TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Awonuga, Oluwaseun
A1  - Gaiduk, Maksym
A1  - Martínez Madrid, Natividad
A1  - Seepold, Ralf
A1  - Haghi, Mostafa
T1  - Comparative Study of Applying Signal Processing Techniques on Ballistocardiogram in Detecting J-Peak using Bi-LSTM Model
JF  - Models and Applications for Embedded Systems
N2  - Cardiovascular diseases (CVD) are leading contributors to global mortality, necessitating advanced methods for vital sign monitoring. Heart Rate Variability (HRV) and Respiratory Rate, key indicators of cardiovascular health, are traditionally monitored via Electrocardiogram (ECG). However, ECG's obtrusiveness limits its practicality, prompting the exploration of Ballistocardiography (BCG) as a non-invasive alternative. BCG records the mechanical activity of the body with each heartbeat, offering a contactless method for HRV monitoring. Despite its benefits, BCG signals are susceptible to external interference and present a challenge in accurately detecting J-Peaks. This research uses advanced signal processing and deep learning techniques to overcome these limitations. Our approach integrates accelerometers for long-term BCG data collection during sleep, applying Discrete Wavelet Transforms (DWT) and Ensemble Empirical Mode Decomposition (EEMD) for feature extraction. The Bi-LSTM model, leveraging these features, enhances heartbeat detection, offering improved reliability over traditional methods. The study's findings indicate that the combined use of DWT, EEMD, and Bi-LSTM for J-Peak detection in BCG signals is effective, with potential applications in unobtrusive long-term cardiovascular monitoring. Our results suggest that this methodology could contribute to HRV monitoring, particularly in home settings, enhancing patient comfort and compliance.
KW  - Signal processing
KW  - J-Peak
KW  - Bi-LSTM Model
Y1  - 2023
UR  - www.dii.univpm.it/MAES-2023
SN  - 978-88-87548-00-6
SB  - 978-88-87548-00-6
SP  - 23
EP  - 30
PB  - Università Politecnica delle Marche, Dipartimento di Ingegneria dell’Informazione
CY  - Ancona, Italy
ER  -