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    Classification of Parkinson's Disease Using Dynamic Time Warping
    (IEEE, 2019) Kurt, Ilke; Ulukaya, Sezer; Erdem, Oguzhan
    Deteriorations in handwriting or in basic shape sketching are one of the most referenced symptoms for early diagnosis of Parkinson's disease (PD). For this reason, the design of a fair, trustworthy and efficacious Computer-aided Diagnosis (CAD) model has supportive importance for the early diagnosis of PD. In this study we investigate the effectiveness of Dynamic Time Warping (DTW) algorithm, which is applied to Archimedean spiral drawings of patients with PD and healthy controls (HC), on PD and healthy subject classification problem. Leave-one-subject-out (LOSO) cross validation scheme is used while training and testing in support vector machine (SVM) and k-nearest neighbors (k-NN) classifiers with various parameters. The accuracy results of %94.44 (%95.83) and %97.52 (%94.44) are achieved by k-NN and SVM classifiers respectively for static (dynamic) spiral test.
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    Individuals with a COVID-19 history exhibit asymmetric gait patterns despite full recovery
    (Elsevier Sci Ltd, 2022) Keklicek, Hilal; Selcuk, Halit; Kurt, Ilke; Ulukaya, Sezer; Ozturk, Gulnur
    COVID-19 is a multisystem infectious disease affecting the body systems. Its neurologic complications include -but are not limited to headache, loss of smell, encephalitis, and cerebrovascular accidents. Even though gait analysis is an objective measure of the neuro-motor system and may provide significant information about the pathophysiology of specific diseases, no studies have investigated the gait characteristics in adults after full recovery from COVID-19. This was a cross-sectional, controlled study that included 12 individuals (mean age, 23.0 +/- 4.1 years) with mild-to-moderate COVID-19 history (COVD) and 20 sedentary controls (CONT; mean age, 24.0 +/- 3.6 years). Gait was evaluated using inertial sensors on a motorized treadmill. Spatial-temporal gait parameters and gait symmetry were calculated by using at least 512 consecutive steps for each participant. The effect-size analyses were utilized to interpret the impact of the results. Spatial-temporal gait characteristics were comparable between the two groups. The COVD group showed more asymmetrical gait patterns than the CONT group in the double support duration symmetry (p = 0.042), single support duration symmetry (p = 0.006), loading response duration symmetry (p = 0.042), and pre-swing duration symmetry (p = 0.018). The effect size analyses of the differences showed large effects (d = 0.68-0.831). Individuals with a history of mild-to-moderate COVID-19 showed more asymmetrical gait patterns than individuals without a disease history. Regardless of its severity, the multifaceted long-term effects of COVID-19 need to be examined and the scope of clinical follow-up should be detailed.
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    Musical Feature Based Classification of Parkinson's Disease Using Dysphonic Speech
    (IEEE, 2018) Kurt, Ilke; Ulukaya, Sezer; Erdem, Oguzhan
    Speech and voice disorders are one of the most significant biomarkers in early diagnosis of Parkinson's disease (PD). The development of an objective, reliable and effective prediction model is crucial for the early detection of PD by experts. The aim of this study is to investigate the effectiveness of musical features of voice recordings on PD and healthy subject discrimination issue. Extracted number of 41 musical features from the voice recordings of 28 PD and 62 healthy controls are used in the context of music information retrieval. These features are employed in the classification models either as a single large set or partitioned into smaller feature groups. Leave-one-subject-out (LOSO), leave-one-out (LOO) and 10-fold cross validation schemes are used while training and testing in support vector machine (SVM) and k-nearest neighbors (k-NN) classifiers by providing statistical measures. The effect of low, normal and high tone voice recordings is also studied separately, and the results show that using low-tone voice recordings may not be useful for discrimination of dysphonic voice. Despite using least number of features of all related schemes which use raw voice recordings, our proposed musical features with LOSO cross validation technique perform better accuracy results than the existing studies.