Abstract
Given the numerous technological advances in communication reaching the health sector, the accelerated growth of telemedicine can be observed. This medical practice can be defined by the use of telecommunication means to provide care, health promotion, treatment, information exchange between doctors and researchers, and also for various health research. However, there are still many methodologies that present a large consumption of computational memory as well as slowness in sending medical data. And with that focus, the present research aims to implement discrete event modeling, called CBEDE (Coding of Bits for Entities by Discrete Events) to improve the transmission of medical data by specifying the wide spectrum of health-related themes. The modeling was performed using the MATLAB Simulink environment, where AWGN communication channel models with DQPSK (Differential Quadrature Phase Shift Keying) modulation were developed and analyzed in relation to information consumption medical data in MB (megabytes). The proposal directs a different approach with respect to signal transmission, employing in the discrete domain the effect of discrete entities’ technique in the bit generation step, aiming to increase the information capacity transmission in healthcare systems, showing better memory consumption utilization regards improvement of 95.86%. Since diagnostic health interaction offered by e-health enables digital solutions for faster and better-quality health care, enabling the optimization of healthcare services, generating greater interaction between physician and patient, as well as all agents in system health care, where CBEDE methodology may enable faster and more efficient scheduling of consultations, transmission devices monitoring data from patients, presenting great potential for the transmission of medical data.
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França, R.P., Iano, Y., Monteiro, A.C.B., Arthur, R. (2021). A Methodology for Improving Efficiency in Data Transmission in Healthcare Systems. In: Chakraborty, C., Banerjee, A., Kolekar, M., Garg, L., Chakraborty, B. (eds) Internet of Things for Healthcare Technologies. Studies in Big Data, vol 73. Springer, Singapore. https://doi.org/10.1007/978-981-15-4112-4_3
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DOI: https://doi.org/10.1007/978-981-15-4112-4_3
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