Diagnosis of Heart Failure using High Quality Ballistocardiography and Respiratory Effort Signals: A Pilot Study

Abstract

Purpose: To enable the in-home diagnosis of heart failure (HF) based on morphological features of high quality ballistocardiography (BCG) signals and respiratory effort. Methods: Non-contact vital signs including BCG and respiratory effort signals from 25 subjects (11 HF, 14 non-heart failure (Non-HF)) were collected using a force sensor-based medical equipment. By assessing the recorded BCG signals w.r.t signal quality indexes, a steady-state BCG template is modeled by using consecutive high quality BCG signals, from which morphological features including the amplitude, time, area and energy features of signal wave groups are extracted to distinguish the HF and Non-HF subjects. Results: It is validated that a total 13 morphological features of BCG and respiratory effort signals showed differences between HF and Non-HF subjects. Using typical classifiers for discriminating HF and Non-HF subjects yields the accuracy, sensitivity and specificity of 92%, 80% and 100%. Conclusion: The acquisition and analysis of high quality BCG signals has the potential of identifying HF disease.