Automated Job Analysis Using Biomechanical Data and Template Matching

Abstract

Spectral analysis of upper limb kinematic measurements has been previously demonstrated useful for quantifying physical stress properties of repetitive motion. The method requires manually separating the data into segments corresponding to individual tasks or work elements and computing power spectra. This study investigated using signal pattern recognition to help automate the analysis by separating the data through identification of stereotypical patterns in cyclical tasks. Joint angular data was collected for five industrial jobs using electrogoniometers attached to the wrist, elbow and shoulder of the dominant limb. A multimedia computer system along with the analyst interactively indicate element break points. The break points were also automatically identified using a template matching (TM) algorithm. The algorithm identified the cycle break points on average to within 0.997 s (S.D.=2.762 s) of the human analyst's reference break point. Nevertheless, automated break point identification should be useful for indicating approximate break point and then interactively fine-tuning the computer as a means for reducing the time required to perform an analysis.

Get full access to this article

View all access options for this article.

References

Dobbs

S. E.

Schmitt

N. M.

Ozemek

H. S.

, (1984), QRS detecion by template matching using real-time correlation on a microcomputer, Journal of Clinical Engineering, 9, 197–212.

Radwin

R. G.

Lin

M. L.

(1993), An analytical method for characterizing repetitive motion and postural stress using spectral analysis, Ergonomics, 36(4), 379–389.

Radwin

R. G.

Lin

M. L.

Yen

T. Y.

, 1994, Exposure assessment of biomechanical stress in repetitive manual work using frequency-weighted filters, Ergonomics, 37 (12), 1984–1998.

Radwin

R. G.

Yen

T. Y.

(1993), Development of an Instrument for Assessing Exposure to Physical Stress in Repetitive Manual Work, Proceeding of the 1993 NSF Design and Manufacturing Systems Conference, SME.

Silka

M.J.

Ranville

Jenkins

J.M.

Yan

M.C.

DiCarlo

L.A.

, (1992) Template Matching Analysis of Unipolar and Bipolar Electrograms in Differentiation of Ventricular Tachycardia and Fibrillation from Sinus Rhythm, Computers in Cardiography, Los Alamitos, IEEE Computers Society Press. 223–225.

Yen

T. Y.

, Unpublished Doctoral Dissertation, University of Wisconsin-Madison, 1997.

Yen

T. Y.

Radwin

R. G.

, 1995, A video-based system for acquiring biomechanical data synchronized with arbitrary events and activities, IEEE transactions on Biomedical Engineering, 42(9), 944–948.