Authors : Sang-Sik Lee, Jin-Hyoung Jeong, Jae-Hyun Jo and Ki-Young Lee
Abstract: In this study, the bio-feedback to prevent the overuse of the low frequency stimulation was studied in the method of using the parameters of the EMG. First of all, before you start the low-frequency stimulation at the position of the face of the electrode to measure the EMG signal during muscle contraction. Observe the measured EMG signals and records the extracted parameter values. After stimulation of the face of the subject in low-frequency stimulation that lasts a certain period of time (up-30 sec) by observing the EMG signal to extract the parameter values. In the present study, the EMG before adding the low frequency stimulation to the mask face, measured normal contraction, EMGs when facial muscles are paralyzed can’t be actually measured and only thought tends to shrink the appropriate facial muscles based on the virtual paralysis muscles protocol presented in this study, actually without shrinkage was measured EMG. Result of comparison of parameters used for the feedback to the subject 17 men and women subjects is as follows. Parameter RMS EMG measured under the assumption of a virtual paralysis muscles, decreased than normal systolic RMS average to <50% there was a statistically significant difference. Virtual paralysis muscle EMG parameters were measured under the assumption of ZCR has been increased by more than the normal shrinkage ZCR a portion was reduced. Also, there was a statistically significant difference. Paralyzed muscles because it does not actually contracted, the protocol of the virtual paralysis muscle is effective for selection of parameters for bio feed back to prevent excessive least low frequency stimulation, practical things considered.
Sang-Sik Lee, Jin-Hyoung Jeong, Jae-Hyun Jo and Ki-Young Lee, 2018. Study of Bio-Feedback Signal Analysis Algorithm Associated with the Development of the Low-Frequency Face Muscle Motion System. Journal of Engineering and Applied Sciences, 13: 3048-3053.