{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T22:52:36Z","timestamp":1777675956320,"version":"3.51.4"},"reference-count":43,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,3,27]],"date-time":"2024-03-27T00:00:00Z","timestamp":1711497600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fonds Erasme","award":["29801"],"award-info":[{"award-number":["29801"]}]},{"name":"Fonds Erasme","award":["043709"],"award-info":[{"award-number":["043709"]}]},{"name":"Fonds de la Recherche Scientifique","award":["29801"],"award-info":[{"award-number":["29801"]}]},{"name":"Fonds de la Recherche Scientifique","award":["043709"],"award-info":[{"award-number":["043709"]}]},{"name":"PRODEX","award":["29801"],"award-info":[{"award-number":["29801"]}]},{"name":"PRODEX","award":["043709"],"award-info":[{"award-number":["043709"]}]},{"name":"Fonds de la Chirurgie Cardiaque","award":["29801"],"award-info":[{"award-number":["29801"]}]},{"name":"Fonds de la Chirurgie Cardiaque","award":["043709"],"award-info":[{"award-number":["043709"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u2019s 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\u2019 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) &gt; 0.77. The reliability of patient-acquired SCG metrics was high (ICC &gt; 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.<\/jats:p>","DOI":"10.3390\/s24072139","type":"journal-article","created":{"date-parts":[[2024,3,27]],"date-time":"2024-03-27T12:41:57Z","timestamp":1711543317000},"page":"2139","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Smartphone-Derived Seismocardiography: Robust Approach for Accurate Cardiac Energy Assessment in Patients with Various Cardiovascular Conditions"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5122-9927","authenticated-orcid":false,"given":"Amin","family":"Hossein","sequence":"first","affiliation":[{"name":"Laboratory of Physics and Physiology, Universit\u00e9 Libre de Bruxelles, 1050 Brussels, Belgium"},{"name":"Cardio-Pulmonary Exercise Laboratory, Faculty of Motor Sciences, Universit\u00e9 Libre de Bruxelles, Erasme Campus, Anderlecht, 1070 Brussels, Belgium"}]},{"given":"Elza","family":"Abdessater","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Erasme Hospital, Universit\u00e9 Libre de Bruxelles, 1050 Bruxelles, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6336-167X","authenticated-orcid":false,"given":"Paniz","family":"Balali","sequence":"additional","affiliation":[{"name":"Laboratory of Physics and Physiology, Universit\u00e9 Libre de Bruxelles, 1050 Brussels, Belgium"}]},{"given":"Elliot","family":"Cosneau","sequence":"additional","affiliation":[{"name":"Heartkinetics S.A., 6041 Charleroi, Belgium"}]},{"given":"Damien","family":"Gorlier","sequence":"additional","affiliation":[{"name":"Heartkinetics S.A., 6041 Charleroi, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7946-075X","authenticated-orcid":false,"given":"J\u00e9r\u00e9my","family":"Rabineau","sequence":"additional","affiliation":[{"name":"Laboratory of Physics and Physiology, Universit\u00e9 Libre de Bruxelles, 1050 Brussels, Belgium"}]},{"given":"Alexandre","family":"Almorad","sequence":"additional","affiliation":[{"name":"Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, 1050 Brussels, Belgium"}]},{"given":"Vitalie","family":"Faoro","sequence":"additional","affiliation":[{"name":"Cardio-Pulmonary Exercise Laboratory, Faculty of Motor Sciences, Universit\u00e9 Libre de Bruxelles, Erasme Campus, Anderlecht, 1070 Brussels, Belgium"}]},{"given":"Philippe","family":"van de Borne","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Erasme Hospital, Universit\u00e9 Libre de Bruxelles, 1050 Bruxelles, Belgium"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,27]]},"reference":[{"key":"ref_1","first-page":"e1","article-title":"Telemedicine and Its Role in Revolutionizing Healthcare Delivery","volume":"5","year":"2017","journal-title":"Am. J. Accountable Care"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/MPRV.2015.19","article-title":"Telemedicine in the Cloud Era: Prospects and Challenges","volume":"14","author":"Jin","year":"2015","journal-title":"IEEE Pervasive Comput."},{"key":"ref_3","first-page":"759","article-title":"Advances in Telemedicine for the Management of the Elderly Cardiac Patient","volume":"18","author":"Jamal","year":"2021","journal-title":"J. Geriatr. Cardiol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1378\/chest.100.4.991","article-title":"Seismocardiography for Monitoring Changes in Left Ventricular Function during Ischemia","volume":"100","author":"Salerno","year":"1991","journal-title":"Chest"},{"key":"ref_5","unstructured":"Salerno, D.M., and Zanetti, J. (2020, November 21). Seismocardiography a New Technique for Recording Cardiac Vibrations Concept Method and Initial Observations. Available online: https:\/\/eurekamag.com\/research\/007\/776\/007776006.php."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ramos-Castro, J., Moreno, J., Miranda-Vidal, H., Garc\u00eda-Gonz\u00e1lez, M.A., Fern\u00e1ndez-Chimeno, M., Rodas, G., and Capdevila, L. (September, January 28). Heart Rate Variability Analysis Using a Seismocardiogram Signal. Proceedings of the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, CA, USA.","DOI":"10.1109\/EMBC.2012.6347274"},{"key":"ref_7","unstructured":"Tkacz, E., Gzik, M., Paszenda, Z., and Pi\u0119tka, E. (2018, January 18\u201320). Heart Beat Detection from Smartphone SCG Signals: Comparison with Previous Study on HR Estimation. Proceedings of the Innovations in Biomedical Engineering, Katowice, Poland."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1237043","DOI":"10.3389\/fcvm.2023.1237043","article-title":"Revolutionizing Smartphone Gyrocardiography for Heart Rate Monitoring: Overcoming Clinical Validation Hurdles","volume":"10","author":"Elgendi","year":"2023","journal-title":"Front. Cardiovasc. Med."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1329290","DOI":"10.3389\/fcvm.2023.1329290","article-title":"Detection of Heart Rate Using Smartphone Gyroscope Data: A Scoping Review","volume":"10","author":"Wu","year":"2023","journal-title":"Front. Cardiovasc. Med."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.resuscitation.2021.07.009","article-title":"Discrimination between the Presence and Absence of Spontaneous Circulation Using Smartphone Seismocardiography: A Preliminary Investigation","volume":"166","author":"Lee","year":"2021","journal-title":"Resuscitation"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Mehrang, S., Jafari Tadi, M., Kaisti, M., Lahdenoja, O., Vasankari, T., Kiviniemi, T., Airaksinen, J., Koivisto, T., and P\u00e4nk\u00e4\u00e4l\u00e4, M. (2018, January 23\u201326). Machine Learning Based Classification of Myocardial Infarction Conditions Using Smartphone-Derived Seismo- and Gyrocardiography. Proceedings of the 2018 Computing in Cardiology Conference (CinC), Maastricht, The Netherlands.","DOI":"10.22489\/CinC.2018.110"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1524","DOI":"10.1161\/CIRCULATIONAHA.117.032804","article-title":"Mobile Phone Detection of Atrial Fibrillation with Mechanocardiography","volume":"137","author":"Jaakkola","year":"2018","journal-title":"Circulation"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"7957","DOI":"10.1109\/JSEN.2020.2981334","article-title":"Classification of Atrial Fibrillation and Acute Decompensated Heart Failure Using Smartphone Mechanocardiography: A Multilabel Learning Approach","volume":"20","author":"Mehrang","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_14","first-page":"271","article-title":"Seismocardiography with Smartphones: No Leap from Bench to Bedside (Yet)","volume":"295","author":"Albrecht","year":"2022","journal-title":"Stud. Health Technol. Inf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"146801","DOI":"10.1109\/ACCESS.2019.2946117","article-title":"Reliability of Self-Applied Smartphone Mechanocardiography for Atrial Fibrillation Detection","volume":"7","author":"Mehrang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Hossein, A., Rabineau, J., Gorlier, D., Pinki, F., van de Borne, P., Nonclercq, A., and Migeotte, P.-F. (2021). Effects of Acquisition Device, Sampling Rate, and Record Length on Kinocardiography during Position-Induced Haemodynamic Changes. BioMed. Eng. OnLine, 20.","DOI":"10.1186\/s12938-020-00837-5"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6823","DOI":"10.1038\/s41598-017-07248-y","article-title":"Gyrocardiography: A New Non-Invasive Monitoring Method for the Assessment of Cardiac Mechanics and the Estimation of Hemodynamic Variables","volume":"7","author":"Lehtonen","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Sieci\u0144ski, S., Kostka, P.S., and Tkacz, E.J. (2020). Gyrocardiography: A Review of the Definition, History, Waveform Description, and Applications. Sensors, 20.","DOI":"10.3390\/s20226675"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Castiglioni, P., Meriggi, P., Rizzo, F., Vaini, E., Faini, A., Parati, G., Merati, G., and Di Rienzo, M. (September, January 30). Cardiac Sounds from a Wearable Device for Sternal Seismocardiography. Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, USA.","DOI":"10.1109\/IEMBS.2011.6091063"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Yeh, C.-C.M., Zhu, Y., Ulanova, L., Begum, N., Ding, Y., Dau, H.A., Silva, D.F., Mueen, A., and Keogh, E. (2016, January 12\u201315). Matrix Profile I: All Pairs Similarity Joins for Time Series: A Unifying View That Includes Motifs, Discords and Shapelets. Proceedings of the 2016 IEEE 16th International Conference on Data Mining (ICDM), Barcelona, Spain.","DOI":"10.1109\/ICDM.2016.0179"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1504","DOI":"10.21105\/joss.01504","article-title":"STUMPY: A Powerful and Scalable Python Library for Time Series Data Mining","volume":"4","author":"Law","year":"2019","journal-title":"J. Open Source Softw."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1096859","DOI":"10.3389\/fcvm.2023.1096859","article-title":"Non-Invasive Cardiac Kinetic Energy Distribution: A New Marker of Heart Failure with Impaired Ejection Fraction (KINO-HF)","volume":"10","author":"Hossein","year":"2023","journal-title":"Front. Cardiovasc. Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"4925","DOI":"10.1002\/ehf2.13522","article-title":"The Kinocardiograph for Assessment of Changes in Haemodynamic Load in Patients with Chronic Heart Failure with Reduced Ejection Fraction","volume":"8","author":"Herkert","year":"2021","journal-title":"ESC Heart Fail."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"141","DOI":"10.11613\/BM.2015.015","article-title":"Understanding Bland Altman Analysis","volume":"25","author":"Giavarina","year":"2015","journal-title":"Biochem. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1037\/0033-2909.86.2.420","article-title":"Intraclass Correlations: Uses in Assessing Rater Reliability","volume":"86","author":"Shrout","year":"1979","journal-title":"Psychol. Bull."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1037\/1082-989X.1.1.30","article-title":"Forming Inferences about Some Intraclass Correlation Coefficients","volume":"1","author":"McGraw","year":"1996","journal-title":"Psychol. Methods"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"H893","DOI":"10.1152\/ajpheart.00942.2011","article-title":"Quantification of Left and Right Ventricular Kinetic Energy Using Four-Dimensional Intracardiac Magnetic Resonance Imaging Flow Measurements","volume":"302","author":"Carlsson","year":"2012","journal-title":"Am. J. Physiol. Heart Circ. Physiol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1186\/s12968-018-0483-6","article-title":"Left Ventricular Blood Flow Kinetic Energy after Myocardial Infarction\u2014Insights from 4D Flow Cardiovascular Magnetic Resonance","volume":"20","author":"Garg","year":"2018","journal-title":"J. Cardiovasc. Magn. Reson."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1093\/ehjci\/jes159","article-title":"Four-Dimensional Blood Flow-Specific Markers of LV Dysfunction in Dilated Cardiomyopathy","volume":"14","author":"Eriksson","year":"2013","journal-title":"Eur. Heart J. Cardiovasc. Imaging"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"10479","DOI":"10.1038\/s41598-019-46823-3","article-title":"Accurate Detection of Dobutamine-Induced Haemodynamic Changes by Kino-Cardiography: A Randomised Double-Blind Placebo-Controlled Validation Study","volume":"9","author":"Hossein","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1038\/s41598-020-79933-4","article-title":"Assessment of Left Ventricular Twist by 3D Ballistocardiography and Seismocardiography Compared with 2D STI Echocardiography in a Context of Enhanced Inotropism in Healthy Subjects","volume":"11","author":"Morra","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_32","unstructured":"Bhoi, A.K., de Albuquerque, V.H.C., Sur, S.N., and Barsocchi, P. (2022). 5G IoT and Edge Computing for Smart Healthcare, Academic Press. Intelligent Data-Centric Systems."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Hossein, A., Rabineau, J., Gorlier, D., Del Rio, J.I.J., van de Borne, P., Migeotte, P.-F., and Nonclercq, A. (2021). Kinocardiography Derived from Ballistocardiography and Seismocardiography Shows High Repeatability in Healthy Subjects. Sensors, 21.","DOI":"10.3390\/s21030815"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1099","DOI":"10.1161\/01.HYP.33.5.1099","article-title":"Race and Diurnal Blood Pressure Patterns","volume":"33","author":"Profant","year":"1999","journal-title":"Hypertension"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1586\/erc.09.35","article-title":"Dipping Pattern of Nocturnal Blood Pressure in Patients with Hypertension","volume":"7","author":"Fagard","year":"2009","journal-title":"Expert Rev. Cardiovasc. Ther."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3446","DOI":"10.1002\/ehf2.14477","article-title":"The Kinocardiograph for Assessment of Fluid Status in Patients with Acute Decompensated Heart Failure","volume":"10","author":"Herkert","year":"2023","journal-title":"ESC Heart Fail."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"734311","DOI":"10.3389\/fphys.2021.734311","article-title":"Closed-Loop Multiscale Computational Model of Human Blood Circulation. Applications to Ballistocardiography","volume":"12","author":"Rabineau","year":"2021","journal-title":"Front. Physiol."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Centracchio, J., Parlato, S., Esposito, D., Bifulco, P., and Andreozzi, E. (2023). ECG-Free Heartbeat Detection in Seismocardiography Signals via Template Matching. Sensors, 23.","DOI":"10.3390\/s23104684"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Parlato, S., Centracchio, J., Esposito, D., Bifulco, P., and Andreozzi, E. (2023). Heartbeat Detection in Gyrocardiography Signals without Concurrent ECG Tracings. Sensors, 23.","DOI":"10.3390\/s23136200"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"13055","DOI":"10.1109\/JSEN.2022.3173205","article-title":"Respiratory Modulation of Sternal Motion in the Context of Seismocardiography","volume":"22","author":"Skoric","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Balali, P., Rabineau, J., Hossein, A., Tordeur, C., Debeir, O., and van de Borne, P. (2022). Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography\u2014A Narrative Review. Sensors, 22.","DOI":"10.3390\/s22239565"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"64","DOI":"10.3390\/vibration2010005","article-title":"Recent Advances in Seismocardiography","volume":"2","author":"Taebi","year":"2019","journal-title":"Vibration"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1109\/JSEN.2017.2787628","article-title":"Universal Pre-Ejection Period Estimation Using Seismocardiography: Quantifying the Effects of Sensor Placement and Regression Algorithms","volume":"18","author":"Ashouri","year":"2018","journal-title":"IEEE Sens. J."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/7\/2139\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:19:21Z","timestamp":1760105961000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/7\/2139"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,27]]},"references-count":43,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["s24072139"],"URL":"https:\/\/doi.org\/10.3390\/s24072139","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,27]]}}}