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Design of a Low Complexity PPG-based Real-time PVCs Detection System
Premature Ventricular Contraction (PVC)
Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC)
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本論文提出一個低複雜度即時心室早期收縮的偵測系統，分成峰值與心室早期收縮異常訊號偵測兩部份來探討。峰值偵測採用So and Chan方法來偵測脈衝波峰，並分析波峰之間的時間差與心率變異度來做為心室早期收縮的特徵判斷條件。
模擬與驗證採用MIT-BIH MIMIC Database (mimic)所提供的PPG資料。 Improved So and Chan方法可有效降低波峰的偵測錯誤，將原來So and Chan方法用於光學式心跳量測訊號。而心室性早期收縮偵測方法可由特徵值辨識出，偵測正確率可達70%，並在發生心室性早期時發出訊息給使用者。由於演算法複雜度低，可達到即時偵測，適合整合於穿戴式電子產品上。|
Heart disease is one of the main causes of death in our country. Even though Patients with the chronic cardiovascular disease can be detected by the Electrocardiogram (ECG) instruments in the hospital, the acute heart disease, such as premature ventricular contractions (PVCs), is still difficult to be found. However, it is of great help for patients to have a wearable device detecting the signal and sending the warnings in advance. In general ECG checking, the doctor may accurately determine the heart disease based on the standard 12-lead electrocardiogram. Unfortunately, not many instruments on the market support ECG that can diagnose the cardiovascular disease. Optical heartbeat measurement in recent years has become the best way to replace the ECG system. Optical instruments provide more advanced measurements in determining physiological symptoms like heart rate, blood oxygen, fatigue, and even blood pressure. The optical heartbeat measurement can be relatively simple whereas ECG performs much more accurate in the fields of pathological features by means of the plethysmograph. Once the optical heartbeat measurement can easily detect premature ventricular contractions, it will benefit the patients with possible cardiovascular and help improve the quality of life for the patients. This dissertation presents a low-complexity real-time PVCs detection system which is divided into two parts: to detect the peak and to investigate early ventricular systolic abnormalities. Peak detection was performed with the So and Chan method, peak to peak interval analysis and heart rate variability were implemented as a characteristic condition for PVCs. Simulation and verification using the plethysmograph data which were provided by MIT-BIH Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC) database. So and Chan is utilized for optical heartbeat measurement signal while the Improved So and Chan method can effectively reduce the error of detecting crest. PVCs detection method can be identified by the eigenvalue, and the correct rate of detection is up to 70%. Besides, the system can send a message to the user in the early ventricular onset. With low-complexity, real-time detection of the algorithm can be achieved. The system is suitable for integration into the wearable devices.
|Appears in Collections:||電機工程學系所|
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