Literature DB >> 30441193

Using Moving Average Method to Recognize Systole and Diastole on Seismocardiogram without ECG Signal.

Loc Luu, Anh Dinh.   

Abstract

Seismocardiogram (SCG) is a cardio-mechanical signal generated by the heart activities and it can be obtained by placing an accelerometer on the chest. Recently, SCG was used to estimate heart operation by evaluating systolic and diastolic events but the SCG must be coupled to the ECG timing in order to analyze and recognize the events on the SCG waveform. In this study, a low complex algorithm is proposed to identify the regions containing systolic and diastolic points in real time without referencing to the ECG. The method uses the slope, a moving average threshold, and systolic interval constraint to identify the systoles and diastoles. The ECG signal was also collected for manual annotation and comparison. This moving average method has an average error rate of 4% for systolic detection and 9% for diastolic detection on the eight testing subjects. The average processing time of the moving average method is 75.2ms for one-minute data which is suitable for realtime wearable device for healthcare applications.

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Year:  2018        PMID: 30441193     DOI: 10.1109/EMBC.2018.8513297

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  1 in total

1.  Adaptive-Cognitive Kalman Filter and Neural Network for an Upgraded Nondispersive Thermopile Device to Detect and Analyze Fusarium Spores.

Authors:  Son Pham; Anh Dinh
Journal:  Sensors (Basel)       Date:  2019-11-09       Impact factor: 3.576

  1 in total

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