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

Seismocardiography (SCG), a method for measuring heart-induced chest vibrations, is gaining attention as a non-invasive, accessible, and cost-effective approach for cardiac pathologies, diagnosis, and monitoring. This study explores the integration of SCG acquired through smartphone technology by assessing the accuracy of metrics derived from smartphone recordings and their consistency when performed by patients. Therefore, we assessed smartphone-derived SCG's reliability in computing median kinetic energy parameters per record in 220 patients with various cardiovascular conditions. The study involved three key procedures: (1) simultaneous measurements of a validated hardware device and a commercial smartphone; (2) consecutive smartphone recordings performed by both clinicians and patients; (3) patients' self-conducted home recordings over three months. Our findings indicate a moderate-to-high reliability of smartphone-acquired SCG metrics compared to those obtained from a validated device, with intraclass correlation (ICC) > 0.77. The reliability of patient-acquired SCG metrics was high (ICC > 0.83). Within the cohort, 138 patients had smartphones that met the compatibility criteria for the study, with an observed at-home compliance rate of 41.4%. This research validates the potential of smartphone-derived SCG acquisition in providing repeatable SCG metrics in telemedicine, thus laying a foundation for future studies to enhance the precision of at-home cardiac data acquisition.

The kinocardiograph for assessment of fluid status in patients with acute decompensated heart failure

AIMS

To improve telemonitoring strategies in heart failure patients, there is a need for novel non-obtrusive sensors that monitor parameters closely related to intracardiac filling pressures. This proof-of-concept study aims to evaluate the responsiveness of cardiac kinetic energy (KE) measured with the Kinocardiograph (KCG), consisting of a seismocardiographic (SCG) sensor and a ballistocardiographic (BCG) sensor, during treatment of patients with acute decompensated heart failure.

METHODS AND RESULTS

Eleven patients with acute decompensated heart failure who were hospitalized for treatment with intravenous diuretics received daily KCG measurements. The KCG measurements were compared with the diameter of the inferior vena cava (IVC) and body weight. Follow-up stopped at discharge, that is, in the recompensated state. Median (interquartile range) weight and IVC diameter decreased significantly after diuretic treatment [weight 74.5 (67.6-98.7) to 73.3 (66.7-95.6) kg, P = 0.003; IVC diameter 2.47 (2.33-2.99) to 1.78 (1.65-2.47) cm, P = 0.03]. In contrast with BCG measurements, significant changes in median KE measured with SCG were observed during the passive filling phase of the diastole [SGG: 0.48 (0.39-0.60) to 0.69 (0.56-0.84), P = 0.026; BCG: 0.68 (0.46-0.73) to 0.68 (0.59-0.82), P = 0.062], the active filling phase of the diastole [SCG: 0.38 (0.30-0.61) to 0.31 (0.09-0.47), P = 0.016; BCG: 0.29 (0.17-0.39) to 0.26 (0.20-0.34), P = 0.248], and the ratio between the passive and active filling phases [SCG: 2.76 (1.68-5.30) to 5.02 (3.13-10.17), P = 0.006; BCG: 5.87 (3.57-7.55) to 5.27 (3.95-9.43), P = 0.790]. The correlations between changes in KE during the passive and active filling phases, using SCG, and changes in weight or IVC were non-significant. Systolic KE did not show significant changes.

CONCLUSION

KE measured with the KCG using SCG is highly responsive to changes in fluid status. Future research is needed to confirm its accuracy in a larger study population and specifically its application for detection of clinical deterioration in the home-environment.

Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography-A Narrative Review

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.