@article {Mogk:2006:0014-0139:1121,
title = "Prediction of forearm muscle activity during gripping",
journal = "Ergonomics",
parent_itemid = "infobike://tandf/terg",
publishercode ="tandf",
year = "2006",
volume = "49",
number = "11",
publication date ="2006-09-15T00:00:00",
pages = "1121-1130",
itemtype = "ARTICLE",
issn = "0014-0139",
eissn = "1366-5847",
url = "https://www.ingentaconnect.com/content/tandf/terg/2006/00000049/00000011/art00007",
doi = "doi:10.1080/00140130600777433",
keyword = "Ergonomic tool, Grip force, Regression, Prediction, Posture, EMG",
author = "Mogk, Jeremy and Keir, Peter",
abstract = "Occupational exposure is typically assessed by measuring forces and body postures to infer muscular loading. Better understanding of workplace muscle activity levels would aid in indicating which muscles may be at risk for overexertion and injury. However, electromyography collection in the workplace is often not practical. Therefore, a set of equations was developed and validated using data from two separate days to predict forearm muscle activity (involving six wrist and finger muscles) from grip force and posture of the wrist (flexed, neutral and extended) and forearm (pronated, neutral, supinated). The error in predicting activation levels of each forearm muscle across the range of grip forces, using the first day data (root mean square error; RMSE model ), ranged from 8.9% maximal voluntary electrical activation (MVE) (flexor carpi radialis) to 11% MVE (extensor digitorum communis). Grip force was the main contributor to predicting muscle activity levels, explaining over 70% of the variance in flexor activation levels and up to 60% in extensor activation levels, respectively. Inclusion of gender as a variable in the model improved estimates of flexor but not extensor activity. While posture itself explained minimal variance in activation without grip force (",
}