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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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Svensøy JN, Alonso E, Elola A, Bjørnerheim R, Ræder J, Aramendi E, Wik L. Cardiac output estimation using ballistocardiography: a feasibility study in healthy subjects. Sci Rep 2024; 14:1671. [PMID: 38238507 PMCID: PMC10796317 DOI: 10.1038/s41598-024-52300-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 01/16/2024] [Indexed: 01/22/2024] Open
Abstract
There is no reliable automated non-invasive solution for monitoring circulation and guiding treatment in prehospital emergency medicine. Cardiac output (CO) monitoring might provide a solution, but CO monitors are not feasible/practical in the prehospital setting. Non-invasive ballistocardiography (BCG) measures heart contractility and tracks CO changes. This study analyzed the feasibility of estimating CO using morphological features extracted from BCG signals. In 20 healthy subjects ECG, carotid/abdominal BCG, and invasive arterial blood pressure based CO were recorded. BCG signals were adaptively processed to isolate the circulatory component from carotid (CCc) and abdominal (CCa) BCG. Then, 66 features were computed on a beat-to-beat basis to characterize amplitude/duration/area/length of the fluctuation in CCc and CCa. Subjects' data were split into development set (75%) to select the best feature subset with which to build a machine learning model to estimate CO and validation set (25%) to evaluate model's performance. The model showed a mean absolute error, percentage error and 95% limits of agreement of 0.83 L/min, 30.2% and - 2.18-1.89 L/min respectively in the validation set. BCG showed potential to reliably estimate/track CO. This method is a promising first step towards an automated, non-invasive and reliable CO estimator that may be tested in prehospital emergencies.
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Affiliation(s)
- Johannes Nordsteien Svensøy
- Norwegian National Advisory Unit on Prehospital Emergency Medicine (NAKOS), Division of Prehospital Services, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Erik Alonso
- Department of Applied Mathematics, University of the Basque Country (UPV/EHU), Bilbao, Spain.
| | - Andoni Elola
- Department of Electronic Technology, University of the Basque Country (UPV/EHU), Eibar, Spain
| | - Reidar Bjørnerheim
- Division of Internal Medicine, Department of Cardiology, Ullevål Hospital, Oslo, Norway
| | - Johan Ræder
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Division of Emergency Medicine, Department of Anestesiology, Ullevål Hospital, Oslo, Norway
| | - Elisabete Aramendi
- Department of Communications Engineering, University of the Basque Country (UPV/EHU), Bilbao, Spain
| | - Lars Wik
- Norwegian National Advisory Unit on Prehospital Emergency Medicine (NAKOS), Division of Prehospital Services, Oslo University Hospital, Oslo, Norway
- Division of Prehospital Services, Department of Air Ambulance, Ullevål Hospital, Oslo, Norway
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Tokmak F, Koivisto T, Lahdenoja O, Vasankari T, Jaakkola S, Airaksinen KEJ. Mechanocardiography detects improvement of systolic function caused by resynchronization pacing. Physiol Meas 2023; 44:125009. [PMID: 38041869 DOI: 10.1088/1361-6579/ad1197] [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: 06/16/2023] [Accepted: 12/01/2023] [Indexed: 12/04/2023]
Abstract
Objective.Cardiac resynchronization therapy (CRT) is commonly used to manage heart failure with dyssynchronous ventricular contraction. CRT pacing resynchronizes the ventricular contraction, while AAI (single-chamber atrial) pacing does not affect the dyssynchronous function. This study compared waveform characteristics during CRT and AAI pacing at similar pacing rates using seismocardiogram (SCG) and gyrocardiogram (GCG), collectively known as mechanocardiogram (MCG).Approach.We included 10 patients with heart failure with reduced ejection fraction and previously implanted CRT pacemakers. ECG and MCG recordings were taken during AAI and CRT pacing at a heart rate of 80 bpm. Waveform characteristics, including energy, vertical range (amplitude) during systole and early diastole, electromechanical systole (QS2) and left ventricular ejection time (LVET), were derived by considering 6 MCG axes and 3 MCG vectors across frequency ranges of >1 Hz, 20-90 Hz, 6-90 Hz and 1-20 Hz.Main results.Significant differences were observed between CRT and AAI pacing. CRT pacing consistently exhibited higher energy and vertical range during systole compared to AAI pacing (p< 0.05). However, QS2, LVET and waveform characteristics around aortic valve closure did not differ between the pacing modes. Optimal differences were observed in SCG-Y, GCG-X, and GCG-Y axes within the frequency range of 6-90 Hz.Significance.The results demonstrate significant differences in MCG waveforms, reflecting improved mechanical cardiac function during CRT. This information has potential implications for predicting the clinical response to CRT. Further research is needed to explore the differences in signal characteristics between responders and non-responders to CRT.
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Affiliation(s)
- Fadime Tokmak
- Department of Computing, University of Turku, Vesilinnantie 5, FI-20500 Turku, Finland
| | - Tero Koivisto
- Department of Computing, University of Turku, Vesilinnantie 5, FI-20500 Turku, Finland
| | - Olli Lahdenoja
- Department of Computing, University of Turku, Vesilinnantie 5, FI-20500 Turku, Finland
| | - Tuija Vasankari
- Heart Center, Turku University Hospital, Hämeentie 11, FI-20520 Turku, Finland
| | - Samuli Jaakkola
- Heart Center, Turku University Hospital, Hämeentie 11, FI-20520 Turku, Finland
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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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Parlato S, Centracchio J, Esposito D, Bifulco P, Andreozzi E. ECG-Free Heartbeat Detection in Seismocardiography and Gyrocardiography Signals Provides Acceptable Heart Rate Variability Indices in Healthy and Pathological Subjects. SENSORS (BASEL, SWITZERLAND) 2023; 23:8114. [PMID: 37836942 PMCID: PMC10575135 DOI: 10.3390/s23198114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 09/12/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023]
Abstract
Cardio-mechanical monitoring techniques, such as Seismocardiography (SCG) and Gyrocardiography (GCG), have received an ever-growing interest in recent years as potential alternatives to Electrocardiography (ECG) for heart rate monitoring. Wearable SCG and GCG devices based on lightweight accelerometers and gyroscopes are particularly appealing for continuous, long-term monitoring of heart rate and its variability (HRV). Heartbeat detection in cardio-mechanical signals is usually performed with the support of a concurrent ECG lead, which, however, limits their applicability in standalone cardio-mechanical monitoring applications. The complex and variable morphology of SCG and GCG signals makes the ECG-free heartbeat detection task quite challenging; therefore, only a few methods have been proposed. Very recently, a template matching method based on normalized cross-correlation (NCC) has been demonstrated to provide very accurate detection of heartbeats and estimation of inter-beat intervals in SCG and GCG signals of pathological subjects. In this study, the accuracy of HRV indices obtained with this template matching method is evaluated by comparison with ECG. Tests were performed on two public datasets of SCG and GCG signals from healthy and pathological subjects. Linear regression, correlation, and Bland-Altman analyses were carried out to evaluate the agreement of 24 HRV indices obtained from SCG and GCG signals with those obtained from ECG signals, simultaneously acquired from the same subjects. The results of this study show that the NCC-based template matching method allowed estimating HRV indices from SCG and GCG signals of healthy subjects with acceptable accuracy. On healthy subjects, the relative errors on time-domain indices ranged from 0.25% to 15%, on frequency-domain indices ranged from 10% to 20%, and on non-linear indices were within 8%. The estimates obtained on signals from pathological subjects were affected by larger errors. Overall, GCG provided slightly better performances as compared to SCG, both on healthy and pathological subjects. These findings provide, for the first time, clear evidence that monitoring HRV via SCG and GCG sensors without concurrent ECG is feasible with the NCC-based template matching method for heartbeat detection.
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Affiliation(s)
| | - Jessica Centracchio
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy; (S.P.); (D.E.); (P.B.)
| | | | | | - Emilio Andreozzi
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy; (S.P.); (D.E.); (P.B.)
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Parlato S, Centracchio J, Esposito D, Bifulco P, Andreozzi E. Heartbeat Detection in Gyrocardiography Signals without Concurrent ECG Tracings. SENSORS (BASEL, SWITZERLAND) 2023; 23:6200. [PMID: 37448046 DOI: 10.3390/s23136200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 06/29/2023] [Accepted: 07/03/2023] [Indexed: 07/15/2023]
Abstract
A heartbeat generates tiny mechanical vibrations, mainly due to the opening and closing of heart valves. These vibrations can be recorded by accelerometers and gyroscopes applied on a subject's chest. In particular, the local 3D linear accelerations and 3D angular velocities of the chest wall are referred to as seismocardiograms (SCG) and gyrocardiograms (GCG), respectively. These signals usually exhibit a low signal-to-noise ratio, as well as non-negligible amplitude and morphological changes due to changes in posture and the sensors' location, respiratory activity, as well as other sources of intra-subject and inter-subject variability. These factors make heartbeat detection a complex task; therefore, a reference electrocardiogram (ECG) lead is usually acquired in SCG and GCG studies to ensure correct localization of heartbeats. Recently, a template matching technique based on cross correlation has proven to be particularly effective in recognizing individual heartbeats in SCG signals. This study aims to verify the performance of this technique when applied on GCG signals. Tests were conducted on a public database consisting of SCG, GCG, and ECG signals recorded synchronously on 100 patients with valvular heart diseases. The results show that the template matching technique identified heartbeats in GCG signals with a sensitivity and positive predictive value (PPV) of 87% and 92%, respectively. Regression, correlation, and Bland-Altman analyses carried out on inter-beat intervals obtained from GCG and ECG (assumed as reference) reported a slope of 0.995, an intercept of 4.06 ms (R2 > 0.99), a Pearson's correlation coefficient of 0.9993, and limits of agreement of about ±13 ms with a negligible bias. A comparison with the results of a previous study obtained on SCG signals from the same database revealed that GCG enabled effective cardiac monitoring in significantly more patients than SCG (95 vs. 77). This result suggests that GCG could ensure more robust and reliable cardiac monitoring in patients with heart diseases with respect to SCG.
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Affiliation(s)
- Salvatore Parlato
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Jessica Centracchio
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Daniele Esposito
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Paolo Bifulco
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Emilio Andreozzi
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
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7
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Centracchio J, Parlato S, Esposito D, Bifulco P, Andreozzi E. ECG-Free Heartbeat Detection in Seismocardiography Signals via Template Matching. SENSORS (BASEL, SWITZERLAND) 2023; 23:4684. [PMID: 37430606 DOI: 10.3390/s23104684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 07/12/2023]
Abstract
Cardiac monitoring can be performed by means of an accelerometer attached to a subject's chest, which produces the Seismocardiography (SCG) signal. Detection of SCG heartbeats is commonly carried out by taking advantage of a simultaneous electrocardiogram (ECG). SCG-based long-term monitoring would certainly be less obtrusive and easier to implement without an ECG. Few studies have addressed this issue using a variety of complex approaches. This study proposes a novel approach to ECG-free heartbeat detection in SCG signals via template matching, based on normalized cross-correlation as heartbeats similarity measure. The algorithm was tested on the SCG signals acquired from 77 patients with valvular heart diseases, available from a public database. The performance of the proposed approach was assessed in terms of sensitivity and positive predictive value (PPV) of the heartbeat detection and accuracy of inter-beat intervals measurement. Sensitivity and PPV of 96% and 97%, respectively, were obtained by considering templates that included both systolic and diastolic complexes. Regression, correlation, and Bland-Altman analyses carried out on inter-beat intervals reported slope and intercept of 0.997 and 2.8 ms (R2 > 0.999), as well as non-significant bias and limits of agreement of ±7.8 ms. The results are comparable or superior to those achieved by far more complex algorithms, also based on artificial intelligence. The low computational burden of the proposed approach makes it suitable for direct implementation in wearable devices.
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Affiliation(s)
- Jessica Centracchio
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Salvatore Parlato
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Daniele Esposito
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Paolo Bifulco
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Emilio Andreozzi
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
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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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Koivisto T, Lahdenoja O, Hurnanen T, Koskinen J, Jafarian K, Vasankari T, Jaakkola S, Kiviniemi TO, Airaksinen KEJ. Mechanocardiography-Based Measurement System Indicating Changes in Heart Failure Patients during Hospital Admission and Discharge. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22249781. [PMID: 36560149 PMCID: PMC9783454 DOI: 10.3390/s22249781] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 11/27/2022] [Accepted: 12/04/2022] [Indexed: 05/26/2023]
Abstract
Heart failure (HF) is a disease related to impaired performance of the heart and is a significant cause of mortality and treatment costs in the world. During its progression, HF causes worsening (decompensation) periods which generally require hospital care. In order to reduce the suffering of the patients and the treatment cost, avoiding unnecessary hospital visits is essential, as hospitalization can be prevented by medication. We have developed a data-collection device that includes a high-quality 3-axis accelerometer and 3-axis gyroscope and a single-lead ECG. This allows gathering ECG synchronized data utilizing seismo- and gyrocardiography (SCG, GCG, jointly mechanocardiography, MCG) and comparing the signals of HF patients in acute decompensation state (hospital admission) and compensated condition (hospital discharge). In the MECHANO-HF study, we gathered data from 20 patients, who each had admission and discharge measurements. In order to avoid overfitting, we used only features developed beforehand and selected features that were not outliers. As a result, we found three important signs indicating the worsening of the disease: an increase in signal RMS (root-mean-square) strength (across SCG and GCG), an increase in the strength of the third heart sound (S3), and a decrease in signal stability around the first heart sound (S1). The best individual feature (S3) alone was able to separate the recordings, giving 85.0% accuracy and 90.9% accuracy regarding all signals and signals with sinus rhythm only, respectively. These observations pave the way to implement solutions for patient self-screening of the HF using serial measurements.
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Affiliation(s)
- Tero Koivisto
- Department of Computing, University of Turku, 20500 Turku, Finland
| | - Olli Lahdenoja
- Department of Computing, University of Turku, 20500 Turku, Finland
| | - Tero Hurnanen
- Department of Computing, University of Turku, 20500 Turku, Finland
| | - Juho Koskinen
- Department of Computing, University of Turku, 20500 Turku, Finland
| | | | - Tuija Vasankari
- Heart Center, Turku University Hospital, University of Turku, 20520 Turku, Finland
| | - Samuli Jaakkola
- Heart Center, Turku University Hospital, University of Turku, 20520 Turku, Finland
| | - Tuomas O Kiviniemi
- Heart Center, Turku University Hospital, University of Turku, 20520 Turku, Finland
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Balali P, Rabineau J, Hossein A, Tordeur C, Debeir O, van de Borne P. Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography-A Narrative Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22239565. [PMID: 36502267 PMCID: PMC9737480 DOI: 10.3390/s22239565] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 11/11/2022] [Accepted: 11/28/2022] [Indexed: 05/29/2023]
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.
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Affiliation(s)
- Paniz Balali
- Laboratoray of Physics and Physiology, Université Libre de Bruxelles, 1050 Brussels, Belgium
- Laboratory of Image Synthesis and Analysis, Université Libre de Bruxelles, 1050 Brussels, Belgium
| | - Jeremy Rabineau
- Laboratoray of Physics and Physiology, Université Libre de Bruxelles, 1050 Brussels, Belgium
| | - Amin Hossein
- Laboratoray of Physics and Physiology, Université Libre de Bruxelles, 1050 Brussels, Belgium
| | - Cyril Tordeur
- Laboratoray of Physics and Physiology, Université Libre de Bruxelles, 1050 Brussels, Belgium
| | - Olivier Debeir
- Laboratory of Image Synthesis and Analysis, Université Libre de Bruxelles, 1050 Brussels, Belgium
| | - Philippe van de Borne
- Laboratoray of Physics and Physiology, Université Libre de Bruxelles, 1050 Brussels, Belgium
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, 1050 Brussels, Belgium
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11
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Centracchio J, Andreozzi E, Esposito D, Gargiulo GD, Bifulco P. Detection of Aortic Valve Opening and Estimation of Pre-Ejection Period in Forcecardiography Recordings. Bioengineering (Basel) 2022; 9:bioengineering9030089. [PMID: 35324778 PMCID: PMC8945374 DOI: 10.3390/bioengineering9030089] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 02/14/2022] [Accepted: 02/18/2022] [Indexed: 11/16/2022] Open
Abstract
Forcecardiography (FCG) is a novel technique that measures the local forces induced on the chest wall by the mechanical activity of the heart. Specific piezoresistive or piezoelectric force sensors are placed on subjects’ thorax to measure these very small forces. The FCG signal can be divided into three components: low-frequency FCG, high-frequency FCG (HF-FCG) and heart sound FCG. HF-FCG has been shown to share a high similarity with the Seismocardiogram (SCG), which is commonly acquired via small accelerometers and is mainly used to locate specific fiducial markers corresponding to essential events of the cardiac cycle (e.g., heart valves opening and closure, peaks of blood flow). However, HF-FCG has not yet been demonstrated to provide the timings of these markers with reasonable accuracy. This study addresses the detection of the aortic valve opening (AO) marker in FCG signals. To this aim, simultaneous recordings from FCG and SCG sensors were acquired, together with Electrocardiogram (ECG) recordings, from a few healthy subjects at rest, both during quiet breathing and apnea. The AO markers were located in both SCG and FCG signals to obtain pre-ejection periods (PEP) estimates, which were compared via statistical analyses. The PEPs estimated from FCG and SCG showed a strong linear relationship (r > 0.95) with a practically unit slope, and 95% of their differences were found to be distributed within ± 4.6 ms around small biases of approximately 1 ms, corresponding to percentage differences lower than 5% of the mean measured PEP. These preliminary results suggest that FCG can provide accurate AO timings and PEP estimates.
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Affiliation(s)
- Jessica Centracchio
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21 80125 Napoli, Italy; (J.C.); (D.E.); (P.B.)
| | - Emilio Andreozzi
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21 80125 Napoli, Italy; (J.C.); (D.E.); (P.B.)
- Correspondence:
| | - Daniele Esposito
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21 80125 Napoli, Italy; (J.C.); (D.E.); (P.B.)
| | - Gaetano Dario Gargiulo
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith 2751, Australia;
| | - Paolo Bifulco
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21 80125 Napoli, Italy; (J.C.); (D.E.); (P.B.)
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12
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Rabineau J, Nonclercq A, Leiner T, van de Borne P, Migeotte PF, Haut B. Closed-Loop Multiscale Computational Model of Human Blood Circulation. Applications to Ballistocardiography. Front Physiol 2021; 12:734311. [PMID: 34955874 PMCID: PMC8697684 DOI: 10.3389/fphys.2021.734311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 11/01/2021] [Indexed: 11/13/2022] Open
Abstract
Cardiac mechanical activity leads to periodic changes in the distribution of blood throughout the body, which causes micro-oscillations of the body's center of mass and can be measured by ballistocardiography (BCG). However, many of the BCG findings are based on parameters whose origins are poorly understood. Here, we generate simulated multidimensional BCG signals based on a more exhaustive and accurate computational model of blood circulation than previous attempts. This model consists in a closed loop 0D-1D multiscale representation of the human blood circulation. The 0D elements include the cardiac chambers, cardiac valves, arterioles, capillaries, venules, and veins, while the 1D elements include 55 systemic and 57 pulmonary arteries. The simulated multidimensional BCG signal is computed based on the distribution of blood in the different compartments and their anatomical position given by whole-body magnetic resonance angiography on a healthy young subject. We use this model to analyze the elements affecting the BCG signal on its different axes, allowing a better interpretation of clinical records. We also evaluate the impact of filtering and healthy aging on the BCG signal. The results offer a better view of the physiological meaning of BCG, as compared to previous models considering mainly the contribution of the aorta and focusing on longitudinal acceleration BCG. The shape of experimental BCG signals can be reproduced, and their amplitudes are in the range of experimental records. The contributions of the cardiac chambers and the pulmonary circulation are non-negligible, especially on the lateral and transversal components of the velocity BCG signal. The shapes and amplitudes of the BCG waveforms are changing with age, and we propose a scaling law to estimate the pulse wave velocity based on the time intervals between the peaks of the acceleration BCG signal. We also suggest new formulas to estimate the stroke volume and its changes based on the BCG signal expressed in terms of acceleration and kinetic energy.
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Affiliation(s)
- Jeremy Rabineau
- TIPs, Université Libre de Bruxelles, Brussels, Belgium
- LPHYS, Université Libre de Bruxelles, Brussels, Belgium
| | | | - Tim Leiner
- Department of Radiology, Utrecht University Medical Center, Utrecht, Netherlands
| | - Philippe van de Borne
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Brussels, Belgium
| | | | - Benoit Haut
- TIPs, Université Libre de Bruxelles, Brussels, Belgium
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13
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Herkert C, Migeotte PF, Hossein A, Spee RF, Kemps HMC. The kinocardiograph for assessment of changes in haemodynamic load in patients with chronic heart failure with reduced ejection fraction. ESC Heart Fail 2021; 8:4925-4932. [PMID: 34687162 PMCID: PMC8712789 DOI: 10.1002/ehf2.13522] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 06/14/2021] [Accepted: 07/05/2021] [Indexed: 01/15/2023] Open
Abstract
Aims The kinocardiograph (KCG) is an unobtrusive device, consisting of a chest sensor, which records local thoracic vibrations produced in result of cardiac contraction and ejection of blood into the great vessels [seismocardiography (SCG)], and a lower back sensor, which records micromovements of the body in reaction to blood flowing through the vasculature [ballistocardiography (BCG)]. SCG and BCG signals are translated to the integral of cardiac kinetic energy (iK) and cardiac maximum power (Pmax), which might be promising metrics for future telemonitoring purposes in heart failure (HF). As a first step of validation, this study aimed to determine whether iK and Pmax are responsive to exercise‐induced changes in the haemodynamic load of the heart in HF patients. Methods and results Fifteen patients with stable HF with reduced ejection fraction performed a submaximal exercise protocol. KCG and cardiac ultrasound measurements were obtained both at rest and at submaximal exercise. BCG iK over the cardiac cycle (CC) increased significantly (0.0026 ± 0.0017 to 0.0052 ± 0.0061 mJ.s.; P = 0.01) during exercise, in contrast to a non‐significant increase in SCG iK CC. BCG Pmax CC increased significantly (0.92 ± 0.89 to 2.03 ± 1.95 mJ/s; P = 0.02), in contrast to a non‐significant increase in SCG Pmax CC. When analysing the systolic phase of the CC, similar patterns were found. Cardiac output (CO) ratio (i.e. CO exercise/CO rest) showed a moderate, significant correlation with BCG Pmax CC ratio (r = +0.65; P = 0.008) and with SCG Pmax CC ratio (r = +0.54; P = 0.04). Conclusions iK and Pmax measured with the KCG, preferentially using BCG, are responsive to changes in the haemodynamic load of the heart in HF patients. The combination of the BCG and SCG sensor might be of added value to fully understand changes in haemodynamics and to discriminate between an HF patient and a healthy individual.
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Affiliation(s)
- Cyrille Herkert
- Department of Cardiology, Máxima Medical Centre, Dominee Theodor Fliednerstraat 1, Eindhoven, 5631 BM, The Netherlands
| | | | - Amin Hossein
- LPHYS, Université Libre de Bruxelles, Brussels, Belgium
| | - Rudolph Ferdinand Spee
- Department of Cardiology, Máxima Medical Centre, Dominee Theodor Fliednerstraat 1, Eindhoven, 5631 BM, The Netherlands
| | - Hareld Marijn Clemens Kemps
- Department of Cardiology, Máxima Medical Centre, Dominee Theodor Fliednerstraat 1, Eindhoven, 5631 BM, The Netherlands.,Department of Industrial Design, Eindhoven University of Technology, Eindhoven, The Netherlands
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14
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Sadek I, Abdulrazak B. A comparison of three heart rate detection algorithms over ballistocardiogram signals. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.103017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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15
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Hossein A, Rabineau J, Gorlier D, Del Rio JIJ, van de Borne P, Migeotte PF, Nonclercq A. Kinocardiography Derived from Ballistocardiography and Seismocardiography Shows High Repeatability in Healthy Subjects. SENSORS (BASEL, SWITZERLAND) 2021; 21:815. [PMID: 33530417 PMCID: PMC7865512 DOI: 10.3390/s21030815] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 01/20/2021] [Accepted: 01/21/2021] [Indexed: 01/14/2023]
Abstract
Recent years have witnessed an upsurge in the usage of ballistocardiography (BCG) and seismocardiography (SCG) to record myocardial function both in normal and pathological populations. Kinocardiography (KCG) combines these techniques by measuring 12 degrees-of-freedom of body motion produced by myocardial contraction and blood flow through the cardiac chambers and major vessels. The integral of kinetic energy (iK) obtained from the linear and rotational SCG/BCG signals, and automatically computed over the cardiac cycle, is used as a marker of cardiac mechanical function. The present work systematically evaluated the test-retest (TRT) reliability of KCG iK derived from BCG/SCG signals in the short term (<15 min) and long term (3-6 h) on 60 healthy volunteers. Additionally, we investigated the difference of repeatability with different body positions. First, we found high short-term TRT reliability for KCG metrics derived from SCG and BCG recordings. Exceptions to this finding were limited to metrics computed in left lateral decubitus position where the TRT reliability was moderate-to-high. Second, we found low-to-moderate long-term TRT reliability for KCG metrics as expected and confirmed by blood pressure measurements. In summary, KCG parameters derived from BCG/SCG signals show high repeatability and should be further investigated to confirm their use for cardiac condition longitudinal monitoring.
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Affiliation(s)
- Amin Hossein
- LPHYS, Université Libre de Bruxelles, 1050 Bruxelles, Belgium; (J.R.); (D.G.); (P.-F.M.)
- BEAMS, Université Libre de Bruxelles, 1050 Bruxelles, Belgium;
| | - Jérémy Rabineau
- LPHYS, Université Libre de Bruxelles, 1050 Bruxelles, Belgium; (J.R.); (D.G.); (P.-F.M.)
| | - Damien Gorlier
- LPHYS, Université Libre de Bruxelles, 1050 Bruxelles, Belgium; (J.R.); (D.G.); (P.-F.M.)
| | - Jose Ignacio Juarez Del Rio
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, 1050 Bruxelles, Belgium; (J.I.J.D.R.); (P.v.d.B.)
| | - Philippe van de Borne
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, 1050 Bruxelles, Belgium; (J.I.J.D.R.); (P.v.d.B.)
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16
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Hossein A, Rabineau J, Gorlier D, Pinki F, van de Borne P, Nonclercq A, Migeotte PF. Effects of acquisition device, sampling rate, and record length on kinocardiography during position-induced haemodynamic changes. Biomed Eng Online 2021; 20:3. [PMID: 33407507 PMCID: PMC7788803 DOI: 10.1186/s12938-020-00837-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 12/10/2020] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Kinocardiography (KCG) is a promising new technique used to monitor cardiac mechanical function remotely. KCG is based on ballistocardiography (BCG) and seismocardiography (SCG), and measures 12 degrees-of-freedom (DOF) of body motion produced by myocardial contraction and blood flow through the cardiac chambers and major vessels. RESULTS The integral of kinetic energy ([Formula: see text]) obtained from the linear and rotational SCG/BCG signals was computed over each dimension over the cardiac cycle, and used as a marker of cardiac mechanical function. We tested the hypotheses that KCG metrics can be acquired using different sensors, and at 50 Hz. We also tested the effect of record length on the ensemble average on which the metrics were computed. Twelve healthy males were tested in the supine, head-down tilt, and head-up tilt positions to expand the haemodynamic states on which the validation was performed. CONCLUSIONS KCG metrics computed on 50 Hz and 1 kHz SCG/BCG signals were very similar. Most of the metrics were highly similar when computed on different sensors, and with less than 5% of error when computed on record length longer than 60 s. These results suggest that KCG may be a robust and non-invasive method to monitor cardiac inotropic activity. Trial registration Clinicaltrials.gov, NCT03107351. Registered 11 April 2017, https://clinicaltrials.gov/ct2/show/NCT03107351?term=NCT03107351&draw=2&rank=1 .
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Affiliation(s)
- Amin Hossein
- LPHYS, Université Libre de Bruxelles, Brussels, Belgium.
- BEAMS, Université Libre de Bruxelles, Brussels, Belgium.
| | | | | | - Farhana Pinki
- LPHYS, Université Libre de Bruxelles, Brussels, Belgium
| | - Philippe van de Borne
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Brussels, Belgium
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17
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Convertino VA, Schauer SG, Weitzel EK, Cardin S, Stackle ME, Talley MJ, Sawka MN, Inan OT. Wearable Sensors Incorporating Compensatory Reserve Measurement for Advancing Physiological Monitoring in Critically Injured Trauma Patients. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6413. [PMID: 33182638 PMCID: PMC7697670 DOI: 10.3390/s20226413] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 11/02/2020] [Accepted: 11/04/2020] [Indexed: 12/21/2022]
Abstract
Vital signs historically served as the primary method to triage patients and resources for trauma and emergency care, but have failed to provide clinically-meaningful predictive information about patient clinical status. In this review, a framework is presented that focuses on potential wearable sensor technologies that can harness necessary electronic physiological signal integration with a current state-of-the-art predictive machine-learning algorithm that provides early clinical assessment of hypovolemia status to impact patient outcome. The ability to study the physiology of hemorrhage using a human model of progressive central hypovolemia led to the development of a novel machine-learning algorithm known as the compensatory reserve measurement (CRM). Greater sensitivity, specificity, and diagnostic accuracy to detect hemorrhage and onset of decompensated shock has been demonstrated by the CRM when compared to all standard vital signs and hemodynamic variables. The development of CRM revealed that continuous measurements of changes in arterial waveform features represented the most integrated signal of physiological compensation for conditions of reduced systemic oxygen delivery. In this review, detailed analysis of sensor technologies that include photoplethysmography, tonometry, ultrasound-based blood pressure, and cardiogenic vibration are identified as potential candidates for harnessing arterial waveform analog features required for real-time calculation of CRM. The integration of wearable sensors with the CRM algorithm provides a potentially powerful medical monitoring advancement to save civilian and military lives in emergency medical settings.
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Affiliation(s)
- Victor A. Convertino
- Battlefield Health & Trauma Center for Human Integrative Physiology, US Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA;
- Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA;
| | - Steven G. Schauer
- Battlefield Health & Trauma Center for Human Integrative Physiology, US Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA;
- Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA;
- Brooke Army Medical Center, JBSA Fort Sam Houston, San Antonio, TX 78234, USA
| | - Erik K. Weitzel
- Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA;
- Brooke Army Medical Center, JBSA Fort Sam Houston, San Antonio, TX 78234, USA
- 59th Medical Wing, JBSA Lackland, San Antonio, TX 78236, USA
| | - Sylvain Cardin
- Navy Medical Research Unit, JBSA Fort Sam Houston, San Antonio, TX 78234, USA;
| | - Mark E. Stackle
- Commander, US Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA;
| | - Michael J. Talley
- Commanding General, US Army Medical Research and Development Command, Fort Detrick, Frederick, MD 21702, USA;
| | - Michael N. Sawka
- Georgia Institute of Technology, Atlanta, GA 30332, USA; (M.N.S.); (O.T.I.)
| | - Omer T. Inan
- Georgia Institute of Technology, Atlanta, GA 30332, USA; (M.N.S.); (O.T.I.)
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Rabineau J, Hossein A, Landreani F, Haut B, Mulder E, Luchitskaya E, Tank J, Caiani EG, van de Borne P, Migeotte PF. Cardiovascular adaptation to simulated microgravity and countermeasure efficacy assessed by ballistocardiography and seismocardiography. Sci Rep 2020; 10:17694. [PMID: 33077727 PMCID: PMC7573608 DOI: 10.1038/s41598-020-74150-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 09/28/2020] [Indexed: 12/12/2022] Open
Abstract
Head-down bed rest (HDBR) reproduces the cardiovascular effects of microgravity. We tested the hypothesis that regular high-intensity physical exercise (JUMP) could prevent this cardiovascular deconditioning, which could be detected using seismocardiography (SCG) and ballistocardiography (BCG). 23 healthy males were exposed to 60-day HDBR: 12 in a physical exercise group (JUMP), the others in a control group (CTRL). SCG and BCG were measured during supine controlled breathing protocols. From the linear and rotational SCG/BCG signals, the integral of kinetic energy ([Formula: see text]) was computed on each dimension over the cardiac cycle. At the end of HDBR, BCG rotational [Formula: see text] and SCG transversal [Formula: see text] decreased similarly for all participants (- 40% and - 44%, respectively, p < 0.05), and so did orthostatic tolerance (- 58%, p < 0.01). Resting heart rate decreased in JUMP (- 10%, p < 0.01), but not in CTRL. BCG linear [Formula: see text] decreased in CTRL (- 50%, p < 0.05), but not in JUMP. The changes in the systolic component of BCG linear iK were correlated to those in stroke volume and VO2 max (R = 0.44 and 0.47, respectively, p < 0.05). JUMP was less affected by cardiovascular deconditioning, which could be detected by BCG in agreement with standard markers of the cardiovascular condition. This shows the potential of BCG to easily monitor cardiac deconditioning.
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Affiliation(s)
- Jeremy Rabineau
- LPHYS, Université Libre de Bruxelles, Brussels, Belgium. .,TIPs, Université Libre de Bruxelles, Brussels, Belgium.
| | - Amin Hossein
- LPHYS, Université Libre de Bruxelles, Brussels, Belgium
| | - Federica Landreani
- Electronic, Information and Biomedical Engineering Department, Politecnico Di Milano, Milan, Italy
| | - Benoit Haut
- TIPs, Université Libre de Bruxelles, Brussels, Belgium
| | - Edwin Mulder
- Institute of Aerospace Medicine, German Aerospace Center (DLR), Cologne, Germany
| | - Elena Luchitskaya
- Institute of Biomedical Problems of the Russian Academy of Sciences, Moscow, Russian Federation
| | - Jens Tank
- Institute of Aerospace Medicine, German Aerospace Center (DLR), Cologne, Germany
| | - Enrico G Caiani
- Electronic, Information and Biomedical Engineering Department, Politecnico Di Milano, Milan, Italy
| | - Philippe van de Borne
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Brussels, Belgium
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19
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Morra S, Gauthey A, Hossein A, Rabineau J, Racape J, Gorlier D, Migeotte PF, le Polain de Waroux JB, van de Borne P. Influence of sympathetic activation on myocardial contractility measured with ballistocardiography and seismocardiography during sustained end-expiratory apnea. Am J Physiol Regul Integr Comp Physiol 2020; 319:R497-R506. [PMID: 32877240 DOI: 10.1152/ajpregu.00142.2020] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Ballistocardiography (BCG) and seismocardiography (SCG) assess vibrations produced by cardiac contraction and blood flow, respectively, through micro-accelerometers and micro-gyroscopes. BCG and SCG kinetic energies (KE) and their temporal integrals (iK) during a single heartbeat are computed in linear and rotational dimensions. Our aim was to test the hypothesis that iK from BCG and SCG are related to sympathetic activation during maximal voluntary end-expiratory apnea. Multiunit muscle sympathetic nerve traffic [burst frequency (BF), total muscular sympathetic nerve activity (tMSNA)] was measured by microneurography during normal breathing and apnea (n = 28, healthy men). iK of BCG and SCG were simultaneously recorded in the linear and rotational dimension, along with oxygen saturation ([Formula: see text]) and systolic blood pressure (SBP). The mean duration of apneas was 25.4 ± 9.4 s. SBP, BF, and tMSNA increased during the apnea compared with baseline (P = 0.01, P = 0.002,and P = 0.001, respectively), whereas [Formula: see text] decreased (P = 0.02). At the end of the apnea compared with normal breathing, changes in iK computed from BCG were related to changes of tMSNA and BF only in the linear dimension (r = 0.85, P < 0.0001; and r = 0.72, P = 0.002, respectively), whereas changes in linear iK of SCG were related only to changes of tMSNA (r = 0.62, P = 0.01). We conclude that maximal end expiratory apnea increases cardiac kinetic energy computed from BCG and SCG, along with sympathetic activity. The novelty of the present investigation is that linear iK of BCG is directly and more strongly related to the rise in sympathetic activity than the SCG, mainly at the end of a sustained apnea, likely because the BCG is more affected by the sympathetic and hemodynamic effects of breathing cessation. BCG and SCG may prove useful to assess sympathetic nerve changes in patients with sleep disturbances.NEW & NOTEWORTHY Ballistocardiography (BCG) and seismocardiography (SCG) assess vibrations produced by cardiac contraction and blood flow, respectively, through micro-accelerometers and micro-gyroscopes. Kinetic energies (KE) and their temporal integrals (iK) during a single heartbeat are computed from the BCG and SCG waveforms in a linear and a rotational dimension. When compared with normal breathing, during an end-expiratory voluntary apnea, iK increased and was positively related to sympathetic nerve traffic rise assessed by microneurography. Further studies are needed to determine whether BCG and SCG can probe sympathetic nerve changes in patients with sleep disturbances.
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Affiliation(s)
- Sofia Morra
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Brussels, Belgium
| | - Anais Gauthey
- Department of Cardiology, Saint-Luc hospital, Université Catholique de Louvain, Brussels, Belgium
| | - Amin Hossein
- Laboratory of Physics and Physiology, Université Libre de Bruxelles, Brussels, Belgium
| | - Jérémy Rabineau
- Laboratory of Physics and Physiology, Université Libre de Bruxelles, Brussels, Belgium
| | - Judith Racape
- Research Centre in Epidemiology, Biostatistics and Clinical Research. School of Public Health. Université Libre de Bruxelles, Brussels, Belgium
| | - Damien Gorlier
- Laboratory of Physics and Physiology, Université Libre de Bruxelles, Brussels, Belgium
| | | | | | - Philippe van de Borne
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Brussels, Belgium
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20
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Morra S, Hossein A, Gorlier D, Rabineau J, Chaumont M, Migeotte PF, Van De Borne P. Ballistocardiography and seismocardiography detection of hemodynamic changes during simulated obstructive apnea. Physiol Meas 2020; 41:065007. [PMID: 32396890 DOI: 10.1088/1361-6579/ab924b] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVE To investigate if modern seismocardiography (SCG) and ballistocardiography (BCG) are useful in the detection of hemodynamic changes occurring during simulated obstructive apneic events. METHODS Forty-seven healthy volunteers performed a voluntary maximum Mueller maneuver (MM) for 10 s, and SCG and BCG signals were simultaneously taken. The kinetic energy of a set of cardiac cycles before and during the apneic episode was automatically computed from the rotational and linear channels of the SCG and BCG waveforms and its temporal integral (i K) was derived (unit of measure: microjoules per second (µJ·s)). The estimated transmural pressure (eP TM ) was assessed as the difference between systemic blood pressure and maximal inspiratory pressure (MIP). The Wilcoxon sign-rank test was used to evaluate differences in energy measurements between normal respiration and the loaded inspiration maneuver. Cardiac kinetic energies and the MIP produced during the MM were compared by linear regression analysis following log transformation in order to assess the correlation between variables. MAIN RESULTS The [Formula: see text] during normal breathing increased from 1.1(0.8; 1.4) to 1.9(1.4; 4.3) µJ·s during MM (p < 0.001). Meanwhile, [Formula: see text] increased from 54 (31; 92) to 84 (44; 153) µJ·s, (p < 0.001). The [Formula: see text] and [Formula: see text] of a set of cardiac cycles during the MM were negatively associated with the MIP (r: -0.59, p < 0.001 and r: -0.53, p = 0.001 for [Formula: see text] and [Formula: see text], respectively). When eP TM was considered, this association became positive (r: +0.58, p < 0.001 and r:+0.60, p < 0.001, for [Formula: see text] and [Formula: see text], respectively). When the i K LIN was considered as the comparative factor, correlations with the MIP and eP TM were weak and insignificant. Men had higher values of i K than women. SIGNIFICANCE Simulated obstructive apnea elicits large rotational i K swings, which are related to the intensity of the inspiratory effort and, as such, to the intensity of the left ventricular afterload. Computation of cardiac kinetic energy through BCG and SCG may shed further light on the impact of obstructive respiratory events on the cardiovascular system.
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Affiliation(s)
- Sofia Morra
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Belgium
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21
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Mora N, Cocconcelli F, Matrella G, Ciampolini P. Detection and Analysis of Heartbeats in Seismocardiogram Signals. SENSORS (BASEL, SWITZERLAND) 2020; 20:E1670. [PMID: 32192162 PMCID: PMC7146295 DOI: 10.3390/s20061670] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 02/24/2020] [Accepted: 03/14/2020] [Indexed: 02/05/2023]
Abstract
This paper presents an unsupervised methodology to analyze SeismoCardioGram (SCG) signals. Starting from raw accelerometric data, heartbeat complexes are extracted and annotated, using a two-step procedure. An unsupervised calibration procedure is added to better adapt to different user patterns. Results show that the performance scores achieved by the proposed methodology improve over related literature: on average, 98.5% sensitivity and 98.6% precision are achieved in beat detection, whereas RMS (Root Mean Square) error in heartbeat interval estimation is as low as 4.6 ms. This allows SCG heartbeat complexes to be reliably extracted. Then, the morphological information of such waveforms is further processed by means of a modular Convolutional Variational AutoEncoder network, aiming at extracting compressed, meaningful representation. After unsupervised training, the VAE network is able to recognize different signal morphologies, associating each user to its specific patterns with high accuracy, as indicated by specific performance metrics (including adjusted random and mutual information score, completeness, and homogeneity). Finally, a Linear Model is used to interpret the results of clustering in the learned latent space, highlighting the impact of different VAE architectural parameters (i.e., number of stacked convolutional units and dimension of latent space).
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Affiliation(s)
| | | | | | - Paolo Ciampolini
- Dip. Ingegneria e Architettura, Università di Parma, Parco Area delle Scienze 181/A, 43124 Parma (PR), Italy; (N.M.); (F.C.); (G.M.)
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Morra S, Hossein A, Gorlier D, Rabineau J, Chaumont M, Migeotte PF, van de Borne P. Modification of the mechanical cardiac performance during end-expiratory voluntary apnea recorded with ballistocardiography and seismocardiography. Physiol Meas 2019; 40:105005. [PMID: 31579047 DOI: 10.1088/1361-6579/ab4a6a] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To assess if micro-accelerometers and gyroscopes may provide useful information for the detection of breathing disturbances in further studies. APPROACH Forty-three healthy volunteers performed a 10 s end-expiratory breath-hold, while ballistocardiograph (BCG) and seismocardiograph (SCG) determined changes in kinetic energy and its integral over time (iK, J · s). BCG measures overall body accelerations in response to blood mass ejection into the main vasculature at each cardiac cycle, while SCG records local chest wall vibrations generated beat-by-beat by myocardial activity. This minimally intrusive technology assesses linear accelerations and angular velocities in 12 degrees of freedom to calculate iK during the whole cardiac cycle. iK produced during systole and diastole were also computed. MAIN RESULTS The iK during normal breathing was 87.1 [63.3; 132.8] µJ · s for the SCG and 4.5 [3.3; 6.2] µJ · s for the BCG. Both increased to 107.1 [69.0; 162.0] µJ · s and 6.1 [4.4; 9.0] µJ · s, respectively, during breath-holding (p = 0.003 and p < 0.0001, respectively). The iK of the SCG further increased during spontaneous respiration following apnea (from 107.1 [69.0; 162.0] µJ · s to 160.0 [96.3; 207.3] µJ · s, p < 0.0001). The ratio between the iK of diastole and systole increased from 0.35 [0.24; 0.45] during apnea to 0.49 [0.31; 0.80] (p < 0.0001) during the restoration of respiration. SIGNIFICANCE A brief voluntary apnea generates large and distinct increases in SCG and BCG waveforms. iK monitoring during sleep may prove useful for the detection of respiratory disturbances. ClinicalTrials.gov number: NCT03760159.
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Affiliation(s)
- Sofia Morra
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Bruxelles, Belgium.,Author to whom any correspondence should be addressed
| | - Amin Hossein
- LPHYS, Université Libre de Bruxelles, Bruxelles, Belgium
| | - Damien Gorlier
- LPHYS, Université Libre de Bruxelles, Bruxelles, Belgium
| | | | - Martin Chaumont
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Bruxelles, Belgium
| | | | - Philippe van de Borne
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, Bruxelles, Belgium.,Both authors contributed equally
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