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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3

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Department: search.filters.department.Department of Mechanical EngineeringSubject: search.filters.subject.Urology

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    A novel method for hemodynamic analysis of penile erection
    (Springernature, 2022) Yıldırım, Canberk; Ertürk, Hakan; Şerefoğlu, Ege Can; Department of Mechanical Engineering; N/A; Pekkan, Kerem; Deniz, Sinan; Faculty Member; Doctor; Department of Mechanical Engineering; College of Engineering; N/A; N/A; Koc University Hospital; 161845; N/A
    Measurement of blood flow velocity through the cavernosal arteries via penile color Doppler ultrasound (PDUS) is the most common objective method for the assessment of erectile function. However, in some clinical cases, this method needs to be augmented via the invasive intracavernosal pressure (ICP) measurement, which is arguably a more direct index for erectile function. The aim of this study is to develop a lumped parameter model (LPM) of the penile circulation mechanism integrated to a pulsatile, patient-specific, bi-ventricular circulation system to estimate ICP values non-invasively. PDUS data obtained from four random patients with erectile dysfunction are used to develop patient-specific LPMs. Cardiac output is estimated from the body surface area. Systemic pressure is obtained by a sphygmomanometer. Through the appropriate parameter set determined by optimization, patient-specific ICP values are predicted with only using PDUS data and validated by pre- and post-papaverine injection cavernosometry measurements. The developed model predicts the ICP with an average error value of 3 mmHg for both phases. Penile size change during erection is predicted with a similar to 15% error, according to the clinical size measurements. The developed mathematical model has the potential to be used as an effective non-invasive tool in erectile function evaluation, expanding the existing clinical decision parameters significantly.
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    A patient-specific lumped parameter model of human penile erection
    (Wiley, 2017) Erturk, H.; Culha, M. G.; Serefoglu, E. C.; Department of Mechanical Engineering; Pekkan, Kerem; Faculty Member; Department of Mechanical Engineering; College of Engineering; 161845
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    Toilet-based continuous health monitoring using urine
    (Nature Portfolio, 2022) Department of Mechanical Engineering; Taşoğlu, Savaş; Faculty Member; Department of Mechanical Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Engineering; 291971
    Regular health monitoring can result in early detection of disease, accelerate the delivery of medical care and, therefore, considerably improve patient outcomes for countless medical conditions that affect public health. A substantial unmet need remains for technologies that can transform the status quo of reactive health care to preventive, evidence-based, person-centred care. With this goal in mind, platforms that can be easily integrated into people’s daily lives and identify a range of biomarkers for health and disease are desirable. However, urine — a biological fluid that is produced in large volumes every day and can be obtained with zero pain, without affecting the daily routine of individuals, and has the most biologically rich content — is discarded into sewers on a regular basis without being processed or monitored. Toilet-based health-monitoring tools in the form of smart toilets could offer preventive home-based continuous health monitoring for early diagnosis of diseases while being connected to data servers (using the Internet of Things) to enable collection of the health status of users. In addition, machine learning methods can assist clinicians to classify, quantify and interpret collected data more rapidly and accurately than they were able to previously. Meanwhile, challenges associated with user acceptance, privacy and test frequency optimization should be considered to facilitate the acceptance of smart toilets in society.