Abstract
Measuring cardiac activity from the chest using an accelerometer is commonly referred to as seismocardiography. Unfortunately, it cannot provide clinically valid data because it is easily corrupted by motion artefacts. This paper proposes two methods to improve peak detection from noisy seismocardiography data. They rely on discrete wavelet transform analysis using either biorthogonal 3.9 or reverse biorthogonal 3.9. The first method involves slicing chest vibrations for each cardiac activity, and then detecting the peak location, whereas the other method aims at detecting the peak directly from chest vibrations without segmentation. Performance evaluations were conducted on signals recorded from small children and adults based on missing and additional peaks. Both algorithms showed a low error rate (15.4% and 2.1% for children/infants and adults, respectively) for signals obtained in resting state. The average error for sitting and breathing tasks (adults only) was 14.4%. In summary, the first algorithm proved more promising for further exploration.
Highlights
IntroductionMeasuring cardiac activity from the chest using an accelerometer is commonly referred to as seismocardiography
Research Unit of Medical Imaging, Physics, and Technology, Oulu University, 90100 Oulu, Finland; Department of Electrical Engineering, Petra Christian University, Surabaya 60236, Indonesia
Two algorithms were proposed and evaluated to detect the peak of chest vibration measured by an accelerometer without ECG signals for real-time application
Summary
Measuring cardiac activity from the chest using an accelerometer is commonly referred to as seismocardiography. Performance evaluations were conducted on signals recorded from small children and adults based on missing and additional peaks Both algorithms showed a low error rate (15.4% and 2.1% for children/infants and adults, respectively) for signals obtained in resting state. Each beat consists of two sounds, S1 and S2, and various algorithms have been developed to analyze them Another non-invasive method is measuring the electrical activity of the heart, resulting in an electrocardiogram (ECG). In this technique, electrodes are placed around the chest and other anatomically specified parts of the body. ECG signals allow the study of heart rate variability (HRV), which represents variation in inter-beat intervals
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