Computer-aided detection systems based on ballistocardiography signals: A review

This comprehensive review paper seeks to provide an in-depth survey of the technologies and methodologies employed in decision support systems for ballistocardiography. The paper extensively covers the biometric information embedded in the measured ballistocardiography signals. The presented exploration of ballistocardiography covers various pivotal stages, including signal measurement techniques, pre-processing methodologies, feature extraction approaches, classification techniques, and evaluation methods. Within the scope of this study, a systematic review has been performed, bringing together notable strategies employed in ballistocardiography from its initial stages to its current state of advancement. The efficacy of these systems in estimating ballistocardiography-based biometrics has demonstrated noteworthy proximity to acceptable levels. The utilization of ballistocardiography signals holds significant promise as an evolving field of research. This paper concludes by addressing the limitations inherent in the current state of research, outlining the potential directions for future investigations and real-world applications, and discussing the crucial aspect of explainability, which represents one of the new trends in computer-aided detection requirements.