Assessment of mental fatigue and stress on electronic sport players with data fusion.

Stress and mental fatigue are in existence constantly in daily life, and decrease our productivity while performing our daily routines. The purpose of this study was to analyze the states of stress and mental fatigue using data fusion while e-sport activity. In the study, ten volunteers performed e-sport duty which required both physical and mental effort and skills for 2 min. Volunteers' electroencephalogram (EEG), galvanic skin response (GSR), heart rate variability (HRV), and eye tracking data were obtained before and during game and then were analyzed. In addition, the effects of e-sports were evaluated with visual analogue scale and d2 attention tests. The d2 tests are performed after the game, and the game has a positive effect on attention and concentration. EEG from the frontal region indicates that the game is partly caused by stress and mental fatigue. HRV analysis showed that the sympathetic and vagal activities created by e-sports on people are different. By evaluating HRV and GSR together, it was seen that the emotional processes of the participants were stressed in some and excited in others. Data fusion can serve a variety of purposes such as determining the effect of e-sports activity on the person and the appropriate game type.

Adaptive analysis of cortical plasticity with fMRI in full face and arm transplants.

The aim of this study is to examine cortical plasticity and to analyze cortical reorganization following hand and facial transplantation, using functional magnetic resonance imaging. Patients who had undergone full-face transplantation, hand transplantation and scapular arm replantation, as well as healthy controls, participated in the study. The perioral area and volar surfaces of the index finger and thumb were stimulated and images were acquired using 3 T functional MRI. The areas of the somatosensory cortex representing the hand and face are different in size and shape due to experience-dependent plasticity. Therefore, a new and more adaptive volume of interest analysis was created whereby the radiuses of the VOI masks were defined by the peak intensity of subsequent clusters. For each control subject, the distribution of activated voxels was observed for various cluster defining thresholds in order to determine the mean number of activated voxels for each stimulation inside the defined region. The determined numbers of voxels per subject were extracted from the defined regions using a binary search algorithm. Subsequently, the distances between the weighted centers of the extracted regions were calculated and compared. In transplant patients, the weighted centers of the hand and face clusters were separated at same-sized volumes. Two of the rehabilitated full-face transplant patients converge to the range of the controls. As a result, the weighted distribution of somatotopy indicated previous and present cortical reorganization. Additionally, referred sensation was assessed in two full-face transplant and one replant patient with activation clusters partially in BA40 in the Inferior Parietal Lobule.

Mathematical model of patella T-reflex and clinical evaluation with Ashworth scales.

Spasticity is one of the major problems that arise in different neurological diseases and seriously affect the quality of human life. Research on the understanding of mechanism of spasticity remains as important as the studies on the spasticity therapy and rehabilitation. In this study, the spasticity mechanism which develops concerning the upper motor neuron lesions is investigated by modelling "Patella tendon reflex triggered patella pendulum". The mathematical model based on the pendulum phenomenon is developed by solving the curve-fitting problem as finding the curve that best fits a set of data points. Electrophysiological and dynamic measurement data were taken from 76 spastic subjects and 20 healthy participants. The mathematical model is determined by the morphological properties of the goniometric variations. The results denote that the mathematical model containing two clinically relevant parameters -frequency component of the damped oscillatory motion defined as "f 0 " with the maximum angle of the reflex defined as "a 0 " ensures to distinguish spasticity from healthy subjects.

Recovery of facial expressions using functional electrical stimulation after full-face transplantation.

BACKGROUND: We assessed the recovery of 2 face transplantation patients with measures of complexity during neuromuscular rehabilitation. Cognitive rehabilitation methods and functional electrical stimulation were used to improve facial emotional expressions of full-face transplantation patients for 5 months. Rehabilitation and analyses were conducted at approximately 3 years after full facial transplantation in the patient group. We report complexity analysis of surface electromyography signals of these two patients in comparison to the results of 10 healthy individuals. METHODS: Facial surface electromyography data were collected during 6 basic emotional expressions and 4 primary facial movements from 2 full-face transplantation patients and 10 healthy individuals to determine a strategy of functional electrical stimulation and understand the mechanisms of rehabilitation. A new personalized rehabilitation technique was developed using the wavelet packet method. Rehabilitation sessions were applied twice a month for 5 months. Subsequently, motor and functional progress was assessed by comparing the fuzzy entropy of surface electromyography data against the results obtained from patients before rehabilitation and the mean results obtained from 10 healthy subjects. RESULTS: At the end of personalized rehabilitation, the patient group showed improvements in their facial symmetry and their ability to perform basic facial expressions and primary facial movements. Similarity in the pattern of fuzzy entropy for facial expressions between the patient group and healthy individuals increased. Synkinesis was detected during primary facial movements in the patient group, and one patient showed synkinesis during the happiness expression. Synkinesis in the lower face region of one of the patients was eliminated for the lid tightening movement. CONCLUSIONS: The recovery of emotional expressions after personalized rehabilitation was satisfactory to the patients. The assessment with complexity analysis of sEMG data can be used for developing new neurorehabilitation techniques and detecting synkinesis after full-face transplantation.

Image-based Analysis of Emotional Facial Expressions in Full Face Transplants.

In this study, it is aimed to determine the degree of the development in emotional expression of full face transplant patients from photographs. Hence, a rehabilitation process can be planned according to the determination of degrees as a later work. As envisaged, in full face transplant cases, the determination of expressions can be confused or cannot be achieved as the healthy control group. In order to perform image-based analysis, a control group consist of 9 healthy males and 2 full-face transplant patients participated in the study. Appearance-based Gabor Wavelet Transform (GWT) and Local Binary Pattern (LBP) methods are adopted for recognizing neutral and 6 emotional expressions which consist of angry, scared, happy, hate, confused and sad. Feature extraction was carried out by using both methods and combination of these methods serially. In the performed expressions, the extracted features of the most distinct zones in the facial area where the eye and mouth region, have been used to classify the emotions. Also, the combination of these region features has been used to improve classifier performance. Control subjects and transplant patients' ability to perform emotional expressions have been determined with K-nearest neighbor (KNN) classifier with region-specific and method-specific decision stages. The results have been compared with healthy group. It has been observed that transplant patients don't reflect some emotional expressions. Also, there were confusions among expressions.

Assessment of Emotional Expressions after Full-Face Transplantation.

We assessed clinical features as well as sensory and motor recoveries in 3 full-face transplantation patients. A frequency analysis was performed on facial surface electromyography data collected during 6 basic emotional expressions and 4 primary facial movements. Motor progress was assessed using the wavelet packet method by comparison against the mean results obtained from 10 healthy subjects. Analyses were conducted on 1 patient at approximately 1 year after face transplantation and at 2 years after transplantation in the remaining 2 patients. Motor recovery was observed following sensory recovery in all 3 patients; however, the 3 cases had different backgrounds and exhibited different degrees and rates of sensory and motor improvements after transplant. Wavelet packet energy was detected in all patients during emotional expressions and primary movements; however, there were fewer active channels during expressions in transplant patients compared to healthy individuals, and patterns of wavelet packet energy were different for each patient. Finally, high-frequency components were typically detected in patients during emotional expressions, but fewer channels demonstrated these high-frequency components in patients compared to healthy individuals. Our data suggest that the posttransplantation recovery of emotional facial expression requires neural plasticity.

Determination of Fatigue Following Maximal Loaded Treadmill Exercise by Using Wavelet Packet Transform Analysis and MLPNN from MMG-EMG Data Combinations.

The muscle fatigue can be expressed as decrease in maximal voluntary force generating capacity of the neuromuscular system as a result of peripheral changes at the level of the muscle, and also failure of the central nervous system to drive the motoneurons adequately. In this study, a muscle fatigue detection method based on frequency spectrum of electromyogram (EMG) and mechanomyogram (MMG) has been presented. The EMG and MMG data were obtained from 31 healthy, recreationally active men at the onset, and following exercise. All participants were performed a maximally exercise session in a motor-driven treadmill by using standard Bruce protocol which is the most widely used test to predict functional capacity. The method used in the present study consists of pre-processing, determination of the energy value based on wavelet packet transform, and classification phases. The results of the study demonstrated that changes in the MMG 176-234 Hz and EMG 254-313 Hz bands are critical to determine for muscle fatigue occurred following maximally exercise session. In conclusion, our study revealed that an algorithm with EMG and MMG combination based on frequency spectrum is more effective for the detection of muscle fatigue than EMG or MMG alone.

Determination of a new VLF band in HRV for ventricular tachyarrhythmia patients.

This study presents a new very low frequency (VLF) band range in ventricular tachyarrhythmia patients and involves an approach for estimation of effect of VLF band on ventricular tachyarrhythmia patients. A model based on wavelet packets (WP) and multilayer perceptron neural network (MLPNN) is used for determination of effective VLF band in heart rate variability (HRV) signals. HRV is decomposed into sub-bands including very low frequency parts and variations of energy are analyzed. Domination test is done using MLPNN and dominant band is determined. As a result, a new VLF band was described in 0.0039063-0.03125 Hz frequency range. This method can be used for other bands or other arrhythmia patients. Especially, estimation of dominant band energy using this method can be helped to diagnose for applications where have important effect of characteristic band.