Finger force capability: measurement and prediction using anthropometric and myoelectric measures
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Forces were measured using strain gauge transducers, and a modification of standard protocols was followed to obtain consistent and applicable data. Correlations within and among maximum finger forces, whole-hand grip force, and anthropometric measures were examined. Multiple regression models were developed to determine the feasibility of predicting of finger strength in various finger couplings from more accessible measures. After examining a wide variety of such mathematical models, the results suggest that finger strength can be predicted from easily obtained measures with only moderate accuracy (R2-adj: 0.45 - 0.64; standard error: 11.95N - 18.88N). Such models, however, begin to overcome the limitations of direct finger strength measurements of individuals.
Surface electrodes were used to record electromyographic signals collected from three standardized electrode sites on the forearm. Multiple linear regression models were generated to predict finger force levels with the three normalized electromographic measures as predictor variables. The results suggest that standardized procedures for obtaining EMG data and simple linear models can be used to accurately predict finger forces (R2-adj: 0.77 - 0.88; standard error: 9.21N - 12.42N) during controlled maximal exertions. However, further work is needed to determine if the models can be generalized to more complex tasks.
- Masters Theses