Validity and reliability study of the quality of recovery scale in Turkish.

Background/aim: The aim of this study was to adapt the "Quality of Recovery-15 Scale", developed to measure the postoperative recovery quality of individuals, into Turkish by carrying out validity and reliability studies. Materials and methods: This methodological study was conducted with a total of 150 patients who underwent surgery under general anesthesia between November 2021 and January 2022 in a training and research hospital in the Black Sea region. Data was collected from the patients through the face-to-face interview method before the operation, on the 24th and the 48th hour postoperatively. First, the linguistic validity of the scale and then the validity and reliability analyses were carried out. Construct validity, confirmatory factor, and reliability analyses were then performed. Results: The Cronbach's alpha coefficient of the scale was 0.851. The Kaiser-Meyer-Olkin test for goodness of fit of the one-dimensional 14-item scale was 0.853 and Bartlett's test was significant. The goodness of fit values of the scale were found to be RMSEA = 0.149, CFI = 0.769, and GFI = 0.745, and they were considered acceptable levels. The eighth item was removed from the scale, which had originally consisted of 15 items, because the item correlation coefficient of this item was <0.200. Conclusion: The "Quality of Recovery Scale" was found to be a reliable and valid scale that can be used to measure the quality of recovery after surgery in Turkish society.

Employment and comparison of different Artificial Neural Networks for epilepsy diagnosis from EEG signals.

In this study, it has been intended to analyze Electroencephalography (EEG) signals by Wavelet Transform (WT) for diagnosis of epilepsy, to employ various Artificial Neural Networks (ANNs) for the signals' automatic classification. Furthermore, carrying out a performance comparison has been aimed. Three EEG signals have been decomposed into frequency sub bands by WT and the feature vectors have been extracted from these sub bands. In order to reduce the sizes of the extracted feature vectors, Principal Component Analysis (PCA) method has been applied when necessary and these feature vectors have been classified by five different ANNs as either epileptic or healthy. The performance evaluation has been carried out by conducting ROC analysis for the used ANN models that and their comparisons have also been included.

Design of a cervical collar device to facilitate and accelerate implementation of first aid.

Frequently there are disasters all over the world-fires, earthquakes, or even some unexpected shocking catastrophes. Hence people injured, or even died. Lifesaving actions begin with the initiation of the chain of survival. With every minute that passes without medical action being taken, the probability of being able to save the patients life decreases by ten percent. After 10 min there is normally no chance of resuscitation being successful. First aid is emergency treatment given before regular medical aid can be obtained. And it is a concept of first hands-on measures performed in a medical emergency by laypersons. The major aim of this study is to develop an easy-feasible cervical collar, for facilitating and accelerating implementation of first aid especially in case of collective injuries. The developed device is different from the cervical collars which are used to treat the neck pain. In the present study, the heartbeat is obtained by detecting pulse with the stethoscope that is a part of the developed device and fixed on the carorid artery. The obtained heartbeat signal has been processed by the electronic control circuit and the used LED has given light according to the patient's life signal. Although there are some disadvantages of the developed system, the precautions for these cases have been taken and the system has been tried to design in order to operate sensibly.

The design of thermoelectric footwear heating system via fuzzy logic.

In this study, Heat Control of Thermoelectric Footwear System via Fuzzy Logic has been implemented in order to use efficiently in cold weather conditions. Temperature control is very important in domestic as well as in many industrial applications. The final product is seriously affected from the changes in temperature. So it is necessary to reach some desired temperature points quickly and avoid large overshoot. Here, fuzzy logic acts an important role. PIC 16F877 microcontroller has been designed to act as fuzzy logic controller. The designed system provides energy saving and has better performance than proportional control that was implemented in the previous study. The designed system takes into consideration so appropriate parameters that it can also be applied to the people safely who has illnesses like diabetes, etc.