Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). We apologize for the inconvenience.
By Topic

Genetic algorithm based optimization of Kullback Information Criterion: Improved system identification of skeletal muscle force and sEMG signals

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Anugolu, M. ; Meas. & Control Eng., Res. Center (MCERC), Idaho State Univ., Pocatello, ID, USA ; Potluri, C. ; Urfer, A. ; Creelman, J.
more authors

This paper focuses on determining the sensitivity of the number of data points used in computing the Kullback Information Criterion (KIC) for the use in sensor data fusion. The primary objective of the sensor fusion is to improve the extraction of dynamic models relating Surface Electromyogrphic (sEMG) signals with the corresponding skeletal muscle force signals. The proposed approach utilizes a pre-processing of the sEMG data with a Half-Gaussian filter. System Identification techniques are employed to extract a relationship between the sEMG and the skeletal muscle force. In this paper linear and non-linear models are inferred from the fused data to describe the sEMG/force relationship. In order to optimize the number of data points for finding the optimum KIC, a Genetic Algorithm (GA) is used.

Published in:

Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International

Date of Conference:

13-16 May 2012