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Feature Extraction for the Cardiovascular Disease Diagnosis
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Avdelningen för informationssystem och -teknologi.
2018 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

Cardiovascular disease is a serious life-threatening disease. It can occur suddenly and progresses rapidly. Finding the right disease features in the early stage is important to decrease the number of deaths and to make sure that the patient can fully recover. Though there are several methods of examination, describing heart activities in signal form is the most cost-effective way. In this case, ECG is the best choice because it can record heart activity in signal form and it is safer, faster and more convenient than other methods of examination. However, there are still problems involved in the ECG. For example, not all the ECG features are clear and easily understood. In addition, the frequency features are not present in the traditional ECG. To solve these problems, the project uses the optimized CWT algorithm to transform data from the time domain into the time-frequency domain. The result is evaluated by three data mining algorithms with different mechanisms. The evaluation proves that the features in the ECG are successfully extracted and important diagnostic information in the ECG is preserved. A user interface is designed increasing efficiency, which facilitates the implementation.

sted, utgiver, år, opplag, sider
2018. , s. 69
Emneord [en]
ECG, Feature Extraction, CWT, Unsupervised Learning, Clustering, User interface, Feature Visualization, ECG Disease Diagnosis.
HSV kategori
Identifikatorer
URN: urn:nbn:se:miun:diva-33742Lokal ID: DT-H16-A2-003OAI: oai:DiVA.org:miun-33742DiVA, id: diva2:1216642
Fag / kurs
Computer Engineering DT1
Utdanningsprogram
International Master's Programme in Computer Engineering TDAAA 120 higher education credits
Veileder
Examiner
Tilgjengelig fra: 2018-06-12 Laget: 2018-06-12 Sist oppdatert: 2018-06-12bibliografisk kontrollert

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