REFERENCES
1. Kubicek WG, Patterson RP, Witsoe DA. Impedance cardiography as a noninvasive method of monitoring cardiac function and other parameters of the cardiovascular system. Ann N Y Acad Sci. 2006;170:724-32.
2. Lababidi Z, Ehmke DA, Durnin RE, Leaverton PE, Lauer RM. The first derivative thoracic impedance cardiogram. Circulation. 1970;41:651-8.
3. Sherwood(chair) A, Allen MT, Fahrenberg J, Kelsey RM, Lovallo WR, Van Doornen LJ. Methodological guidelines for impedance cardiography. Psychophysiology. 2007;27:1-23.
4. Scholte NTB, Van Ravensberg AE, Shakoor A, et al. A scoping review on advancements in noninvasive wearable technology for heart failure management. NPJ Digit Med. 2024;7:279.
5. Petek BJ, Al-Alusi MA, Moulson N, et al. Consumer wearable health and fitness technology in cardiovascular medicine: JACC state-of-the-art review. J Am Coll Cardiol. 2023;82:245-64.
6. Jamieson A, Chico TJA, Jones S, Chaturvedi N, Hughes AD, Orini M. A guide to consumer-grade wearables in cardiovascular clinical care and population health for non-experts. NPJ Cardiovasc Health. 2025;2:44.
7. Bernstein DP. Impedance cardiography: pulsatile blood flow and the biophysical and electrodynamic basis for the stroke volume equations. J Electr Bioimpedance. 2009;1:2-17.
8. Árbol JR, Perakakis P, Garrido A, Mata JL, Fernández-Santaella MC, Vila J. Mathematical detection of aortic valve opening (B point) in impedance cardiography: A comparison of three popular algorithms. Psychophysiology. 2016;54:350-7.
9. Trybek P, Sobotnicka E, Wawrzkiewicz-Jałowiecka A, et al. A new method of identifying characteristic points in the impedance cardiography signal based on empirical mode decomposition. Sensors. 2023;23:675.
10. Pan J, Tompkins WJ. A real-time QRS detection algorithm. IEEE Trans Biomed Eng. 1985;BME-32:230-6.
11. Fuller HD. Evaluation of left ventricular function by impedance cardiography: a review. Prog Cardiovasc Dis. 1994;36:267-73.
12. Karpiel I, Richter-Laskowska M, Feige D, Gacek A, Sobotnicki A. An effective method of detecting characteristic points of impedance cardiogram verified in the clinical pilot study. Sensors. 2022;22:9872.
13. Xie Y, Yu H, Xie Q. Motion impedance cardiography denoising method based on canonical correlation analysis and coherence analysis. Biomed Signal Process Control. 2023;86:105300.
14. Li X, Ni R, Ji Z. ICG signal denoising based on ICEEMDAN and PSO-VMD methods. Phys Eng Sci Med. 2024;47:1547-56.
15. Colominas MA, Schlotthauer G, Torres ME. Improved complete ensemble EMD: a suitable tool for biomedical signal processing. Biomed Signal Process Control. 2014;14:19-29.
16. Dragomiretskiy K, Zosso D. Variational mode decomposition. IEEE Trans Signal Process. 2014;62:531-44.
17. Kumari PD, Singh KM, Mayaluri ZL, et al. A hybrid variational mode decomposition framework for enhanced cardiac output estimation using impedance cardiography. Sci Rep. 2025;15:25784.
18. Pale U, Muller N, Arza A, Atienza D. ReBeatICG: real-time low-complexity beat-to-beat impedance cardiogram delineation algorithm. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC); 2021 Nov 1-5; Mexico. IEEE; 2021. pp. 5618-24.
19. Inan OT, Migeotte P, Park K, et al. Ballistocardiography and seismocardiography: a review of recent advances. IEEE J Biomed Health Inform. 2015;19:1414-27.
20. Bhattacharya S, Santucci F, Jankovic M, et al. Cardiac time intervals under motion using bimodal chest E-tattoos and multistage processing. IEEE Trans Biomed Eng. 2025;72:413-24.
21. Lin DJ, Kimball JP, Zia J, Ganti VG, Inan OT. Reducing the impact of external vibrations on fiducial point detection in seismocardiogram signals. IEEE Trans Biomed Eng. 2022;69:176-85.
22. Shandhi MMH, Fan J, Heller JA, Etemadi M, Klein L, Inan OT. Estimation of changes in intracardiac hemodynamics using wearable seismocardiography and machine learning in patients with heart failure: a feasibility study. IEEE Trans Biomed Eng. 2022;69:2443-55.
23. Zhou Z, Huang J, Li H, et al. Camera seismocardiogram based monitoring of left ventricular ejection time. IEEE Trans Biomed Eng. 2025;72:2609-22.
24. Jiménez-González A. Timing the opening and closure of the aortic valve using a phonocardiogram envelope: a performance test for systolic time intervals measurement. Physiol Meas. 2021;42:025004.
25. Zang J, An Q, Li B, Zhang Z, Gao L, Xue C. A novel wearable device integrating ECG and PCG for cardiac health monitoring. Microsyst Nanoeng. 2025;11:7.
26. Illueca Fernandez E, Couceiro R, Abtahi F, et al. HeartCycle: a comprehensive dataset of synchronized impedance cardiography and echocardiography for accurate hemodynamic predictions (version 1.0.0). PhysioNet. 2025.
27. Savitzky A, Golay MJE. Smoothing and differentiation of data by simplified least squares procedures. Anal Chem. 2002;36:1627-39.
28. Mondal A, Bhattacharya P, Saha G. An automated tool for localization of heart sound components S1, S2, S3 and S4 in pulmonary sounds using Hilbert transform and Heron’s formula. SpringerPlus. 2013;2:512.
29. Thalmayer A, Zeising S, Fischer G, Kirchner J. A robust and real-time capable envelope-based algorithm for heart sound classification: validation under different physiological conditions. Sensors. 2020;20:972.
30. Sakoe H, Chiba S. Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans Acoust Speech Signal Process. 1978;26:43-9.





