Abstract
Electrocardiogram (ECG) signal provides a lot of information about the cardiac functions through its patterns displayed. Besides to use ECG for cardiovascular diseases diagnostic function, the use of ECG has extended to wider areas such as monitoring the performance of athletes, lie detections, human authentication, stresses and emotion measurement. Moreover, from the ECG signal, the heart rate (HR), heart rate variability (HRV) and R-R intervals can be obtained and relate these physiological response value with human physical activities. Thus, the using of an electrocardiogram (ECG) device or wearable ECG monitor to diagnose the heart condition for the training performance evaluation is desirable. The result is recorded and assessed by analyzer (prototype of this project) for diagnosis. This work employs the Metabolic Equivalent Task (MET) to perform the level of physiological activities from volunteers. Any deviation from target heart rate value indicate the current physiological condition proportional to result of training level (either achieved the target already or need to add more the intensity, load, and duration of training). Thus, this work will assess and evaluate the proposed physical activity performance based on the assessment of ECG signal during exercise.
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References
Price DD How to read an Electrocardiogram (ECG). Basic Principles of the ECG, 20–25, Apr 2012
Mary Boudreau Conover (1996) Wellems syndrome in understanding electrocardiography, Mosby
Kin A (2000) ECG signal related with cardiac activity
Genovesis S, Zaccaria D (2007) Effects of exercise training on heart rate. Europace 9(1):55–60
Moody GB (1992) ECG-based indices of physical activity
Gupta N, Gupta V, Gupta K (2014) A study of effect of physical activity on autonomic functions assessed by frequency domain of HRV in healthy young males. Int J Basic Appl Med Sci 4(3):44–48
Christianne de Faria Coelho-Ravagnani Estimation of the metabolic equivalent (MET) of an exercise protocol. Exer Sport Sci 19
Rompelman O, Janssen RJ (1982) Use of phase spectral information in assessment of frequency content of ECG waveform. 129:679
Jaanus Lass KM (1997) Measurement of correlation between heart rate and physiological parameter variations
Samuel Kim MLL (2011) Modeling high level description of real life physical activities using multimodal sensor signal
Douglas C. Montgomery, George C. Runger (2007) Engineering Statistics, Wiley
Vainoras A, Jurkonis V (2008) Complexity assessment of ECG RR interval. In: Computers in cardiology, 2008
Chan HL, Lin CH, Ko YL (2003) Segmentation of heart rate variability in different physical activities
Durfee W (2011) Arduino Microcontroller Guide, University of Minnesota
Suzuken Co.Ltd, Kenz-cardico 302 Operation Manual, Japan
Malik D C++ Programming From Problem Analysis to Program Design Course Technology, Cengage Learning, Massachusetts
Advanced circuits Inc. (2009) Building a printed circuit board
Acknowledgments
This work is sponsored by Multi-Disciplinary Research (MDR) Vot: U091, Universiti Tun Hussein Onn Malaysia.
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Ibrahim, N., Ann, C.W., Sari, S. (2018). Analysis on MET Value Due to the Relation Between Echocardiogram (ECG) Signal and Human Physical Activities. In: Vo Van, T., Nguyen Le, T., Nguyen Duc, T. (eds) 6th International Conference on the Development of Biomedical Engineering in Vietnam (BME6) . BME 2017. IFMBE Proceedings, vol 63. Springer, Singapore. https://doi.org/10.1007/978-981-10-4361-1_5
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DOI: https://doi.org/10.1007/978-981-10-4361-1_5
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