Assessment of conductive textile-based electrocardiogram measurement for the development of a lonely death prevention system

Kwon MH, Kwon YE. A Study on the subjectivity of the elderly who live alone caregivers in perception of lonely death. Korean J Adult Nurs. 2012;24(6):647–58. https://doi.org/10.7475/kjan.2012.24.6.647.

Article  MATH  Google Scholar 

Králová J. What is social death? Contemp Soc Sci. 2015;10(3):235–48. https://doi.org/10.1080/21582041.2015.1114407.

Article  MATH  Google Scholar 

Caswell G, O’Connor M. Agency in the context of social death: dying alone at home. In: Králová J, Walter T(eds.) Social death: Questioning the life-death boundary; Routledge: 2018. pp. 27–399

Borgstrom, E. Social death in end-of-life care policy. In: Social death: Questioning the life-death boundary; Routledge: 2018. pp. 50–61.

Lee J, Cohen PN, Lee Mj, Woo H. Lone death in South Korea: Exploring community level factors on lone death in South Korea.

Kim HS. Analysis of dying alone among media reports. Asia pac J Psychol Couns. 2017;1:3540. https://doi.org/10.21742/apjpc.2017.1.1.06.

Article  MATH  Google Scholar 

Yeung, J.S., Yoonjung. South Korea’s middle aged men are dying ‘lonely deaths’. Available online: https://edition.cnn.com/2022/12/18/asia/south-korea-godoksa-lonely-death-intl-hnk-dst/index.html Accessed on 2 Apr.

Dey R, Samanta PK, Chokda RP, De BP, Appasani B, Srinivasulu A, Philibert N. Graphene-based electrodes for ECG signal monitoring: fabrication methodologies, challenges and future directions. Cogent Eng. 2023;10:2246750. https://doi.org/10.1080/23311916.2023.2246750.

Article  Google Scholar 

Wartzek T, Lammersen T, Eilebrecht B, Walter M, Leonhardt S. Triboelectricity in capacitive biopotential measurements. IEEE Trans Biomed Eng. 2010;58:1268–77. https://doi.org/10.1109/TBME.2010.2100393.

Article  Google Scholar 

Lulai LM, Guo S, Worswick S, DeLeo VA, Adler BL. Contact dermatitis in the inpatient hospital setting–an updated review of the literature. Curr Dermatol Rep. 2022;11:179–93. https://doi.org/10.1007/s13671-022-00366-5.

Article  Google Scholar 

Myers J, Arena R, Franklin B, Pina I, Kraus WE, McInnis K, Balady GJ. Recommendations for clinical exercise laboratories: a scientific statement from the American Heart Association. Circulation. 2009;119:3144–61. https://doi.org/10.1161/CIRCULATIONAHA.109.192520.

Article  Google Scholar 

Sandau KE, Funk M, Auerbach A, Barsness GW, Blum K, Cvach M, Lampert R, May JL, McDaniel GM, Perez MV. Update to practice standards for electrocardiographic monitoring in hospital settings: a scientific statement from the American Heart Association. Circulation. 2017;136:e273–344. https://doi.org/10.1161/CIR.0000000000000527.

Article  Google Scholar 

Heo JS, Eom J, Kim YH, Park SK. Recent progress of textile-based wearable electronics: a comprehensive review of materials, devices, and applications. Small. 2018;14:1703034. https://doi.org/10.1002/smll.201703034.

Article  MATH  Google Scholar 

Ismar E, KurşunBahadir S, Kalaoglu F, Koncar V. Futuristic clothes: Electronic textiles and wearable technologies. Global Chall. 2020;4:1900092. https://doi.org/10.1002/gch2.201900092.

Article  MATH  Google Scholar 

Lee I, Shin S, Jang Y, Song Y, Jeong JW, Kim S. Comparison of conductive fabric sensor and Ag-AgCl sensor under motion artifacts. In: Proceedings of the 2008 30th annual international conference of the IEEE engineering in medicine and biology society, 2008. pp. 1300–3.

Lee E, Kim I, Liu H, Cho G. Exploration of AgNW/PU nanoweb as ECG textile electrodes and comparison with Ag/AgCl electrodes. Fibers Polym. 2017;18:1749–53. https://doi.org/10.1007/s12221-017-7410-6.

Article  MATH  Google Scholar 

Qin Q, Li J, Yao S, Liu C, Huang H, Zhu Y. Electrocardiogram of a silver nanowire based dry electrode: quantitative comparison with the standard Ag/AgCl gel electrode. IEEE Access. 2019;7:20789–800. https://doi.org/10.1109/access.2019.2897590.

Article  Google Scholar 

Malik M. Heart rate variability: Standards of measurement, physiological interpretation, and clinical use: Task force of the European Society of Cardiology and the North American Society for Pacing and Electrophysiology. Ann Noninvasive Electrocardiol. 1996;1:151–81. https://doi.org/10.1111/j.1542-474x.1996.tb00275.x.

Article  MATH  Google Scholar 

Pan J, Tompkins WJ. A real-time QRS detection algorithm. IEEE trans biomed Eng. 1985. https://doi.org/10.1109/tbme.1985.325532.

Article  MATH  Google Scholar 

Schafer RW. What is a Savitzky-Golay filter?[lecture notes]. IEEE Signal Process Mag. 2011;28:111–7. https://doi.org/10.1109/msp.2011.941097.

Article  MATH  Google Scholar 

Shaffer F, Ginsberg JP. An overview of heart rate variability metrics and norms. Front Pub Heal. 2017. https://doi.org/10.3389/fpubh.2017.00258.

Article  MATH  Google Scholar 

Hamilton PS, Tompkins WJ. Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. IEEE Trans Biomed Eng. 1986;BME-33(12):1157–65. https://doi.org/10.1109/TBME.1986.325695.

Article  Google Scholar 

Woo MA, Stevenson WG, Moser DK, Middlekauff HR. Complex heart rate variability and serum norepinephrine levels in patients with advanced heart failure. J Am Coll Cardiol. 1994;23:565–9. https://doi.org/10.1016/0735-1097(94)90737-4.

Article  Google Scholar 

Rajendra Acharya U, Suri JS, Spaan JAE, Krishnan SM, editors. Advances in cardiac signal processing. Berlin, Heidelberg: Springer Berlin Heidelberg; 2007. https://doi.org/10.1007/978-3-540-36675-1.

Book  MATH  Google Scholar 

Ciccone AB, Siedlik JA, Wecht JM, Deckert JA, Nguyen ND, Weir JP. Reminder: RMSSD and SD1 are identical heart rate variability metrics. Muscle Nerve. 2017;56:674–8. https://doi.org/10.1002/mus.25573.

Article  Google Scholar 

Tulppo MP, Makikallio TH, Seppänen T, Laukkanen RT, Huikuri HV. Vagal modulation of heart rate during exercise: effects of age and physical fitness. Am J Physiol Heart Circ Physiol. 1998;274:H424–9. https://doi.org/10.1152/ajpheart.1998.274.2.H424.

Article  Google Scholar 

Brennan M, Palaniswami M, Kamen P. Poincaré plot interpretation using a physiological model of HRV based on a network of oscillators. Am J Physiol Heart Circ Physiol. 2002;283:H1873–86. https://doi.org/10.1152/ajpheart.00405.2000.

Article  Google Scholar 

Bansal D, Khan M, Salhan A. A review of measurement and analysis of heart rate variability. In: Proceedings of the 2009 international conference on computer and automation engineering, 2009. pp. 243–6.

Chatterjee S, Thakur RS, Yadav RN, Gupta L, Raghuvanshi DK. Review of noise removal techniques in ECG signals. IET Signal Proc. 2020;14:569–90. https://doi.org/10.1049/iet-spr.2020.0104.

Article  Google Scholar 

Liu X, Yang J, Zhu X, Zhou S, Wang H, Zhang H. A novel R-peak detection method combining energy and wavelet transform in electrocardiogram signal. Biomed Eng Appl Basis Commun. 2014;26:1450007. https://doi.org/10.4015/s1016237214500070.

Article  MATH  Google Scholar 

Kaya Y, Pehlivan H, Tenekeci M. Effective ECG beat classification using higher order statistic features and genetic feature selection. Biomed Res India. 2017;28(17):7594–603.

MATH  Google Scholar 

Sharma T, Sharma KK. QRS complex detection in ECG signals using locally adaptive weighted total variation denoising. Comput Biol Med. 2017;87:187–99. https://doi.org/10.1016/j.compbiomed.2017.05.027.

Article  MATH  Google Scholar 

Lo L-W, Zhao J, Aono K, Li W, Wen Z, Pizzella S, Wang Y, Chakrabartty S, Wang C. Stretchable sponge electrodes for long-term and motion-artifact-tolerant recording of high-quality electrophysiologic signals. ACS Nano. 2022;16:11792–801. https://doi.org/10.1021/acsnano.2c04962.

Article  Google Scholar 

Sekitani T, Yokota T, Kuribara K, Kaltenbrunner M, Fukushima T, Inoue Y, Sekino M, Isoyama T, Abe Y, Onodera H. Ultraflexible organic amplifier with biocompatible gel electrodes. Nat Commun. 2016;7:11425. https://doi.org/10.1038/ncomms11425.

Article  Google Scholar 

Zhang N, Yue L, Xie Y, Samuel OW, Omisore OM, Pei W, Xing X, Lin C, Zheng Y, Wang L. A novel antibacterial membrane electrode based on bacterial cellulose/polyaniline/AgNO3 composite for bio-potential signal monitoring. IEEE J transl Eng Health Med. 2018;6:1–10. https://doi.org/10.1109/jtehm.2018.2863388.

Article  Google Scholar 

Satti AT, Park J, Park J, Kim H, Cho S. Fabrication of parylene-coated microneedle array electrode for wearable ECG device. Sensors. 2020;20:5183. https://doi.org/10.3390/s20185183.

Article  MATH  Google Scholar 

Rajendra Acharya U, Paul Joseph K, Kannathal N, Lim CM, Suri JS. Heart rate variability: a review. Med Biol Eng Compu. 2006;44:1031–51. https://doi.org/10.1007/s11517-006-0119-0.

Article  Google Scholar 

Ziegler D, Piolot R, Strassburger K, Lambeck H, Dannehl K. Normal ranges and reproducibility of statistical, geometric, frequency domain, and non-linear measures of 24-hour heart rate variability. Horm Metab Res. 1999;31:672–9. https://doi.org/10.1055/s-2007-978819.

Article  Google Scholar 

Roy B, Ghatak S. Nonlinear methods to assess changes in heart rate variability in type 2 diabetic patients. Arq Bras Cardiol. 2013;101:317–27. https://doi.org/10.5935/abc.20130181.

Article  MATH  Google Scholar 

Ishijima M. Cardiopulmonary monitoring by textile electrodes without subject-awareness of being monitored. Med Biol Eng Compu. 1997;35:685–90. https://doi.org/10.1007/bf02510978.

Article  MATH  Google Scholar 

Devot S, Bianchi AM, Naujoka E, Mendez MO, Brauers A, Cerutti S. Sleep monitoring through a textile recording system. In: Proceedings of the 2007 29th annual international conference of the IEEE engineering in medicine and biology society, 2007. pp. 2560–3.

Mirza M, Shen W-K, Sofi A, Jahangir A, Mori N, Tajik AJ, Jahangir A. Frequent periodic leg movement during sleep is associated with left v

Comments (0)

No login
gif