Browsing by Author "Aksahin, Mehmet"

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Multifunctional Phototherapy Device Design
(2019) Aksahin, Mehmet
Today, phototherapy devices are used to treat newborn jaundice. However, there are some cases that the commercial phototherapy devices are inadequate. Most of the device are controlled only at the certain interval that prevents instantaneous monitoring the newborn's vital parameters. For other cases, devices are one-way lighting. In addition, when the baby is taken away from the device, unnecessary lighting causes the decrease in LED's lifetime. In the scope of the study, intensive phototherapy device was developed to eliminate deficiencies that are mentioned above. Properties of the developed phototherapy device are; Automatic detection of newborn's presence, double-sided illumination, continuous monitoring with IP webcam, temperature measurement of the environment and also newborn's body temperature. The light intensity of the device was measured with a photometer as 28.6 mu W/cm(2)/nm that was obtained from 460nm wavelength LED illumination in both top and bottom in accordance with the American Academy of Pediatrics (AAP) guideline.
Obstructive Sleep Apnea Classification with Artificial Neural Network Based On Two Synchronic Hrv Series
(2015) Aksahin, Mehmet; Erdamar, Aykut; Firat, Hikmet; Ardic, Sadik; Erogul, Osman; 0000-0001-8588-480X; AAA-6844-2019
In the present study, "obstructive sleep apnea (OSA) patients" and "non-OSA patients" were classified into two groups using with two synchronic heart rate variability (HRV) series obtained from electrocardiography (ECG) and photoplethysmography (PPG) signals. A linear synchronization method called cross power spectrum density (CPSD), commonly used on HRV series, was performed to obtain high-quality signal features to discriminate OSA from controls. To classify simultaneous sleep ECG and PPG signals recorded from OSA and non-OSA patients, various feed forward neural network (FFNN) architectures are used and mean relative absolute error (MRAE) is applied on FFNN results to show affectivities of developed algorithm. The FFNN architectures were trained with various numbers of neurons and hidden layers. The results show that HRV synchronization is directly related to sleep respiratory signals. The CPSD of the HRV series can confirm the clinical diagnosis; both groups determined by an expert physician can be 99% truly classified as a single hidden-layer FFNN structure with 0.0623 MRAE, in which the maximum and phase values of the CPSD curve are assigned as two features. In future work, features taken from different physiological signals can be added to define a single feature that can classify apnea without error.
Photodynamic Therapy-Induced Microvascular Changes in a Nonmelanoma Skin Cancer Model Assessed by Photoacoustic Microscopy and Diffuse Correlation Spectroscopy
(2016) Rohrbach, Daniel J.; Salem, Hakeem; Aksahin, Mehmet; Sunar, Ulas
One of the main mechanisms of action for photodynamic therapy (PDT) is the destruction of tumor vasculature. We observed the PDT-induced vasculature destruction in a mouse model of skin cancer using two techniques: Photoacoustic microscopy (PAM) and diffuse correlation spectroscopy (DCS). PAM showed high-resolution images of the abnormal microvasculature near the establishing tumor area at pre-PDT, as well as the subsequent destruction of those vessels post-PDT. DCS indicated a significant blood flow decrease after PDT, confirming the vascular destruction. Noninvasive assessment of vascular changes may be indicative of therapy response.