Title :
Influence of gender on the myoelectric signal of shank muscles
Author :
Di Nardo, F. ; Mengarelli, A. ; Maranesi, E. ; Burattini, L. ; Fioretti, S.
Author_Institution :
Dipt. di Ing. dell´Inf., Univ. Politec. delle Marche, Ancona, Italy
Abstract :
The surface electromyographic (sEMG) signal is commonly utilized as principal input information to the controller of robotic systems, such as exoskeleton robots. It has been shown that sEMG signals could vary from subject to subject, and that gender is one of the factors influencing this variation. Thus, the goal of this study is to detect possible gender-related differences in the EMG activity of the two main ankle-flexor muscles (tibialis anterior, TA and gastrocnemius lateralis, GL) during gait at comfortable speed and cadence. The statistical analysis of surface EMG signals, performed in seven male (M-group) and seven female (F-group) age-matched adults, showed clear gender-related differences in the behavior of TA and GL. The estimation of the different activation modalities, indeed, permitted to detect that F-group choose a walking modality with a more elevated number of activations during gait cycle, compared to M-group. This suggests a propensity of females for a more complex recruitment of the muscles during gait. The novel information on gender-related differences provided here suggest considering a separate approach for males and females, in providing electromyographic signals as input information to the controller of exoskeleton robot.
Keywords :
electromyography; gait analysis; medical robotics; medical signal processing; orthotics; statistical analysis; EMG activity; F-group; GL behavior; M-group; TA behavior; activation modalities; cadence; comfortable speed; complex recruitment; elevated activation number; exoskeleton robot controller; gait cycle; gastrocnemius lateralis; gender-related differences; main ankle-flexor muscles; myoelectric signal; principal input information; robotic system controller; shank muscles; statistical analysis; surface EMG signals; surface electromyographic signal; tibialis anterior; walking modality; Electromyography; Exoskeletons; Finite impulse response filters; Legged locomotion; Muscles; Statistical analysis; exoskeleton robot; gender; statistical gait analysis; surface EMG control;
Conference_Titel :
Mechatronic and Embedded Systems and Applications (MESA), 2014 IEEE/ASME 10th International Conference on
Conference_Location :
Senigallia
Print_ISBN :
978-1-4799-2772-2
DOI :
10.1109/MESA.2014.6935537