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For: Inan OT, Baran Pouyan M, Javaid AQ, Dowling S, Etemadi M, Dorier A, Heller JA, Bicen AO, Roy S, De Marco T, Klein L. Novel Wearable Seismocardiography and Machine Learning Algorithms Can Assess Clinical Status of Heart Failure Patients. Circ Heart Fail 2018;11:e004313. [PMID: 29330154 DOI: 10.1161/CIRCHEARTFAILURE.117.004313] [Cited by in Crossref: 56] [Cited by in F6Publishing: 34] [Article Influence: 18.7] [Reference Citation Analysis]
Number Citing Articles
1 Di Rienzo M, Rizzo G, Işılay ZM, Lombardi P. SeisMote: A Multi-Sensor Wireless Platform for Cardiovascular Monitoring in Laboratory, Daily Life, and Telemedicine. Sensors (Basel) 2020;20:E680. [PMID: 31991918 DOI: 10.3390/s20030680] [Cited by in Crossref: 14] [Cited by in F6Publishing: 8] [Article Influence: 7.0] [Reference Citation Analysis]
2 Morra S, Pitisci L, Su F, Hossein A, Rabineau J, Racape J, Gorlier D, Herpain A, Migeotte PF, Creteur J, van de Borne P. Quantification of Cardiac Kinetic Energy and Its Changes During Transmural Myocardial Infarction Assessed by Multi-Dimensional Seismocardiography. Front Cardiovasc Med 2021;8:603319. [PMID: 33763456 DOI: 10.3389/fcvm.2021.603319] [Reference Citation Analysis]
3 Işilay Zeybek ZM, Racca V, Pezzano A, Tavanelli M, Di Rienzo M. Can Seismocardiogram Fiducial Points Be Used for the Routine Estimation of Cardiac Time Intervals in Cardiac Patients? Front Physiol 2022;13:825918. [DOI: 10.3389/fphys.2022.825918] [Reference Citation Analysis]
4 Taebi A, Solar BE, Bomar AJ, Sandler RH, Mansy HA. Recent Advances in Seismocardiography. Vibration 2019;2:64-86. [PMID: 34113791 DOI: 10.3390/vibration2010005] [Cited by in Crossref: 53] [Cited by in F6Publishing: 5] [Article Influence: 17.7] [Reference Citation Analysis]
5 Mora N, Cocconcelli F, Matrella G, Ciampolini P. A Unified Methodology for Heartbeats Detection in Seismocardiogram and Ballistocardiogram Signals. Computers 2020;9:41. [DOI: 10.3390/computers9020041] [Cited by in Crossref: 2] [Article Influence: 1.0] [Reference Citation Analysis]
6 Shandhi MMH, Hersek S, Fan J, Sander E, De Marco T, Heller JA, Etemadi M, Klein L, Inan OT. Wearable Patch-Based Estimation of Oxygen Uptake and Assessment of Clinical Status during Cardiopulmonary Exercise Testing in Patients With Heart Failure. J Card Fail 2020;26:948-58. [PMID: 32473379 DOI: 10.1016/j.cardfail.2020.05.014] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
7 Naseri Jahfari A, Tax D, Reinders M, van der Bilt I. Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View. JMIR Med Inform 2022;10:e29434. [PMID: 35044316 DOI: 10.2196/29434] [Reference Citation Analysis]
8 Sadek I, Biswas J. Nonintrusive heart rate measurement using ballistocardiogram signals: a comparative study. SIViP 2019;13:475-82. [DOI: 10.1007/s11760-018-1372-z] [Cited by in Crossref: 13] [Cited by in F6Publishing: 2] [Article Influence: 3.3] [Reference Citation Analysis]
9 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) 2020;20:E6413. [PMID: 33182638 DOI: 10.3390/s20226413] [Cited by in Crossref: 8] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
10 Cheng L, Qiu Y, Schmidt BJ, Wei GW. Review of applications and challenges of quantitative systems pharmacology modeling and machine learning for heart failure. J Pharmacokinet Pharmacodyn 2021. [PMID: 34637069 DOI: 10.1007/s10928-021-09785-6] [Reference Citation Analysis]
11 Zia J, Kimball J, Hersek S, Shandhi MMH, Semiz B, Inan OT. A Unified Framework for Quality Indexing and Classification of Seismocardiogram Signals. IEEE J Biomed Health Inform 2020;24:1080-92. [PMID: 31369387 DOI: 10.1109/JBHI.2019.2931348] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 2.3] [Reference Citation Analysis]
12 Lanzer JD, Leuschner F, Kramann R, Levinson RT, Saez-Rodriguez J. Big Data Approaches in Heart Failure Research. Curr Heart Fail Rep 2020;17:213-24. [PMID: 32783147 DOI: 10.1007/s11897-020-00469-9] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
13 Singhal A, Cowie MR. The Role of Wearables in Heart Failure. Curr Heart Fail Rep 2020;17:125-32. [PMID: 32494944 DOI: 10.1007/s11897-020-00467-x] [Cited by in Crossref: 8] [Cited by in F6Publishing: 5] [Article Influence: 8.0] [Reference Citation Analysis]
14 Cook J, Umar M, Khalili F, Taebi A. Body Acoustics for the Non-Invasive Diagnosis of Medical Conditions. Bioengineering 2022;9:149. [DOI: 10.3390/bioengineering9040149] [Reference Citation Analysis]
15 Ode O, Orlandic L, Inan OT. Towards Continuous and Ambulatory Blood Pressure Monitoring: Methods for Efficient Data Acquisition for Pulse Transit Time Estimation. Sensors (Basel) 2020;20:E7106. [PMID: 33322391 DOI: 10.3390/s20247106] [Reference Citation Analysis]
16 Sadek I, Biswas J, Abdulrazak B. Ballistocardiogram signal processing: a review. Health Inf Sci Syst 2019;7:10. [PMID: 31114676 DOI: 10.1007/s13755-019-0071-7] [Cited by in Crossref: 32] [Cited by in F6Publishing: 9] [Article Influence: 10.7] [Reference Citation Analysis]
17 Guo A, Pasque M, Loh F, Mann DL, Payne PRO. Heart Failure Diagnosis, Readmission, and Mortality Prediction Using Machine Learning and Artificial Intelligence Models. Curr Epidemiol Rep 2020;7:212-9. [DOI: 10.1007/s40471-020-00259-w] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
18 Gupta P, Moghimi MJ, Jeong Y, Gupta D, Inan OT, Ayazi F. Precision wearable accelerometer contact microphones for longitudinal monitoring of mechano-acoustic cardiopulmonary signals. NPJ Digit Med 2020;3:19. [PMID: 32128449 DOI: 10.1038/s41746-020-0225-7] [Cited by in Crossref: 18] [Cited by in F6Publishing: 7] [Article Influence: 9.0] [Reference Citation Analysis]
19 Hossein A, Mirica DC, Rabineau J, Rio JID, Morra S, Gorlier D, Nonclercq A, van de Borne P, Migeotte PF. Accurate Detection of Dobutamine-induced Haemodynamic Changes by Kino-Cardiography: A Randomised Double-Blind Placebo-Controlled Validation Study. Sci Rep 2019;9:10479. [PMID: 31324831 DOI: 10.1038/s41598-019-46823-3] [Cited by in Crossref: 11] [Cited by in F6Publishing: 7] [Article Influence: 3.7] [Reference Citation Analysis]
20 Yang C, Fan F, Aranoff N, Green P, Li Y, Liu C, Tavassolian N. An Open-Access Database for the Evaluation of Cardio-Mechanical Signals From Patients With Valvular Heart Diseases. Front Physiol 2021;12:750221. [PMID: 34658932 DOI: 10.3389/fphys.2021.750221] [Reference Citation Analysis]
21 Rahmani MH, Berkvens R, Weyn M. Chest-Worn Inertial Sensors: A Survey of Applications and Methods. Sensors (Basel) 2021;21:2875. [PMID: 33921900 DOI: 10.3390/s21082875] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
22 Inan OT, Tenaerts P, Prindiville SA, Reynolds HR, Dizon DS, Cooper-Arnold K, Turakhia M, Pletcher MJ, Preston KL, Krumholz HM, Marlin BM, Mandl KD, Klasnja P, Spring B, Iturriaga E, Campo R, Desvigne-Nickens P, Rosenberg Y, Steinhubl SR, Califf RM. Digitizing clinical trials. NPJ Digit Med 2020;3:101. [PMID: 32821856 DOI: 10.1038/s41746-020-0302-y] [Cited by in Crossref: 38] [Cited by in F6Publishing: 31] [Article Influence: 19.0] [Reference Citation Analysis]
23 Faragli A, Abawi D, Quinn C, Cvetkovic M, Schlabs T, Tahirovic E, Düngen HD, Pieske B, Kelle S, Edelmann F, Alogna A. The role of non-invasive devices for the telemonitoring of heart failure patients. Heart Fail Rev 2021;26:1063-80. [PMID: 32338334 DOI: 10.1007/s10741-020-09963-7] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 0.5] [Reference Citation Analysis]
24 Gardner M, Randhawa S, Malouf G, Reynolds K. A Wearable Ballistocardiography Device for Estimating Heart Rate During Positive Airway Pressure Therapy: Investigational Study Among the General Population. JMIR Cardio 2021;5:e26259. [PMID: 33949952 DOI: 10.2196/26259] [Reference Citation Analysis]
25 Khedraki R, Srivastava AV, Bhavnani SP. Framework for Digital Health Phenotypes in Heart Failure. Heart Failure Clinics 2022. [DOI: 10.1016/j.hfc.2021.12.003] [Reference Citation Analysis]
26 Semiz B, Carek AM, Johnson JC, Ahmad S, Heller JA, Vicente FG, Caron S, Hogue CW, Etemadi M, Inan OT. Non-Invasive Wearable Patch Utilizing Seismocardiography for Peri-Operative Use in Surgical Patients. IEEE J Biomed Health Inform 2021;25:1572-82. [PMID: 33090962 DOI: 10.1109/JBHI.2020.3032938] [Reference Citation Analysis]
27 Amin MS, Wozniak M, Barbaric L, Pickard S, Yerrabelli RS, Christensen A, Coiado OC. Experimental Technologies in the Diagnosis and Treatment of COVID-19 in Patients with Comorbidities. J Healthc Inform Res 2021;:1-24. [PMID: 34541448 DOI: 10.1007/s41666-021-00106-7] [Reference Citation Analysis]
28 Vavrinsky E, Subjak J, Donoval M, Wagner A, Zavodnik T, Svobodova H. Application of Modern Multi-Sensor Holter in Diagnosis and Treatment. Sensors (Basel) 2020;20:E2663. [PMID: 32392697 DOI: 10.3390/s20092663] [Cited by in Crossref: 7] [Cited by in F6Publishing: 3] [Article Influence: 3.5] [Reference Citation Analysis]
29 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 DOI: 10.1186/s12938-020-00837-5] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
30 Lee K, Ni X, Lee JY, Arafa H, Pe DJ, Xu S, Avila R, Irie M, Lee JH, Easterlin RL, Kim DH, Chung HU, Olabisi OO, Getaneh S, Chung E, Hill M, Bell J, Jang H, Liu C, Park JB, Kim J, Kim SB, Mehta S, Pharr M, Tzavelis A, Reeder JT, Huang I, Deng Y, Xie Z, Davies CR, Huang Y, Rogers JA. Mechano-acoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch. Nat Biomed Eng 2020;4:148-58. [PMID: 31768002 DOI: 10.1038/s41551-019-0480-6] [Cited by in Crossref: 65] [Cited by in F6Publishing: 44] [Article Influence: 21.7] [Reference Citation Analysis]
31 Johnson EMI, Heller JA, Garcia Vicente F, Sarnari R, Gordon D, McCarthy PM, Barker AJ, Etemadi M, Markl M. Detecting Aortic Valve-Induced Abnormal Flow with Seismocardiography and Cardiac MRI. Ann Biomed Eng 2020;48:1779-92. [PMID: 32180050 DOI: 10.1007/s10439-020-02491-3] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
32 Adamo S, Ambrosino P, Ricciardi C, Accardo M, Mosella M, Cesarelli M, d’Addio G, Maniscalco M. A Machine Learning Approach to Predict the Rehabilitation Outcome in Convalescent COVID-19 Patients. JPM 2022;12:328. [DOI: 10.3390/jpm12030328] [Reference Citation Analysis]
33 Duncker D, Ding WY, Etheridge S, Noseworthy PA, Veltmann C, Yao X, Bunch TJ, Gupta D. Smart Wearables for Cardiac Monitoring-Real-World Use beyond Atrial Fibrillation. Sensors (Basel) 2021;21:2539. [PMID: 33916371 DOI: 10.3390/s21072539] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
34 Dehkordi P, Khosrow-Khavar F, Di Rienzo M, Inan OT, Schmidt SE, Blaber AP, Sørensen K, Struijk JJ, Zakeri V, Lombardi P, Shandhi MMH, Borairi M, Zanetti JM, Tavakolian K. Comparison of Different Methods for Estimating Cardiac Timings: A Comprehensive Multimodal Echocardiography Investigation. Front Physiol 2019;10:1057. [PMID: 31507437 DOI: 10.3389/fphys.2019.01057] [Cited by in Crossref: 12] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
35 Yang C, Ojha BD, Aranoff ND, Green P, Tavassolian N. Classification of aortic stenosis using conventional machine learning and deep learning methods based on multi-dimensional cardio-mechanical signals. Sci Rep 2020;10:17521. [PMID: 33067495 DOI: 10.1038/s41598-020-74519-6] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
36 Daskalaki E, Parkinson A, Brew-Sam N, Hossain MZ, O'Neal D, Nolan CJ, Suominen H. The Potential of Current Noninvasive Wearable Technology for the Monitoring of Physiological Signals in the Management of Type 1 Diabetes: Literature Survey. J Med Internet Res 2022;24:e28901. [PMID: 35394448 DOI: 10.2196/28901] [Reference Citation Analysis]
37 Morra S, Hossein A, Rabineau J, Gorlier D, Racape J, Migeotte PF, van de Borne P. Assessment of left ventricular twist by 3D ballistocardiography and seismocardiography compared with 2D STI echocardiography in a context of enhanced inotropism in healthy subjects. Sci Rep 2021;11:683. [PMID: 33436841 DOI: 10.1038/s41598-020-79933-4] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
38 Aydemir VB, Nagesh S, Shandhi MMH, Fan J, Klein L, Etemadi M, Heller JA, Inan OT, Rehg JM. Classification of Decompensated Heart Failure From Clinical and Home Ballistocardiography. IEEE Trans Biomed Eng 2020;67:1303-13. [PMID: 31425011 DOI: 10.1109/TBME.2019.2935619] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 2.3] [Reference Citation Analysis]
39 Stuckey TD, Gammon RS, Goswami R, Depta JP, Steuter JA, Meine FJ 3rd, Roberts MC, Singh N, Ramchandani S, Burton T, Grouchy P, Khosousi A, Shadforth I, Sanders WE Jr. Cardiac Phase Space Tomography: A novel method of assessing coronary artery disease utilizing machine learning. PLoS One 2018;13:e0198603. [PMID: 30089110 DOI: 10.1371/journal.pone.0198603] [Cited by in Crossref: 8] [Cited by in F6Publishing: 7] [Article Influence: 2.0] [Reference Citation Analysis]
40 Quesada O, Shandhi MMH, Beach S, Dowling S, Tandon D, Heller J, Etemadi M, Roy S, Gonzalez Velez JM, Inan OT, Klein L. Use of Ballistocardiography to Monitor Cardiovascular Hemodynamics in Preeclampsia. Womens Health Rep (New Rochelle) 2021;2:97-105. [PMID: 33937907 DOI: 10.1089/whr.2020.0127] [Reference Citation Analysis]
41 Wolsk E, Gustafsson F. When Making Your Bed Feels Like Running a Marathon: Understanding Exercise Limitation in Heart Failure. Circ Heart Fail 2020;13:e007993. [PMID: 33201751 DOI: 10.1161/CIRCHEARTFAILURE.120.007993] [Reference Citation Analysis]
42 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;8:4925-32. [PMID: 34687162 DOI: 10.1002/ehf2.13522] [Reference Citation Analysis]
43 Witt D, Kellogg R, Snyder M, Dunn J. Windows Into Human Health Through Wearables Data Analytics. Curr Opin Biomed Eng 2019;9:28-46. [PMID: 31832566 DOI: 10.1016/j.cobme.2019.01.001] [Cited by in Crossref: 50] [Cited by in F6Publishing: 28] [Article Influence: 16.7] [Reference Citation Analysis]
44 Shandhi MMH, Bartlett WH, Heller JA, Etemadi M, Young A, Plotz T, Inan OT. Estimation of Instantaneous Oxygen Uptake During Exercise and Daily Activities Using a Wearable Cardio-Electromechanical and Environmental Sensor. IEEE J Biomed Health Inform 2021;25:634-46. [PMID: 32750964 DOI: 10.1109/JBHI.2020.3009903] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
45 Zia J, Kimball J, Hersek S, Inan OT. Modeling Consistent Dynamics of Cardiogenic Vibrations in Low-Dimensional Subspace. IEEE J Biomed Health Inform 2020;24:1887-98. [PMID: 32175880 DOI: 10.1109/JBHI.2020.2980979] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
46 Shandhi MMH, Semiz B, Hersek S, Goller N, Ayazi F, Inan OT. Performance Analysis of Gyroscope and Accelerometer Sensors for Seismocardiography-Based Wearable Pre-Ejection Period Estimation. IEEE J Biomed Health Inform 2019;23:2365-74. [PMID: 30703050 DOI: 10.1109/JBHI.2019.2895775] [Cited by in Crossref: 24] [Cited by in F6Publishing: 11] [Article Influence: 8.0] [Reference Citation Analysis]