Purpose. To evaluate the clinical applicability of a telemonitoring system: telemetric system for collection and distant surveillance of medical information (TEMEO). Methods. We evaluated 60 patients, applying simultaneously standard Holter ECG and telemonitoring. Two different comparisons were performed: (1) TEMEO ECG with standard 12-lead ECG; (2) TEMEO Holter with standard ECG Holter. Results. We found a very high coincidence rate (99.3%) between TEMEO derived ECGs and standard ECGs. Intraclass correlation coefficient analysis revealed high and significant correlation coefficients regarding average, maximal, and minimal heart rate, % of time in tachycardia, single supraventricular ectopic beats (SVEB), and single and couplets of ventricular ectopic beats (VEB) between Holter ECG and TEMEO derived parameters. Couplets of SVEB were recorded as different by the two monitoring systems, however, with a borderline statistical significance. Conclusions. TEMEO derived ECGs have a very high coincidence rate with standard ECGs. TEMEO patient monitoring provides results that are similar to those derived from a standard Holter ECG. 1. Introduction Telemedicine is a relatively new medical trend which incorporates medicine, telecommunications, and information technologies, providing diagnostic workup, treatment, consulting, and training. It enables a patient to get specialized medical advice 24 hours a day independent of his/her location. Telemedicine has been acknowledged in world-leading countries and there are a large number of clinical trials and even some medical journals devoted entirely to this topic. Most of telemonitoring studies however focus on heart failure population [1–5], about 3500 patients included in total, with different kinds of data transmission. Results from most [1–4], but not all [5], of these studies have shown that telemonitoring can be effective in clinical management of patients. Experience with ECG monitoring is still insufficient. Most of the results come from laboratory tests and small clinical trials [6–16], while data transmission via mobile network is rare. Telemonitoring systems are designed in various ways and adapted to detect and transmit information regarding different clinical parameters. Systems that detect RR intervals and are able to record electrocardiograms (ECG) do not yet have a large clinical application. After performing a literature search we were not able to find a clinical study comparing such a system with the gold standard for ambulatory ECG monitoring—Holter ECG system. Considering this and some existing
References
[1]
M. Clarke, A. Shah, and U. Sharma, “Systematic review of studies on telemonitoring of patients with congestive heart failure: a meta-analysis,” Journal of Telemedicine and Telecare, vol. 17, no. 1, pp. 7–14, 2011.
[2]
J. Polisena, K. Tran, K. Cimon et al., “Home telemonitoring for congestive heart failure: a systematic review and meta-analysis,” Journal of Telemedicine and Telecare, vol. 16, no. 2, pp. 68–76, 2010.
[3]
S. C. Inglis, R. A. Clark, F. A. McAlister et al., “Structured telephone support or telemonitoring programmes for patients with chronic heart failure.,” Cochrane Database of Systematic Reviews, vol. 8, p. CD007228, 2010.
[4]
A. Giordano, S. Scalvini, E. Zanelli et al., “Multicenter randomised trial on home-based telemanagement to prevent hospital readmission of patients with chronic heart failure,” International Journal of Cardiology, vol. 131, no. 2, pp. 192–199, 2009.
[5]
F. Koehler, S. Winkler, M. Schieber et al., “Impact of remote telemedical management on mortality and hospitalizations in ambulatory patients with chronic heart failure: the telemedical interventional monitoring in heart failure study,” Circulation, vol. 123, no. 17, pp. 1873–1880, 2011.
[6]
M. Braecklein, I. Tchoudovski, C. Moor, K. Egorouchkina, L. P. Pang, and A. Bolz, “Wireless telecardiological monitoring system for the homecare area,” in Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE-EMBS '05), vol. 4, pp. 3793–3795, September 2005.
[7]
Y. Zhang, J. Bai, X. Zhou et al., “First trial of home ECG and blood pressure telemonitoring system in Macau,” Telemedicine Journal, vol. 3, no. 1, pp. 67–72, 1997.
[8]
B. Wu, Y. Zhuo, X. Zhu, Q. Yan, L. Zhu, and G. Li, “A novel mobile ECG telemonitoring system,” in Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE-EMBS '05), vol. 4, pp. 3818–3821, September 2005.
[9]
Q. Fang, F. Sufi, and I. Cosic, “A mobile device based ECG analysis system,” in Data Mining in Medical and Biological Research, E. Giannopoulou, Ed., pp. 209–226, I-Tech Education and Publishing KG, Vienna, Austria, 2008.
[10]
D. Vukajlovic, B. Bojovic, L. Hadzievski, S. George, I. Gussak, and D. Panescu, “Wireless remote monitoring of atrial fibrillation using reconstructed 12-lead ECGs,” in Proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '10), vol. 1, pp. 1113–1118, arg, September 2010.
[11]
J. Tomcsányi and P. Bezzeg, “Home ECG monitoring of high-risk post myocardial infarction patients,” Orvosi Hetilap, vol. 150, no. 21, pp. 985–988, 2009.
[12]
C. Glaros, D. I. Fotiadis, A. Likas, et al., “A wearable intelligent system for monitoring health condition and rehabilitation of running athletes,” in Proceedings of the Annual International Conference of the IEEE Conference on Information Technology Applications in Biomedicine, pp. 276–279, 2003.
[13]
K. Hung and Y. T. Zhang, “Implementation of a WAP-based telemedicine system for patient monitoring,” IEEE Transactions on Information Technology in Biomedicine, vol. 7, no. 2, pp. 101–107, 2003.
[14]
G. Yang, Y. Cao, J. Chen, H. Tenhunen, and L. R. Zheng, “An Active-Cable connected ECG monitoring system for ubiquitous healthcare,” in Proceedings of the 3rd International Conference on Convergence and Hybrid Information Technology (ICCIT '08), pp. 392–397, November 2008.
[15]
M. B. M. Amien and J. Lin, “Dual-mode continuous arrhythmias telemonitoring system,” Journal of Applied Sciences, vol. 7, no. 7, pp. 965–971, 2007.
[16]
T. Sakamoto, D. Wei, and K. Hamao, “A study of ECG telemonitoring system using mobile internet connections,” in Proceedings of the 4th International Conference on Computer and Information Technology (CIT '04), pp. 593–597, September 2004.
[17]
I. I. Christov, “Real time electrocardiogram qrs detection using combined adaptive threshold,” BioMedical Engineering, vol. 3, no. 1, p. 28, 2004.
[18]
I. Christov, I. Dotsinsky, I. Simova, R. Prokopova, E. Trendafilova, and S. Naydenov, “Dataset of manually measured QT intervals in the electrocardiogram,” BioMedical Engineering Online, vol. 5, p. 31, 2006.
[19]
I. Christov, “Assessment of the performance of the adaptive thresholding algorithm for QRS detection with the use of AHA database,” Bioautomation, vol. 6, pp. 27–37, 2007.
