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Quality of One-channel Telemetric ECG Sensor Signal in Maximum Exercise Stress Tests

Abstract

The aim of this study was to evaluate the quality of the ECG signal, obtained from a telemetric body-sensor device during a maximum stress test on an ergometer. Twenty-three subjects, 13 males, were included in the study (20.56±1.19 years). Two different sensor positions were verified on each subject by the concurrent use of two ECG sensors. Each subject participated in four exercise stress tests: two on a treadmill and two on a cycle ergometer. In the first test, both sensors were attached to self-adhesive skin electrodes on the body, while in the second test the sensors were additionally fixed with self-adhesive tapes. The measurements were compared on both ergometers, in terms of the ECG sensors’ positions and the methods used for the sensors’ fixation. The results showed a significant difference in the running speed that provides an assessable ECG signal between the non-fixed and the fixed sensors at position left inferior (p = 0.000), as well as between the positions left inferior and left superior in the first (p = 0.019), and in the second test (p = 0.000) on the treadmill. On the cycle ergometer the differences were significant between the positions left inferior and left superior in the first (p = 0.000), and the second test (p = 0.003), and between the tests with fixed and non-fixed sensors in the position left superior (p = 0.011). The study confirms that ECG sensors could be used for maximal exercise stress tests in laboratories, especially on a cycle ergometer, and that they present a great potential for future use of ECG sensors during physical activity.

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Image Segmentation of Thermal Waving Inspection based on Particle Swarm Optimization Fuzzy Clustering Algorithm

for crisp and fuzzy cluster. Pattern Recognition , 37, 487-501. [14] Liu, X.L. (2006). Research on Fuzzy-Clustering-Based Method of Image Segmentation . Master dissertation of Hefei University of Technology, Anhui Hefei, China. [15] Li, L.L. (2009). Fuzzy C-Means Algorithm and Its Application in Image Segmentation . Master dissertation of Shandong Demonstration University, Shandong Jinan, China. [16] Yang, Z.W., Zhang, W., Wu, C.Q. et al. (2010). Infrared thermography applied to evaluate adhesive quality of missile

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Comparison of Two Experiments Based on a Physical and a Torsion Pendulum to Determine the Mass Moment of Inertia Including Measurement Uncertainties

Systems (2006). Guide to adhesively mounting accelerometers . Technical Report. [19] Joint Committee for Guides in Meteorology. (2008). Evaluation of measurement data —- Guide to the expression of uncertainty in measurement . JCGM 100:2008. [20] Joint Committee for Guides in Meteorology. (2008). Evaluation of measurement data —- Supplement 1 to the “Guide to the expression of uncertainty in measurement” – Propagation of distributions using a Monte Carlo method . JCGM 101:2008. [21] Wübbeler, G., Harris, P.M., Cox, M.G., Elster, C. (2010). A Two

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RFID Tag as a Sensor - A Review on the Innovative Designs and Applications

Transactions on Circuits and Systems II: Express Briefs, 57 (2), 95-99. [71] Rakibet, O.O., Rumens, C.V., Batchelor, J.C., Holder, S.J. (2014). Epidermal passive RFID strain sensor for assisted technologies. IEEE Antennas and Wireless Propagation Letters, 13, 814-817. [72] Rose, D.P., et al. (2015). Adhesive RFID sensor patch for monitoring of sweat electrolytes. IEEE Transactions on Biomedical Engineering, 62 (6), 1457-1465. [73] Wickramasinghe, A., Ranasinghe, D.C. (2015). Ambulatory monitoring using passive computational

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