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DC Field | Value | Language |
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dc.contributor.author | PRAYOGA, Yudhistira Aji | - |
dc.date.accessioned | 2024-06-10T04:03:19Z | - |
dc.date.available | 2024-06-10T04:03:19Z | - |
dc.date.issued | 2024-03-18 | - |
dc.identifier.nim | 201810201032 | en_US |
dc.identifier.uri | https://repository.unej.ac.id/xmlui/handle/123456789/121268 | - |
dc.description.abstract | Abnormalities in the heart’s beating are called arrhythmias. Arrhythmias are divided based on the resulting heart rhythm, namely bradycardia which has less than 60 beats per minute and tachycardia which has more than 100 beats per minute. The estimated number of people with arrhythmias increasing age in the elderly population, around 11,39% or 28 million people in Indonesia in 2020. Heartbeat can be detected using PPG (Photoplethysmography) by measuring change in blood volume in the finger based on the signal systole point. The usual measurement is to measure based on the systole point of the time domain PPG signal alone without analyzing in more depth the inconsistent PPG signal beteen systole points. This study tries to analyze the heartbeat of 3 types of patients, namely normal, tachycardia, and bradycardia using the time domain and frequency domain. Time domain analysis was carried out with frequency distribution based on the period between systole points compared with other types of patients. The frequency distribution between systole points is expressed in a histogram and compared using euclidean distance. The results obtained were that the euclidean distance value had a higher value in the comparison of normal patients and arrhthmic patients than in the comparison of normal patients with normal patients. The frequency distribution in bradycardia and tachycardia patients is wider than normal. The features taken from the histogram are the frequency mode and the number of bins which will be separated using a support vector machinee. The accuracy obtained is above 90% because the classes are well divided. Frequency domain analysis is with STFT (Short Time Fourier Transform). The values that are varied are the window length and the frequency distribution obtained compared to the time domain signal. The smallest and most consistent euclidean distance value was obtained in a window length of | en_US |
dc.language.iso | other | en_US |
dc.publisher | MIPA | en_US |
dc.subject | Euclidean Distance | en_US |
dc.subject | Frequency Domain Analysis (FDA) | en_US |
dc.subject | Support Vector Machine (SVM) | en_US |
dc.subject | Time Domain Analysis (TDA). | en_US |
dc.title | Bradycardia and Tachycardia Detection System From PPG (Photoplethysmograph) Signal With TDA (Time Domain Analysis) and FDA (Frequency Domain Analysis) | en_US |
dc.type | Other | en_US |
dc.identifier.prodi | Fisika | en_US |
dc.identifier.pembimbing1 | Bowo Eko Cahyono, S.Si., M.Si., Ph.D | en_US |
dc.identifier.pembimbing2 | Prof.Nuryani S.Si., M.Si., Ph.D | en_US |
dc.identifier.validator | validasi_repo_iswahyudi_Mei_2024 | en_US |
dc.identifier.finalization | 0a67b73d_2024_06_tanggal 10 | en_US |
Appears in Collections: | UT-Faculty of Mathematics and Natural Sciences |
Files in This Item:
File | Description | Size | Format | |
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[Draft] Skripsi_Yudhistira Aji Prayoga_201810201032.pdf Until 2028-04-11 | 2.29 MB | Adobe PDF | View/Open Request a copy |
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