Statistical Analysis of Electrocardiogram Signal for Sleep / Awake Stages

Uyku evreleme uyku laboratuvarlarında sıklıkla kullanılan hastalık te¸shis yöntemlerinin önemli bir a¸samasıdır. Bireyden alınan elektroensefalografi, elektrookulogram ve elektromiyografi gibi biyolojik sinyallerin uzman doktor tarafından incelenmesiyle birlikte uyku evreleri tespit edilir. 5 farklı evre vardır. Bunlar Uyanıklık, Evre 1, Evre 2, Evre 3 ve Hızlı Göz Hareketleri evresidir. Bazı hastalıklarda uykunun her evresinin belirlenmesine ihtiyaç yoktur. Sadece Uyku / Uyanıklık durumlarının belirlenmesi yeterlidir. Bu çalı¸smada, daha kolay elde edilebilir olan elektrokardiyografi sinyali ile Uyku / Uyanıklık durumları arasındaki ili¸ski istatistiksel olarak incelenmi¸stir. Bunun için iki bireyden alınan uyku kayıtları sayısal filtreler ile temizlenmi¸s ve 30 saniyelik epoklara bölünmü¸stür. Her epoktan 25 adet özellik çıkarılmı¸s ve özelliklerin Uyku / Uyanıklık ile arasındaki istatistiksel ili¸ski saptanmı¸stır. 25 özelli˘gin 21’inin Uyku / Uyanıklık ile istatistiksel olarak (p < 0:05) ili¸skili oldu˘gu tespit edilmi¸stir. Sonuç olarak elektrokardiyografi sinyalinin Uyku / Uyanıklık tespitinde kullanılabilece˘gi kanısına varılmı¸stır.Sleep staging is an important stage of the disease diagnosis methods commonly used in sleep laboratories. pecialist physician detects sleep stages according to biological signals such as electroencephalography, electrocyogram and electromyography. There are 5 different stages. These are Awake, Stage 1, Stage 2, Stage 3 and Rapid Eye Movement Sleep. In some diseases, there is no need to determine each stage of sleep. It is sufficient to determine only the Sleep / Awake stages. In this study, the relationship between electrocardiographic signal and Sleep / Awake states which are more easily available was analyzed statistically. For this purpose, sleep records from two individuals were cleaned with numerical filters and divided into 30 second epochs. Twenty-five features were removed from each epoch and a statistical relationship was found between the features of Sleep and Awake. 21 of the 25 features were found to be correlated with Sleep / Awake (p < 0:05). As a result, it has been concluded that electrocardiography signal can be used in sleep / awake detection

The Effect of Treatment on Nitric Oxide and Asymmetric Dimethyl Arginine Levels in Asthma Patients

Giriş ve Amaç: Asimetrik dimetilarjinin (ADMA) ve nitrik oksit (NO), etkilerini birlikte gösterirler, bu moleküller arasındaki denge hava yolu tonusunun ve fonksiyonunun sıkı düzenlenmesine katkıda bulunmaktadır. Çalışmamızda astım tedavisinin serum ADMA, NO, düzeylerine solunum fonksiyon testlerindeki (SFT) değişimlerine, Total IgE, hemogram düzeylerindeki değişiklikleri belirlemeyi amaçlanmıştır. Gereç ve Yöntemler: Çalışmamızda astım tanısı konmuş 30 erkek/kadın hasta (40-60 yaş) ve benzer yaş grubunda 24 erkek/kadın kontrol grubu kullanılmıştır. Çalışmada tedavi öncesi ve sonrası hasta ve kontrol gruplarından serum ADMA, NO, Total IgE düzeylerine ELISA yöntemiyle ve hemogram düzeyleri ise otomatik kan sayım cihazında belirlenmiştir. Bulgular: Astımlı hastaların tedavi öncesi ve tedavi sonrası ADMA ve NO düzeyleri kontrol grubu ile arasında anlamlı fark bulunmuştur (p<0,001). Astımlı hastaların tedavi öncesi ve tedavi sonrası grupların total IgE düzeyleri kontrol grubu ile arasında fark istatistiksel olarak anlamlı bulunmuştur. (p<0,001). Astımlı hastaların tedavi öncesi ve tedavi sonrası grupların %FVC ve % PEF25−75% düzeyleri kontrol grubu ile arasındaki fark, tedavi öncesi grubun %FVC, %PEF25−75% düzeyleri tedavi sonrası grup arasındaki fark istatistiksel olarak anlamlı bulunmuştur (p<0,001). Sonuç: Astım hastalarında tedavinin hastalar üzerindeki etkileri bu çalışma ile belirlenmiş ve elde edilen veriler tedavi sonrası astım hastalarında iyileşme gözlenen parametre düzeylerinin astım hastalarında tedaviye yanıtın takibinin belirlenmesinde kullanılabileceği ortaya konmuştur.Objective: Asymmetric dimethyl arginine (ADMA) and nitric oxide (NO) show their effects together and the balance between these molecules contributes to the tight regulation of airway tone and function. In this study, we aimed to determine the changes in serum ADMA, NO, levels of pulmonary function tests (PFT), total IgE and hemogram levels of asthma treatment. Materials and Methods: In this study, 30 male / female patients (40-60 years) diagnosed with asthma and 24 male / female control groups of similar age group were used. In the study, serum ADMA, NO, Total IgE levels before and after treatment were determined by ELISA method using commercial kit and hemogram levels were determined by automatic blood counting device. Results: There was a significant difference between ADMA and NO levels in asthmatic patients before and after treatment (p<0.001). The difference between total IgE levels of asthmatic patients before and after treatment was found to be statistically significant (p<0.001). The difference between the FVC% and PEF25-75% levels of the pretreatment and post-treatment groups of the asthmatic patients with the control group and the %FVC and %PEF25- 75% of the pretreatment group were found to be statistically significant (p<0.001). Conclusion: The effects of treatment on asthmatic patients were determined in this study and it was shown that the parameter levels improved in asthmatic patients after treatment can be used to determine the response to treatment in asthmatic patients

Automatic sleep staging in obstructive sleep apnea patients using photoplethysmography, heart rate variability signal and machine learning techniques

It is extremely significant to identify sleep stages accurately in the diagnosis of obstructive sleep apnea. In the study, it was aimed at determining sleep and wakefulness using a practical and applicable method. For this purpose , the signal of heart rate variability (HRV) has been derived from photoplethysmography (PPG). Feature extraction has been made from PPG and HRV signals. Afterward, the features, which will represent sleep and wakefulness in the best possible way, have been selected using F-score feature selection method. The selected features were classified with k-nearest neighbors classification algorithm and support vector machines. According to the results of the classification, the classification accuracy rate was found to be 73.36 %, sensivity 0.81, and specificity 0.77. Examining the performance of the classification, classifier kappa value was obtained as 0.59, area under an receiver operating characteristic value as 0.79, tenfold cross-validation as 77.35 %, and F-measurement value as 0.79. According to the results accomplished, it was concluded that PPG and HRV signals could be used for sleep staging process. It is a great advantage that PPG signal can be measured more practically compared to the other sleep staging signals used in the literature. Improving the systems, in which these signals will be used, will make diagnosis methods more practical

Smoking prevalence among elementary school-age children in Sirnak province in Turkey

Conclusion: The findings suggested that smoking prevalence can be high and nicotine addiction can be common among elementary school-aged children (age interval: 6-14 years) in Sirnak in Turkey, in addition to demonstrating that these children can easily access tobacco without experiencing any difficulties

Assessment of the Results of the Prick Tests Carried Out in Düzce Province

Skin prick test is a simple, inexpensive, reliable, and rapid test that is widely utilized in clinical practice. Allergic conditions develop as a result of various factors including genetic predisposition, humidity, plant cover, and altitude. Our objective was to assess the allergic sensitivity rate among allergic patients in D&uuml;zce province. A retrospective patient file evaluation was carried out among 310 subjects attending to a Chest Diseases Outpatient Facility in D&uuml;zce with respiratory complaints such as asthma and allergic rhinitis between May 2014 and May 2016. The results of skin prick test were stratified according to age and gender. Of the 310 patients included 187 (60.3%) were male and 123 (39.7%) were female. The most common reaction observed was against D. Farinea in 44 subjects (14.2). Other common reactions included D. Pteronyssinus in 35 patients (11.3%), grass in 19 patients (6.1%), cereals in 19 patients (6.1%), and grass mixture in 16 patients (5.15%). The peak incidence of reactions occurred between 20 and 29 years of age. For atopic patients residing in the province of D&uuml;zce, particular attention should be given to dust mite, grass, or cereal allergens

Signal Processing and Communications Applications Conference

Obstructive Sleep Apnea diagnosis is diagnosed by a specialist doctor, examining the records taken with the polysomnography device. Sleep staging is the first and most important step in diagnosis. In the second step, diagnose with respiratory scoring. Sleep staging can be performed with at least three signals and ten channel electrodes. The electrodes are can be connected only by a qualified technician to the patient. Electrode connection patterns disrupt the patient's natural sleep environment. In addition, diagnosis can be made only in the laboratory. There is a need for practical measurement systems to solve these problems. In this study, it is suggested that Heart Rate Variable (HRV) derived from Photopethemography (PPG) signal can be used in sleep staging. In the study, HRV was derived from the PPG signal. 15 features were extracted from the HRV in the time domain. Mann-Whitney U Test was used for statistical analysis and distinctive features have been identified for sleep arousal. Mann-Whitney U Test was used to determine whether the extracted features were a distinguishing feature for the Sleep Awakening status. When the results are examined, it was determined that p < 0.05 for all features discriminant for sleep wakefulness. When the results are examined, HRV derived from the PPG signal can be used to develop a sleep staging system which can be used at home

Elektrokardiyogram Sinyalinin Uyku / Uyanıklık Evreleri için İstatistiksel Olarak İncelenmesi

Uyku evreleme uyku laboratuvarlarında sıklıkla kullanılan hastalık te¸shis yöntemlerinin önemli bir a¸samasıdır. Bireyden alınan elektroensefalografi, elektrookulogram ve elektromiyografi gibi biyolojik sinyallerin uzman doktor tarafından incelenmesiyle birlikte uyku evreleri tespit edilir. 5 farklı evre vardır. Bunlar Uyanıklık, Evre 1, Evre 2, Evre 3 ve Hızlı Göz Hareketleri evresidir. Bazı hastalıklarda uykunun her evresinin belirlenmesine ihtiyaç yoktur. Sadece Uyku / Uyanıklık durumlarının belirlenmesi yeterlidir. Bu çalı¸smada, daha kolay elde edilebilir olan elektrokardiyografi sinyali ile Uyku / Uyanıklık durumları arasındaki ili¸ski istatistiksel olarak incelenmi¸stir. Bunun için iki bireyden alınan uyku kayıtları sayısal filtreler ile temizlenmi¸s ve 30 saniyelik epoklara bölünmü¸stür. Her epoktan 25 adet özellik çıkarılmı¸s ve özelliklerin Uyku / Uyanıklık ile arasındaki istatistiksel ili¸ski saptanmı¸stır. 25 özelli˘gin 21’inin Uyku / Uyanıklık ile istatistiksel olarak (p < 0:05) ili¸skili oldu˘gu tespit edilmi¸stir. Sonuç olarak elektrokardiyografi sinyalinin Uyku / Uyanıklık tespitinde kullanılabilece˘gi kanısına varılmı¸stır.Sleep staging is an important stage of the disease diagnosis methods commonly used in sleep laboratories. pecialist physician detects sleep stages according to biological signals such as electroencephalography, electrocyogram and electromyography. There are 5 different stages. These are Awake, Stage 1, Stage 2, Stage 3 and Rapid Eye Movement Sleep. In some diseases, there is no need to determine each stage of sleep. It is sufficient to determine only the Sleep / Awake stages. In this study, the relationship between electrocardiographic signal and Sleep / Awake states which are more easily available was analyzed statistically. For this purpose, sleep records from two individuals were cleaned with numerical filters and divided into 30 second epochs. Twenty-five features were removed from each epoch and a statistical relationship was found between the features of Sleep and Awake. 21 of the 25 features were found to be correlated with Sleep / Awake (p < 0:05). As a result, it has been concluded that electrocardiography signal can be used in sleep / awake detection

Signal Processing and Communications Applications Conference

Obstructive Sleep Apnea is a disease that occurs due to respiratory arrest in sleep. The diagnosis of the disease is made with the polysomnography device, which is the gold standard method of diagnosis. Diagnosis is performed by sleep staging and respiratory scoring steps. Respiratory scoring is performed with at least four signals. Technical knowledge is required to connect the electrodes. Moreover, the electrodes are so disturbing that it will delay the patient's sleeping time. Alternative systems for polysomnography devices are needed to solve these problems. In the study, Heart Rate Variable (HRV) derived from the photoplethysmographic signal was proposed for respiratory scoring. For the study, 15 features were extracted from HRV. Mann-Whitney U Test was used to determine whether the extracted features were distinguishing for apnea and control groups. According to the results, p < 0.05 belongs to properties 1-9 and 13-15, and these properties were found to be distinctive for the groups. According to the results of the study, respiratory scoring can be performed more practically by using HRV

Signal Processing and Communications Applications Conference

Obstructive Sleep Apnea diagnosis is diagnosed by a specialist doctor, examining the records taken with the polysomnography device. Sleep staging is the first and most important step in diagnosis. In the second step, diagnose with respiratory scoring. Sleep staging can be performed with at least three signals and ten channel electrodes. The electrodes are can be connected only by a qualified technician to the patient. Electrode connection patterns disrupt the patient's natural sleep environment. In addition, diagnosis can be made only in the laboratory. There is a need for practical measurement systems to solve these problems. In this study, it is suggested that Heart Rate Variable (HRV) derived from Photopethemography (PPG) signal can be used in sleep staging. In the study, HRV was derived from the PPG signal. 15 features were extracted from the HRV in the time domain. Mann-Whitney U Test was used for statistical analysis and distinctive features have been identified for sleep arousal. Mann-Whitney U Test was used to determine whether the extracted features were a distinguishing feature for the Sleep Awakening status. When the results are examined, it was determined that p < 0.05 for all features discriminant for sleep wakefulness. When the results are examined, HRV derived from the PPG signal can be used to develop a sleep staging system which can be used at home