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offers:diplomthemen [2020/07/15 12:56]
petra [Laufende Bachelorarbeiten]
offers:diplomthemen [2020/08/03 10:10] (current)
niemann [Masterthemen in Magdeburg]
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 |**Contact:** | [[uli.niemann@ovgu.de|Uli Niemann, M.Sc.]], [[sylvia@isg.cs.uni-magdeburg.de|Dr. Sylvia Saalfeld]] | |**Contact:** | [[uli.niemann@ovgu.de|Uli Niemann, M.Sc.]], [[sylvia@isg.cs.uni-magdeburg.de|Dr. Sylvia Saalfeld]] |
 |**Further infos:** | The topic is available as Bachelor's/Master's Thesis, but it can be converted into a student assistant job (//HiWi//). | |**Further infos:** | The topic is available as Bachelor's/Master's Thesis, but it can be converted into a student assistant job (//HiWi//). |
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-^Bachelor's/ Master's Thesis: Classification and Visualization of Plantar Pressure and Temperature Time-Series in Patients with Diabetic Foot Syndrome^^  
-|  {{:offers:diplomthemen:ba_diabetic_foot_syndrome.png? 120}}| Complications afflicted with the diabetic foot syndrome have a substantial impact on the patient’s life quality. The combination of vascular constrictions and nerve damages (neuropathy) leads to a disturbed pressure and pain perception. As a consequence, high local pressure strains remain unnoticed which lead to an impeded regional blood flow in the short term and tissue destructions and ulcerations in the long term. <html><br /></html> In collaboration with the university clinic Magdeburg, a study with a group of dia-betic patients with severe polyneuropathy and a group of healthy controls was conducted where pressure and temperature was collected with means of an “intelligent” shoe insole. The insole is equipped with multiple sensors which gather pressure and temperature signals and transfer them via Bluetooth to a dedicated smartphone app for further analysis. One of the goals is the timely detection of emerging foot ulcerations which is characterized by a significant temperature in-crease of affected regions. <html><br /></html> The goal of the project is the classification of pressure and temperature time series to distinguish between neuropathic diabetics and healthy controls. For example, we want to study whether disease-specific patterns in the run of the time series can be detected. Predictive features and time-series segments (motifs) should be illustrated by suitable visualizations which can be directly used by the clinical partners. |  
-|**Prerequisites:**| Experience with R (preferred), Python or MATLAB; working knowledge of data mining | 
-|**Further Information:**|{{:offers:diplomthemen:ba_diabetic_foot_syndrome.pdf|Flyer (in German and English)}}| 
-|**Contact:** | [[uli.niemann@isg.cs.uni-magdeburg.de|Uli Niemann, M.Sc.]]| 
  
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