As the socio-economic environment has changed, the number of single and elderly households has increased, and the demand for maintaining a long and healthy life has been increased by continuously monitoring and managing physical conditions against unexpected accidents that may occur when living alone at home. In response to these demands, it is necessary to develop services that provide personalized healthcare services by recording and analyzing living patterns and biometric information in an unconscious way. In this paper, we propose an accuracy improvement method using similarity and Signal-to-noise ratio analysis for BCG measurement method using piezo sensors and a system for continuous personal health monitoring in home without user awareness. Heart rate and respiration rate were derived using the acquired BCG data, and the biometric information is stored symmetrically for personal information security.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Lim CY (2018) Realization of gait pattern detection and bio-signal monitoring system using smart pad of pressure sensor type. J Inst Electron Eng Korea 1:85–86
Gubner RS, Rodstein M, Ungerleider HE (1953) Ballistocardiography: An appraisal of technic, physiologic principles, and clinical value. Circulation 7(2):268–286
Pinheiro E, Postolache O, Girão P (2010) “Theory and developments in an unobtrusive cardiovascular system representation: ballistocardiography. The open Biomed Eng J 4:201
Inan OT, et al (2015) Systems and methods for monitoring heart function. U.S. Patent 9215991, Dec 22, 2015
Da He D, Winokur ES, Sodini CG (2011) A continuous, wearable, and wireless heart monitor using head ballistocardiogram (BCG) and head electrocardiogram (ECG). In: 2011 Annual International Conference of the IEEE engineering in medicine and biology society, 2011
Inan OT et al (2009) Non-invasive cardiac output trending during exercise recovery on a bathroom-scale-based ballistocardiograph. Physiol Meas 30(3):261
Etemadi M et al (2011) Rapid assessment of cardiac contractility on a home bathroom scale. IEEE Trans Inf Technol Biomed 15(6):864–869
Javaid AQ, Ashouri H, Inan OT (2016) Estimating systolic time intervals during walking using wearable ballistocardiography. In: 2016 IEEE-EMBS International Conference on biomedical and health informatics (BHI), 2016
Starr I et al (1939) Studies on the estimation of cardiac ouptut in man, and of abnormalities in cardiac function, from the heart’s recoil and the blood’s impacts; the ballistocardiogram. Am J Physiol-Legacy Content 127(1):1–28
Starr I (1965) Progress towards a physiological cardiology: a second essay on the ballistocardiogram. Ann Intern Med 63(6):1079–1105
Tadi MJ, et al (2016) Gyrocardiography: A new non-invasive approach in the study of mechanical motions of the heart. Concept, method and initial observations. In: 2016 38th Annual International Conference of the IEEE engineering in medicine and biology society (EMBC), 2016.
Lee J et al (2019) Design of a symmetry protocol for the efficient operation of IP cameras in the IoT environment. Symmetry 11(3):361
Alametsä J, et al (2004) The potential of EMFi sensors in heart activity monitoring. In: Proc. 2nd OpenECG Workshop: integration ECG into the EHR interoperability of ECG Device Syst. Berlin, Germany, 2004
Redmond SJ, Heneghan C (2006) Cardiorespiratory-based sleep staging in subjects with obstructive sleep apnea. IEEE Trans Biomed Eng 53(3):485–496
Alihanka J, Vaahtoranta K, Saarikivi I (1981) A new method for long-term monitoring of the ballistocardiogram, heart rate, and respiration. Am J Physiol-Regul Integr Comp Physiol 240(5):R384–R392
Paalasmaa J, Waris M, Toivonen H, Leppäkorpi L, Partinen M (2012) Unobtrusive online monitoring of sleep at home. In: 34th IEEE EMBC, August 28–September 1, San Diego, USA, 2012
Lekkala J, Tuppurainen J, Paajanen M (2003) Material and operational properties of large area membrane type sensors for smart environments. In: XVII IMEKO World Congress, June 22–27, Dubrovnik, Croatia, 2003
Vehkaoja A, Kontunen A, Lekkala J (2015) Effects of sensor type and sensor location on signal quality in bed mounted ballistocardiographic heart rate and respiration monitoring. In: Proc. Of 37th Annu. Int. Conf. of IEEE engineering in medicine and biological society, Milano, Italy, 2015
Przystup P, Bujnowski A, Ruminski J, Wtorek J (2013) A multisensor detector of a sleep apnea for using at home. In: 2013 6th International Conference on Human System Interactions, HSI 2013.
Brink M, Müller CH, Schierz C (2006) Contact-free measurement of heart rate, respiration rate, and body movements during sleep. Behav Res Methods 38(3):511–521
Juha MK, Mark G, Juha P (2012) Multichannel bed pressure sensor for sleep monitoring. In: IEEE 2012 Computing in Cardiology, 9–12 Sept., Krakow, Poland, 2012
Kortelainen J, Virkkala J (2007) FFT averaging of multichannel BCG signals from bed mattress sensor to improve estimation of heart beat interval. In: 29th IEEE EMBC, August 23–26, Lyon, France, 2007
Brüser C, Stadlthanner K, de Waele S, Leonhardt S (2011) Adaptive beat-to-beat heart rate estimation in ballistocardiograms. IEEE Trans Inf Technol Biomed 15(5):778–786
Noh SW (2014) Applications of new ballistocardiograph systems. Ph.D. Dissertation. University of Seoul National University, KR., 2014
Sörnmo L, Laguna P (2005) ECG signal processing. Bioelectr Signal Process Cardiac Neurol Appl 1(1):453–566
Pan J, Tompkins WJ (1985) A real-time QRS detection algorithm. IEEE Trans Biomed Eng 32(3):230–236
This work was supported by the Community business revitalization business Program (P0002366, "Development of Modular ICT Healthcare Open Platform for Social and Economic Enterprise Scale-up") funded By the Ministry of Trade, Industry & Energy (MOTIE, Korea)
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Yang, C., Ku, G.W., Lee, JG. et al. Improving the Accuracy of Biosignal Analysis Using BCG by Applying a Signal-to-Noise Ratio and Similarity-Based Channel Selection Algorithm. J. Electr. Eng. Technol. 16, 1043–1050 (2021). https://doi.org/10.1007/s42835-020-00601-8
- Heart/respiration rate
- Channel selection