TY - GEN
T1 - An EMG signal processing system for control of an ankle-foot orthosis
AU - Gmerek, Artur J.
AU - Davoodi, Mohammadreza
AU - Meskin, Nader
AU - Jaber, Fadi
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/8
Y1 - 2017/11/8
N2 - This paper presents an electromyographic (EMG)based digital processing system for estimating foot direction of motion and force exerted from muscles of the human lower leg. This information can be used in the control frameworks of ankle-foot orthoses (AFOs). In essence, it is usually necessary to estimate the ankle's muscles voluntary contraction (VC) and user's intention of motion in order to control an AFO in a reliable and effective way. Consequently, a data processing system is developed that can designate these parameters from EMG signals. The voluntary contraction is calculated based on the root mean square (RMS) of EMG signals, and the direction of motion is estimated by using a feature-based classifier. The experiments are performed on five healthy, sitting subjects and the methodology consists of selecting discriminative features and using basic classifiers. The results of this work show that the direction of motion can be estimated in real-time with high accuracy.
AB - This paper presents an electromyographic (EMG)based digital processing system for estimating foot direction of motion and force exerted from muscles of the human lower leg. This information can be used in the control frameworks of ankle-foot orthoses (AFOs). In essence, it is usually necessary to estimate the ankle's muscles voluntary contraction (VC) and user's intention of motion in order to control an AFO in a reliable and effective way. Consequently, a data processing system is developed that can designate these parameters from EMG signals. The voluntary contraction is calculated based on the root mean square (RMS) of EMG signals, and the direction of motion is estimated by using a feature-based classifier. The experiments are performed on five healthy, sitting subjects and the methodology consists of selecting discriminative features and using basic classifiers. The results of this work show that the direction of motion can be estimated in real-time with high accuracy.
UR - https://www.scopus.com/pages/publications/85045575147
U2 - 10.1109/CoDIT.2017.8102632
DO - 10.1109/CoDIT.2017.8102632
M3 - Conference contribution
AN - SCOPUS:85045575147
T3 - 2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017
SP - 444
EP - 449
BT - 2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017
Y2 - 5 April 2017 through 7 April 2017
ER -