RF biomedical signals transmission system for telemedicine applications
Abstract
In this research work, a radio frequency (RF) system under QPSK modulation is developed for the transmission of biomedical signals such as EMG and ECG in the 2 GHz band. The system is implemented through a transceiver that operates in 4G applications through a dual transceiver. The signals are acquired by means of the ECG/EKG acquisition card and surface electrodes, the management and treatment of the signal are carried out in C language, and a quadratic bandpass filter is implemented in the digital modulation on the ARRADIO+SocKit card. The implementation developed is a contribution to Telemedicine work for the post-pandemic era. The system makes a spectral evaluation of the quality of the QAM constellation, as well as the spectral analysis of the invasion of adjacent bands. As future work, it is intended to migrate to 5G in a transceiver that operates in the 3-6 GHz bands.
Downloads
References
Serhani, H. T. Kassabi, E., Ismail, H., Nujum, A., (2020). ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges. Sensors, 20(6):1796, pp. 1-40.
Gamboa, D., Coria, L., Cárdenas, J. R. Ramírez, R., Valle, P. A., (2019). Hardware Implementation of a Non-Linear Observer for a Diabetes Mellitus Type 1 Mathematical Model. Sensors, 23(4), pp. 1475-1486.
Tsai, T., Hong, J., Wang, L., Lee, S., (2012). Low-Power Analog Integrated Circuits for Wireless ECG Acquisition Systems. IEEE Transactions on Information Technology in Biomedicine, 16(5), pp. 907-917.
Hung, K., Yuan-Ting Z., (2003). Implementation of a WAP-based telemedicine system for patient monitoring, IEEE Transactions on Information Technology in Biomedicine, 7(2), pp. 101-107.
Bhalerao, S., Ahmad Ansari, I., Kumar, A., Kumar Jain, D., (2019). A reversible and multipurpose ECG data hiding technique for telemedicine applications, Pattern Recognition Letters, 125, pp. 463-473.
Reyes Crusaley, L. D. , Cárdenas-Valdez, J.R. Vázquez, G. E. García-Ortega, M. de J., Calvillo-Téllez, A., (2019). Sistema de clasificación SVM de señales electromiográficas extraídas en un sistema embebido. Research in Computing Science, 148(2), pp. 135-141.
Cárdenas-Valdez, J. R., Valdez-Luis, D. García-Ortega, M. J., Corral-Domínguez, A. H., Galaviz-Aguilar, J. A., (2020). SVM Classifier and evaluation of muscle power of EMG signals and Python implementation, International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE), pp. 20-22.
Sunitha, N., (2015). Implementation using VHDL of an ECG signal using CSP, International Conference on Circuits, Power and Computing Technologies (ICCPCT-2015), pp. 1-4.
Rudic, B., Schimpf, R. and Borggrefe, M. (2014). Short QT syndrome–review of diagnosis and treatment. Arrhythmia & electrophysiology review, 3(2), pp. 76-79.
Leslie, L., Felmlee, N. (2010). Brugada syndrome. Unmasking a silent killer, Nursing: Spring 2010, 40, pp. 8-10.
Surawicz, B., et, al. (2009). AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: part III: intraventricular conduction disturbances: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society. Endorsed by the International Society for Computerized Electrocardiology, Journal of the American College of Cardiology,53(11), pp. 976-981.
