Browsing by Author "Yildiz, Metin"

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Can Sleep Apnea be Detected by Heart Sounds?
(2017) Yildiz, Metin; Tabak, Zeynep; Yetkin, Sinan
Objective: It has previously been shown that there are morphological changes in hearth sounds during respiration and holding breath. In this study, for the first time in the literature, it was investigated whether sleep apnea could be detected automatically from heart sounds by teaching various classifiers of time and frequency plane parameters which are thought to be able to characterize the morphological changes seen in heart sounds during apnea. Materials and Methods: For this purpose, heart sounds were recorded simultaneously with full polysomnography records from 17 people. Classification studies were performed by assigning feature vectors obtained from heart sounds to K nearest neighbors and support vector machines. Results: The best result with K nearest neighbor classifier was 48% accuracy, 100% selectivity level. With support vector machines classifier, 82% accuracy and 42% selectivity values were reached. Conclusion: According to these values, it is concluded that the parameters of the heart sound used in this study do not make it possible to diagnose the sleep apnea from the heart sounds.
Computer Based Eye-Writing System by Using Eog
(2015) Ulkutas, Hesna Ozbek; Yildiz, Metin; 0000-0002-2554-6953; JJF-5070-2023
The aim of this study is to suggest a faster method that would also have better accuracy rate in coding eye movements into characters compared to previously developed by EOG visual writing techniques and to develop a system of computer-based applications that would implement this new method. To this end, several experiments were utilized in order to determine the performance of the observed coding method we propose, with reference to these experiments results; a new method encoding 29 letters and 3 commands ( spaces, erase, read) by utilizing only 4 directions with two different angles and four different waiting period is proposed. For implementing proposed new technique, a computer based EOG measurement and inference system is developed. The results of trials with this newly developed system indicate that while the accuracy rate of coding into right characters in the first trial of a text comprised of 180 letters is 92.5%, this accuracy rate of the coding reaches to 100% starting from the fourth trial of the technique. Average writing speed of 16.8 words per minute that is measured with this method is the highest rate that has been achieved among EOG-based systems.
Development of Computer Based Ballistocardiography System
(2014) Ozturk, Nurhan; Yildiz, Metin; https://orcid.org/0000-0002-2554-6953; JJF-5070-2023
Ballistocardiography is a measurement method which monitors physiologic parameters such as heart rate and respiration through measuring the vibrations caused by heart beat. In this study, a computer based system which enables monitoring the changes in the heart rate and respiration without any electrical connection with the patient is introduced. It is examined whether this system can be used in monitoring the heart beat velocity and respiration through making comparisons with a commercial data acquisition system. During the study, it is observed that heart beat velocity is determined with a maximum 5% error and respiration frequency with a maximum 5.8%. Furthermore, respiratory standstill can be detected with this system. According to these results, it could be concluded that the system can be used as pre-diagnosis with the aim of monitoring respiration disorders during sleep.
Effect of Spontaneous Saliva Swallowing on Short-Term Heart Rate Variability (HRV) and Reliability of HRV Analysis
(2018) Yildiz, Metin; Doma, Serian; 0000-0002-2554-6953; 28949087
The effects of effortful swallowing and solid meal ingestions on heart rate variability (HRV) have been examined previously. The effects of spontaneous saliva swallowing on short-term HRV and reliability of HRV analysis have not been studied before. The effect of saliva swallowing on HRV analyses parameters [meanRRI, SDNN (standard deviation of normal-to-normal), LF (low frequency), HF (high frequency) powers, LH/HF] and the reliability of LF and HF powers were investigated by frequency, time-frequency and intraclass correlation coefficient (ICC) analyses. Electrocardiogram and swallowing signal that obtained from an electronic stethoscope placed on the necks of subjects were recorded simultaneously from 30 healthy and young volunteers in sitting position during 15min. Spontaneous swallowing has been shown to significantly alter some HRV parameters (SDNN, LF power and LF/HF ratio). Time-frequency analysis results showed that the contribution of saliva swallowing to LF (1-58%) and HF (2-42%) powers could change significantly depending on the number of swallowing. The ICC of the LF and HF powers for the successive 5-min signal segments were found 089, 092, respectively. These values decreased to 073 and 090 in the subjects with more swallowing rate. When the analyses were made for 2-min signal periods, these values decreased to 063 and 067. We concluded that spontaneous saliva swallowing can change HRV parameters. We have also seen that changes in swallowing rate and use of short signal segments may reduce the reliability of HRV analyses.
Evaluation of Moro reflex with an objective method in late preterm and term infants
(2019) Ince, Deniz Anuk; Ecevit, Ayse; Yildiz, Metin; Tugcu, Ali Ulas; Ceran, Burak; Tekindal, Mustafa Agah; Turan, Ozden; Tarcan, Aylin; 0000-0002-4369-2110; 0000-0002-2554-6953; 30660088; I-6746-2016
Eye Gaze Location Detection Based On Iris Tracking with Web Camera
(2018) Yildiz, Metin; Yorulmaz, Muhammet; C-7863-2018
In recent years, there has been an increased interest in human computer interaction systems where web cameras are used as input devices. In this study, a system developed to distinguish eye gaze locations on the screen by referring to the position of the iris part of the eye is introduced. It is aimed to distinguish more eye gaze location compared to the previous works by web cam. K-nearest neighbors classifier was used to detect eye gaze location by the feature vector of the iris center coordinates. As a result of the first experiments with 10 subjects, the 17 different eye gaze locations on the screen have classified with an average of 97.64% accuracy. It has been observed that only the two adjacent points near the center of the screen in the vertical direction are detected incorrectly. It is expected to increase the classification performance ratio by not using these two incorrectly detected points in future studies.
Feasıbility of Heart Rate Variability Analysis With Heart Sounds
(2014) Yildiz, Metin; Turkoglu, Zeynep; https://orcid.org/0000-0002-2554-6953; JJF-5070-2023
Heart rate variability (HRV) analysis, which is providing information about the autonomic nervous system with non-invasive method, performed with using digitized electrocardiogram records. In this study, whether HRV analysis can be done from heart sounds (which are recorded with electronic stethoscopes) has been investigated. For this purpose, an algorithm has been developed for detecting the consecutive heart time period from simultaneously recorded heart sounds and ECG. Some standard HRV parameters are calculated and compared from the HRV derived from ECG and heart sound signals. The experimental results show that, both HRV parameters derived from the heart sounds while the resting position and the ECG are very close. In conclusion, they can be used in HRV analysis.
A Feasibility Study of Communication with Cold Stimulations
(2014) Budak, Erdem Inanc; Yildiz, Metin; https://orcid.org/0000-0002-2554-6953; JJF-5070-2023
Some part of available sytems which requires surgery (kohlear implant) for communication of completely deaf people, other parts just heal for one side hearing impaired people (soundbite technologies). Thus, there are lot of research of tactiles that are methods for communication through skin. However, existing communication systems's speed are too low, also devices couldn't move because, they working with electricity and have big massive. In this paper we have developed alternative communication method that the system uses cold stimulus for transfer characters through skin and also first tests have been done. We used peltiers for exist to cold stimuli and developed a computer based control system to transfer to peltiers via coding. We saw that subjects perceived two stimulus per second at one point of their forearms. But when we used more than one stimulus for coding characters, perception percent get low. Overall of results, we prove that communication with thermal way is alternative method that gives promise.
Gaze-Controlled Turkish Virtual Keyboard Application with Webcam
(2019) Yildiz, Metin; Yorulmaz, Muhammet; C-7863-2018
In this study, an easy-to-use and inexpensive system aimed at solving the communication needs of people with disabilities such as ALS by writing with their eyes was introduced. The performance of the system are measured by writing speed (word per minutes) and error rate. The system consists of a webcam that fixed in front of the eye with a plastic eyeglass, and a computer. On the keyboard proposed in this study, the characters to be typed are placed at 22 discrete points which can be detected without error. 16 characters which are most used in Turkish (total %85 usage rate), can be selected with a single gaze. Other characters can be selected with gazing these points with a dwell time. The iris circle on the image recorded by the camera is found according to the Hough transform and the position of the center coordinates of the eye is classified by using the k-nearest neighbor algorithm from the machine learning methods and the character to be written is determined. In order to select the letters at the gaze points, the letter that is highlighted by the software in voice and color is moved to the writing area in the middle of the screen by eye. As a result of the first experiments, it has been observed that the system developed allows the average of 6.63 words per minute (approximately 33 letters) to be written with an error rate of 0.86%.
Issues related to reliability of HRV analysis and effect of spontaneous saliva swallowing on HRV
(2017) Yildiz, Metin; Doma, Serian; 0000-0002-2554-6953; 2-s2.0-85020877461; 28617300
A New PC-Based Text Entry System Based on EOG Coding
(2018) Yildiz, Metin; Ulkutas, Hesna Ozbek; 0000-0002-2554-6953
ome disadvantages of optical eye tracking systems have increased the interest to EOG (Electrooculography) based Human Computer Interaction (HCI). However, text entry attempts using EOG have been slower than expected because the eyes should move several times for entering a character. In order to improve the writing speed and accuracy of EOG based text entry, a new method based on the coding of eye movements has been suggested in this study. In addition, a real time EOG based HCI system has developed to implement the method. In our method all characters have been encoded by single saccades in 8 directions and different dwell time. In order to standardize dwell times and facilitate the coding process, computer assisted voice guidance was used. A number of experiments have been conducted to examine the effectiveness of the proposed method and system. At the end of the fifth trials, an experienced user was able to write at average 13.2 wpm (5 letters = 1 word) with 100% accuracy using the developed system. The results of our experiments have shown that text entry with the eye can be done quickly and efficiently with the proposed method and system.
A Preliminary Study on OSA Severity Levels Detection by Evaluating Speech Signals Nonlinearities With Multi-Class Classification
(2023) Ugur, Tugce Kantar; Yilmaz, Derya; Yildiz, Metin; Yetkin, Sinan
Diagnosis of obstructive sleep apnea (OSA) from speech has become a popular research area in recent years, which can be an alternative way to the application difficulties in polysomnography (PSG). The promising results obtained in our previous study, in which we tried to detect apnea using nonlinear analysis of speech, gave rise to the thought that it is possible to detect OSA and OSA severity by diversifying speech samples and nonlinear features. The principal aim of this study, for the first time in the literature, is to detect the OSA severity levels as mild, moderate, and severe as in the clinic use (multi-class classification) using nonlinear analyses of speech while the patient is awake. In addition, healthy/OSA classification (binary classification) was also carried out. The feature selection method of ANOVA was applied to 336 features (28 voices x 12 features) for each subject, 14 and 5 features were used in multi-class and binary classifications, respectively. As a result of the classifications made with various KNN and SVMs models, the best results were obtained by SVMs in both classifications for OSA severities (with one-vs-all classification scheme and the Gaussian kernel) and OSA detection (with the quadratic kernel) as 82% and 95.1% accuracies, respectively. The proposed study showed that OSA and OSA severity can be determined with the small number of nonlinear features calculated from a few different speech samples, in nearly 15 minutes, consistent with PSG results (simple snorer, mild, moderate, and severe OSA). In conclusion, the highest OSA/healthy classification accuracy rate in the literature was achieved. Furthermore, OSA severity detection in four-class performed quite well as a preliminary study.
The Source of Heart Rhythm Changes Caused by Swallowing
(2020) Yildiz, Metin; Domaz, Serian; 32613437
Swallowing can lead to the development of syncope in people who have difficulty swallowing during food intake. It has shown that even spontaneous saliva swallowing can change heart rate variability (HRV). Recently, it has been suggested that changes in heart rate during swallowing may be caused by respiratory activities. In this study, the hypothesis that swallowing induced HRV are caused from breathing changes during swallowing has been tested. For this purpose, electrocardiogram (ECG), chest circumference (respiration) signals and swallowing sounds were recorded simultaneously from 20 subjects. Subjects were asked not to swallow their saliva in the first 4 min of the experiment and to swallow them several times in the next 4 min. To observe respiratory effects on HRV during swallowing, a detailed cardio-respiratory system mathematical model was used. By applying recorded chest circumference signal to the mathematical model, respiration induced HRV changes were obtained. The HRV parameters of with and without swallowing regions of the real (obtained from ECG) and model-HRV (obtained from mathematical model) were compared by paired Studentttest. Statistical differences seen in the real-HRV between the swallowing and non-swallowing regions (SDNN, LF power, approximate entropy) were not observed in the model-HRV. Considering that the only factor constituting HRV in the mathematical model is respiration, it was concluded that swallowing changes HRV with a mechanism other than breathing changes.