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Hossein A, Abdessater E, Balali P, Cosneau E, Gorlier D, Rabineau J, Almorad A, Faoro V, van de Borne P. Smartphone-Derived Seismocardiography: Robust Approach for Accurate Cardiac Energy Assessment in Patients with Various Cardiovascular Conditions. SENSORS (BASEL, SWITZERLAND) 2024; 24:2139. [PMID: 38610349 PMCID: PMC11014030 DOI: 10.3390/s24072139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/19/2024] [Accepted: 03/25/2024] [Indexed: 04/14/2024]
Abstract
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.
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Affiliation(s)
- Amin Hossein
- Laboratory of Physics and Physiology, Université Libre de Bruxelles, 1050 Brussels, Belgium
- Cardio-Pulmonary Exercise Laboratory, Faculty of Motor Sciences, Université Libre de Bruxelles, Erasme Campus, Anderlecht, 1070 Brussels, Belgium
| | - Elza Abdessater
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, 1050 Bruxelles, Belgium
| | - Paniz Balali
- Laboratory of Physics and Physiology, Université Libre de Bruxelles, 1050 Brussels, Belgium
| | | | | | - Jérémy Rabineau
- Laboratory of Physics and Physiology, Université Libre de Bruxelles, 1050 Brussels, Belgium
| | - Alexandre Almorad
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, 1050 Brussels, Belgium
| | - Vitalie Faoro
- Cardio-Pulmonary Exercise Laboratory, Faculty of Motor Sciences, Université Libre de Bruxelles, Erasme Campus, Anderlecht, 1070 Brussels, Belgium
| | - Philippe van de Borne
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, 1050 Bruxelles, Belgium
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Herkert C, De Lathauwer I, van Leunen M, Spee RF, Balali P, Migeotte P, Hossein A, Lu Y, Kemps HMC. The kinocardiograph for assessment of fluid status in patients with acute decompensated heart failure. ESC Heart Fail 2023; 10:3446-3453. [PMID: 37710415 PMCID: PMC10682902 DOI: 10.1002/ehf2.14477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 06/28/2023] [Accepted: 07/04/2023] [Indexed: 09/16/2023] Open
Abstract
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.
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Affiliation(s)
- Cyrille Herkert
- Department of CardiologyMáxima Medical CentreEindhovenThe Netherlands
| | | | - Mayke van Leunen
- Department of CardiologyMáxima Medical CentreEindhovenThe Netherlands
| | | | - Paniz Balali
- LPHYSUniversité Libre de BruxellesBrusselsBelgium
| | | | - Amin Hossein
- LPHYSUniversité Libre de BruxellesBrusselsBelgium
| | - Yuan Lu
- Department of Industrial DesignEindhoven University of TechnologyEindhovenThe Netherlands
| | - Hareld Marijn Clemens Kemps
- Department of CardiologyMáxima Medical CentreEindhovenThe Netherlands
- Department of Industrial DesignEindhoven University of TechnologyEindhovenThe Netherlands
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Al Younis SM, Hadjileontiadis LJ, Stefanini C, Khandoker AH. Non-invasive technologies for heart failure, systolic and diastolic dysfunction modeling: a scoping review. Front Bioeng Biotechnol 2023; 11:1261022. [PMID: 37920244 PMCID: PMC10619666 DOI: 10.3389/fbioe.2023.1261022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 10/09/2023] [Indexed: 11/04/2023] Open
Abstract
The growing global prevalence of heart failure (HF) necessitates innovative methods for early diagnosis and classification of myocardial dysfunction. In recent decades, non-invasive sensor-based technologies have significantly advanced cardiac care. These technologies ease research, aid in early detection, confirm hemodynamic parameters, and support clinical decision-making for assessing myocardial performance. This discussion explores validated enhancements, challenges, and future trends in heart failure and dysfunction modeling, all grounded in the use of non-invasive sensing technologies. This synthesis of methodologies addresses real-world complexities and predicts transformative shifts in cardiac assessment. A comprehensive search was performed across five databases, including PubMed, Web of Science, Scopus, IEEE Xplore, and Google Scholar, to find articles published between 2009 and March 2023. The aim was to identify research projects displaying excellence in quality assessment of their proposed methodologies, achieved through a comparative criteria-based rating approach. The intention was to pinpoint distinctive features that differentiate these projects from others with comparable objectives. The techniques identified for the diagnosis, classification, and characterization of heart failure, systolic and diastolic dysfunction encompass two primary categories. The first involves indirect interaction with the patient, such as ballistocardiogram (BCG), impedance cardiography (ICG), photoplethysmography (PPG), and electrocardiogram (ECG). These methods translate or convey the effects of myocardial activity. The second category comprises non-contact sensing setups like cardiac simulators based on imaging tools, where the manifestations of myocardial performance propagate through a medium. Contemporary non-invasive sensor-based methodologies are primarily tailored for home, remote, and continuous monitoring of myocardial performance. These techniques leverage machine learning approaches, proving encouraging outcomes. Evaluation of algorithms is centered on how clinical endpoints are selected, showing promising progress in assessing these approaches' efficacy.
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Affiliation(s)
- Sona M. Al Younis
- Department of Biomedical Engineering, Healthcare Engineering Innovation Center (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
| | - Leontios J. Hadjileontiadis
- Department of Biomedical Engineering, Healthcare Engineering Innovation Center (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
| | - Cesare Stefanini
- Creative Engineering Design Lab at the BioRobotics Institute, Applied Experimental Sciences Scuola Superiore Sant'Anna, Pontedera (Pisa), Italy
| | - Ahsan H. Khandoker
- Department of Biomedical Engineering, Healthcare Engineering Innovation Center (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
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De Keyzer E, Hossein A, Rabineau J, Morissens M, Almorad A, van de Borne P. Non-invasive cardiac kinetic energy distribution: a new marker of heart failure with impaired ejection fraction (KINO-HF). Front Cardiovasc Med 2023; 10:1096859. [PMID: 37200972 PMCID: PMC10185762 DOI: 10.3389/fcvm.2023.1096859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 04/10/2023] [Indexed: 05/20/2023] Open
Abstract
Background Heart failure (HF) remains a major cause of mortality, morbidity, and poor quality of life. 44% of HF patients present impaired left ventricular ejection fraction (LVEF). Kinocardiography (KCG) technology combines ballistocardiography (BCG) and seismocardiography (SCG). It estimates myocardial contraction and blood flow through the cardiac chambers and major vessels through a wearable device. Kino-HF sought to evaluate the potential of KCG to distinguish HF patients with impaired LVEF from a control group. Methods Successive patients with HF and impaired LVEF (iLVEF group) were matched and compared to patients with normal LVEF ≥ 50% (control). A 60 s KCG acquisition followed cardiac ultrasound. The kinetic energy from KCG signals was computed in different phases of the cardiac cycle (i K s y s t o l i c ; Δ i K d i a s t o l i c ) as markers of cardiac mechanical function. Results Thirty HF patients (67 [59; 71] years, 87% male) were matched with 30 controls (64.5 [49; 73] years, 87% male). SCG Δ i K d i a s t o l i c , BCG i K s y s t o l i c , BCG Δ i K d i a s t o l i c were lower in HF than controls (p < 0.05), while SCG i K s y s t o l i c was similar. Furthermore, a lower SCG i K s y s t o l i c was associated with an increased mortality risk during follow-up. Conclusions KINO-HF demonstrates that KCG can distinguish HF patients with impaired systolic function from a control group. These favorable results warrant further research on the diagnostic and prognostic capabilities of KCG in HF with impaired LVEF.Clinical Trial Registration: NCT03157115.
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Affiliation(s)
- Eva De Keyzer
- Department of Cardiology, Brugmann Hospital, Université Libre de Bruxelles, Brussels, Belgium
| | - Amin Hossein
- Laboratoray of Physics and Physiology, Université Libre de Bruxelles, Brussels, Belgium
| | - Jeremy Rabineau
- Laboratoray of Physics and Physiology, Université Libre de Bruxelles, Brussels, Belgium
| | - Marielle Morissens
- Department of Cardiology, Brugmann Hospital, Université Libre de Bruxelles, Brussels, Belgium
| | - Alexandre Almorad
- Department of Cardiology, Brugmann Hospital, Université Libre de Bruxelles, Brussels, Belgium
- Heart Rhythm Management Centre, European Reference Networks Guard-Heart, Universitair Ziekenhuis Brussel - Vrije Universiteit Brussel, Brussels, Belgium
| | - Philippe van de Borne
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Brussels, Belgium
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Ganti VG, Gazi AH, An S, Srivatsa AV, Nevius BN, Nichols CJ, Carek AM, Fares M, Abdulkarim M, Hussain T, Greil FG, Etemadi M, Inan OT, Tandon A. Wearable Seismocardiography‐Based Assessment of Stroke Volume in Congenital Heart Disease. J Am Heart Assoc 2022; 11:e026067. [DOI: 10.1161/jaha.122.026067] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background
Patients with congenital heart disease (CHD) are at risk for the development of low cardiac output and other physiologic derangements, which could be detected early through continuous stroke volume (SV) measurement. Unfortunately, existing SV measurement methods are limited in the clinic because of their invasiveness (eg, thermodilution), location (eg, cardiac magnetic resonance imaging), or unreliability (eg, bioimpedance). Multimodal wearable sensing, leveraging the seismocardiogram, a sternal vibration signal associated with cardiomechanical activity, offers a means to monitoring SV conveniently, affordably, and continuously. However, it has not been evaluated in a population with significant anatomical and physiological differences (ie, children with CHD) or compared against a true gold standard (ie, cardiac magnetic resonance). Here, we present the feasibility of wearable estimation of SV in a diverse CHD population (N=45 patients).
Methods and Results
We used our chest‐worn wearable biosensor to measure baseline ECG and seismocardiogram signals from patients with CHD before and after their routine cardiovascular magnetic resonance imaging, and derived features from the measured signals, predominantly systolic time intervals, to estimate SV using ridge regression. Wearable signal features achieved acceptable SV estimation (28% error with respect to cardiovascular magnetic resonance imaging) in a held‐out test set, per cardiac output measurement guidelines, with a root‐mean‐square error of 11.48 mL and
R
2
of 0.76. Additionally, we observed that using a combination of electrical and cardiomechanical features surpassed the performance of either modality alone.
Conclusions
A convenient wearable biosensor that estimates SV enables remote monitoring of cardiac function and may potentially help identify decompensation in patients with CHD.
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Affiliation(s)
- Venu G. Ganti
- Bioengineering Graduate Program Georgia Institute of Technology Atlanta GA
| | - Asim H. Gazi
- School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA
| | - Sungtae An
- School of Interactive Computing Georgia Institute of Technology Atlanta GA
| | - Adith V. Srivatsa
- The Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology Atlanta GA
| | - Brandi N. Nevius
- School of Mechanical Engineering Georgia Institute of Technology Atlanta GA
| | - Christopher J. Nichols
- The Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology Atlanta GA
| | - Andrew M. Carek
- Department of Biomedical Engineering, McCormick School of Engineering Northwestern University Evanston IL
- Department of Anesthesiology, Feinberg School of Medicine Northwestern University Evanston IL
| | - Munes Fares
- Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX
| | - Mubeena Abdulkarim
- Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX
| | - Tarique Hussain
- Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX
| | - F. Gerald Greil
- Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX
| | - Mozziyar Etemadi
- Department of Biomedical Engineering, McCormick School of Engineering Northwestern University Evanston IL
- Department of Anesthesiology, Feinberg School of Medicine Northwestern University Evanston IL
| | - Omer T. Inan
- Bioengineering Graduate Program Georgia Institute of Technology Atlanta GA
- School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA
| | - Animesh Tandon
- Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX
- Cleveland Clinic Children’s Cleveland OH
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