Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography—A Narrative Review

Abstract

Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activity at the body’s center of mass and on the chest, respectively. Since their inception, their potential for evaluating cardiovascular health has been studied. However, both BCG and SCG are impacted by respiration, leading to a periodic modulation of these signals. As a result, data processing algorithms have been developed to exclude the respiratory signals, or recording protocols have been designed to limit the respiratory bias. Reviewing the present status of the literature reveals an increasing interest in applying these techniques to extract respiratory information, as well as cardiac information. The possibility of simultaneous monitoring of respiratory and cardiovascular signals via BCG or SCG enables the monitoring of vital signs during activities that require considerable mental concentration, in extreme environments, or during sleep, where data acquisition must occur without introducing recording bias due to irritating monitoring equipment. This work aims to provide a theoretical and practical overview of cardiopulmonary interaction based on BCG and SCG signals. It covers the recent improvements in extracting respiratory signals, computing markers of the cardiorespiratory interaction with practical applications, and investigating sleep breathing disorders, as well as a comparison of different sensors used for these applications. According to the results of this review, recent studies have mainly concentrated on a few domains, especially sleep studies and heart rate variability computation. Even in those instances, the study population is not always large or diversified. Furthermore, BCG and SCG are prone to movement artifacts and are relatively subject dependent. However, the growing tendency toward artificial intelligence may help achieve a more accurate and efficient diagnosis. These encouraging results bring hope that, in the near future, such compact, lightweight BCG and SCG devices will offer a good proxy for the gold standard methods for assessing cardiorespiratory function, with the added benefit of being able to perform measurements in real-world situations, outside of the clinic, and thus decrease costs and time.

Non-invasive cardiac kinetic energy distribution: a new marker of heart failure with impaired ejection fraction (KINO-HF)

“…More recently, these techniques have been used in domains such as atrial fibrillation ( 10 ) and hypertension detection ( 11 ), heart failure monitoring ( 12 , 13 ), cardiorespiratory fitness assessment ( 14 , 15 ), and many others. Recent advances in the field of SCG were published by Taebi et al ( 16 ).…”

Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies

“…Subsequent researchers, such as Henderson [63], Heald and Tucker [64], Starr and Krumbhaar [65], and Rubenstein [66], among others, have explored the influence of respiration on the BCG signal. Unlike SCG, micro-motion is not limited to the chest but extends to the entire body surface [67]. The BCG component also encompasses movement along all three axes and can be measured as acceleration, velocity, displacement, or force signal [53].…”

“…While the impact of respiration on ECG [68] has been extensively studied, research on the effects of respiration on SCG and BCG lags. According to a systematic review by Han et al [69], only a small percentage of studies focus on respiratory monitoring [67]. BCG is primarily influenced by cyclical changes in intrathoracic pressure resulting from pulmonary ventilation [18], serving as a source of respiratory-cardiovascular coupling [70].…”

“…The thoraco-abdominal respiratory pump, in turn, generates oscillations in venous return and left ventricular afterload, leading to arterial pressure oscillations [71][72][73], consequently triggering the baroreflex. Additionally, there is a direct interaction between the brainstem respiratory oscillator and cardiac vagal preganglionic neurons in the nucleus accumbens [67,70]. The latest literature reflecta a significant enthusiasm for employing these techniques in extracting respiratory data.…”

Smartphone-Derived Seismocardiography: Robust Approach for Accurate Cardiac Energy Assessment in Patients with Various Cardiovascular Conditions

“…As presented in the methods, the reliability of rotational kinetic energy was not investigated in the current work; therefore, the results obtained here are only relevant to linear kinetic energy. Previous studies [40,41] have established that respiration markedly influences the metrics obtained from SCG. However, this study did not investigate the repeatability of metrics derived from a specific respiration phase.…”