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    The effect of modifiable lifestyle factors on semen quality
    (Ediciones Doyma, S.L., 2020) Kaya, C.; Aykaç, A.; Kaya, Y.; Tas, M.
    Introduction and objectives: To examine the association between lifestyle factors (body mass index, smoking, alcohol consumption, coffee intake, physical activity, sauna and cell phone usage, wearing tight-fitting underwear), and conventional semen parameters. Materials and methods: 1311 participants who attended the Andrology Clinic were included in the study. All participants were separated into two groups as men with normozoospermia and dysspermia. All participants answered a questionnaire which contains questions about the modifiable lifestyle factors. The total risk scores were calculated after all the positive lifestyle factors had been counted. Results: Men with normozoospermia and dysspermia consisted of 852 (65.0%) and 459 (35.0%) participants respectively. A negative relationship between the wearing of tight underwear and having normal semen parameters was detected between the two groups (p = 0.004). While going to a sauna regularly was negatively related to semen concentration, wearing tight underwear was also related to both lower motility, normal morphology as well as semen concentration (p < 0.05). While the total score of all participants was 5.22 ± 1.34 point, there were no statistical differences between the two groups (p = 0.332). It was found that having 3 more or fewer points was not related to any type of semen parameters and results of a spermiogram. Conclusion: The clinicians should give advice to infertile male patients about changing their risky lifestyle, for infertility, to a healthy lifestyle for fertility. Better designed studies, with larger sample sizes using conventional semen analysis with sperm DNA analysis methods, should be planned to identify the possible effects of lifestyle factors on semen quality. © 2019 Asociación Española de Andrología, Medicina Sexual y Reproductiva
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    EOG based intelligent direction detect system with pre-filtering algorithm
    (Institute of Electrical and Electronics Engineers Inc., 2015) Erkaymaz, H.; Özer, M.; Kaya, C.; Orak, I.M.
    Nowadays, artificial movements have been obtained by utilizing other organs for paralyzed patients. Especially the usage of eye movements for giving message to outside world became popular as a scientific subject. In studies according to eye movements, the Electrooculogram (EOG) signal is used. In this study, the vertical and horizontal EOG signals taken from electrodes, placed around the eyes, have been modelled by using Artificial Neural Networks (ANN) which is one of artificial intelligent technique. The system can sense four main directions (Right, Left, Up and Down) at the same time it can also detect blinking movements. Firstly, the signals have been pre-filtered, amplified and classified by ANN. The performance of recommended model has been demonstrated by analyzing statistical accuracy and confusion matrix according to the features of obtained signal. It has been seen that eye movements can be successfully determined by designed model. © 2015 IEEE.