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SETSCI - Volume (2018) ISAS 2018 - Ist International Symposium on Innovative Approaches in Scientific Studies, Kemer-Antalya, Turkey, Apr 11, 2018 Functional Development in Facial Transplants Using Surface EMG Analysis: Literature Review (ISAS 2018_173)
Serkan Şenkal 1, Hakan Çoban 2, Mustafa Demir 3, Arzu Sarıgül 4 * 1Turhal Meslek Yüksekokulu, Gaziosmanpaşa Üniversitesi , Tokat, Turkey 2Turhal Vocational School, Gaziosmanpaşa University , Tokat, Turkey 3Turhal Meslek Yüksekokulu, Gaziosmanpaşa Üniversitesi , Tokat, Turkey 4Turhal Meslek Yüksekokulu, Gaziosmanpaşa Üniversitesi , Tokat, Turkey * Corresponding author: firstname.lastname@example.org Published Date: 2018-06-23 | Page (s): 196-197 | 110 5
In recent years, significant improvements have been made in face transplants as well as organ transplants operations. It is also important to improve the adaptation process and quality of life of the patient after the transplant as well as the successful completion of the transplantation operations. Facial transplant patients need to undergo a specific rehabilitation process in order to perform facial movements like healthy individuals. As a result of this rehabilitation process, the functional development of the patient can be analyzed by recorded electromyogram (EMG) signals through surface electrodes. Cognitive rehabilitation methods and functional electrical stimulation have been used in the literature to improve emotional expressions and improve the ability to perform certain primer movements in full-face transplant patients. With functional electrical stimulation, muscle contractions occur naturally. This means that muscle activation can prevent muscle cramps. In cognitive rehabilitation, the patient and the healthy individual are together. They are asked to do similar movements under the same conditions. It is ensured that the patient follows the healthy individual and follows the movements so that he can perform these movements with the help of stimuli. The functional development of patients, recorded EMG before and after rehabilitation was analyzed by comparing the data obtained from healthy subjects. Time, frequency and time-frequency domain analysis methods are used in the analysis of EMG signals. Methods such as root mean square (RMS), total absolute value (IAV), mean absolute value (MAV) are examples of time domain analysis methods. Mean frequency (MF), median frequency (MDF), wavelength and zero crossing (ZC) methods are frequency domain analysis methods. Also frequency domain analysis methods are used such as Short Time Fourier transform (STFT), wavelet transform (WT) and time transformations such as continuous wavelet transform (CWT) and discrete-time wavelet transform (DWT), and Wigner-Ville distribution (WVD). In addition to these methods, the nonlinear analysis methods such Higuchi fractal dimension method for analyzing the complexity of biomedical signals is used in EMG signal analysis. At the end of the analysis of end-of-life rehabilitation processes, improvements in facial symmetry of patients and increased ability to perform basic facial expressions and primer facial movements have been observed. As the time to start pre-rehabilitation was later, the time to start post-rehabilitation was taken to the fore, which was similar to healthy individuals. Furthermore, expressions and movements after rehabilitation became stronger than before. it is seen that similarity increases in the ability to perform facial expressions when compared to patients and healthy individuals using the fuzzy entropy method.
Face Transplantation, Surface EMG, Functional Electrical Stimulation, Cognitive Rehabilitation