Analysis of Energy Concentration of the Speech, EEG, and ECG Signals in Healthcare Applications—A Survey

Balaji, M. Sundar Prakash; Jayabharathy, R.; Jegadeesan, Nirmala; Devasena, L.; Babu, G. Venkat; Elamaran, V.; Venkatraman, Vishwesh

doi:10.1166/jmihi.2020.2870

Cited by 10 publications

(1 citation statement)

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“…Compression reduces the amount of bandwidth necessary for wireless communication, while low-power wireless technology helps to save money. It also reduces the amount of space required to store ECG data [ 35 – 37 ].…”

Section: Methodsmentioning

confidence: 99%

Reconfigurable Architectures with High-Frequency Noise Suppression for Wearable ECG Devices

Jerard

Thilagaraj

Pandiaraj

et al. 2021

Journal of Healthcare Engineering

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Recent advances in electronics and microelectronics have aided the development of low-cost devices that are widely used as well-being or preventive monitoring devices by many people. Remote health monitoring, which includes wearable sensors, actuators, and modern communication and information systems, offers effective programs that allow people to live peacefully in their own homes while also being protected in some way. High-frequency noise, power-line interface, and baseline drift are prevalent during the data-acquisition system of an ECG signal, and they can limit signal understanding. They (noises) must be isolated in order to provide an appropriate diagnostic of the patient. When removing high-frequency components (noise) from an ECG signal with an FIR filter, the critical path delay increases considerably as the filter's duration increases. To reduce high-frequency noise, simple moving average filters with pipelining and look-ahead transformation techniques are extensively used in this study. With the use of pipelining and look-ahead techniques, the only objective is to increase the clock speed of the designs. The moving average filters (conventional and proposed) were created on an Altera Cyclone IV FPGA EP4CE115F29C7 chip using the Quartus II software v13.1 tool. Finally, performance metrics such logic elements, clock speed, and power consumption were compared and studied thoroughly. The recursive pipelined 8-tap MA filter with look-ahead approach outperforms the other designs (685.48 MHz) in this investigation.

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Section: Methodsmentioning

confidence: 99%