Quantitative representation of electromyographic patterns generated during human locomotion

Author

Shiavi, R.

Author_Institution

Dept. of Biomed. Eng., Vanderbilt Univ., Nashville, TN, USA

Volume

9

Issue

1

fYear

1990

fDate

3/1/1990 12:00:00 AM

Firstpage

58

Lastpage

60

Abstract

The problem addressed is the representation of electromyographic (EMG) profiles in an economical manner so that two tasks can be undertaken: (1) discovery of the different types of patterns in a population using pattern analysis techniques and (2) integration of the information in the EMG profiles with kinematic and dynamic information. The three signal processing techniques used to extract representative features of the EMG profiles are summarized. These techniques are based on the Tauberian approximation, Fourier series, and Karhunen-Loeve expansion and were chosen because they emphasize some characteristic of the gait EMG. All are designed to reduce the dimensionality of the linear envelope of the EMG so that interpretability can be enhanced and subsequent quantitative analyses can be performed.<>

Keywords

bioelectric potentials; biomechanics; muscle; pattern recognition; signal processing; Fourier series; Karhunen-Loeve expansion; Tauberian approximation; electromyographic patterns; gait EMG; human locomotion; pattern analysis techniques; quantitative representation; signal processing techniques; Character generation; Electromyography; Envelope detectors; Feature extraction; Humans; Kinematics; Muscles; Neuromuscular; Performance analysis; Performance evaluation;

fLanguage

English

Journal_Title

Engineering in Medicine and Biology Magazine, IEEE

Publisher

ieee

ISSN

0739-5175

Type

jour

DOI

10.1109/51.62908

Filename

62908