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In this paper, a novel method to detect atrial fibrillation (AFib) from a seismocardiogram (SCG) is presented. The proposed method is based on linear classification of the spectral entropy and a heart rate variability index computed from the SCG. The performance of the developed algorithm is demonstrated on data gathered from 13 patients in clinical setting. After motion artifact removal, in total...
A wireless multisensor platform for monitoring human's cardiovascular system is presented. The designed sensor node incorporates front-ends for an ECG, an accelerometer and a pressure sensor. The system architecture builds on an openMSP430 processor. The main application for the designed System on Chip (SoC) is the detection of atrial fibrillation (AF). To this end, a dedicated hardware accelerator...
Present a low power, miniaturized biomedical sensor node featuring electro-, seismo-and gyrocardiography. Measurement session can be set up and controlled over Bluetooth Low Energy interface. Acquired raw or preprocessed sensor data can be stored locally to the microSD memory card. To the best of the authors' knowledge, the presented device is the smallest reported to enable heart monitoring from...
In this paper we study the feasibility of seismocardiography (SCG) for the detection of Atrial Fibrillation (AF). In this preclinical study, data acquired from one patient having paroxysmal AF (no other heart diseases) is used to introduce specific changes in SCG signal due to AF. Observed changes and phenomena create a foundation for the development of SCG-based AF detection algorithms. SCG data...
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