High-Frequency Noise Removal on Corrupted ECG Signal Using Exponential Averagers

Raj, R. Mohan; Thanapal, P.; Saravanan, S.; Balaji, M. Sundar Prakash; Elamaran, V.

doi:10.1007/978-981-16-5048-2_4

Cited by 3 publications

(2 citation statements)

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“…It is commonly used for prototyping and functional verification of ASICs (application-specific integrated circuits). FPGAs are significantly faster in applications where simultaneous computing is required for various processes due to their unique parallel computing capability [ 13 , 33 ].…”

Section: Methodsmentioning

confidence: 99%

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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%

“…As a result, the IIR portion of the recursive MA filter, as explained below, must be applied to this look-ahead transformation. In the time domain, the integrator portion (1/ z − 1) is given as [ 23 , 33 ]

…”

Section: Methodsmentioning

confidence: 99%