equation can be used by ergonomists to estimate acceptable forces and torques where both duty cycle (DC) is known and maximum strength data are available. Our psychophysical study provides evidence to validate the MAE equation for high DC tasks (DC ≥ 0.50). In fact, the relationship between the equation and existing data is improved with the inclusion of our data.
ISSN:0014-0139
1366-5847
DOI:10.1080/00140139.2014.957734