Design of Digital IIR Filter for Noise Reduction in ECG Signal

Singh, Narendra; Ayub, Shahanaz; Saini, Jitender

doi:10.1109/cicn.2013.45

Cited by 23 publications

(8 citation statements)

References 1 publication

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“…Singh et al [11] applied an IIR Butterworth filter to remove high power noise in the ECG. It is also stated that IIR Butterworth low pass filter offer better result of what IIR filter has to offer and the result shows that the power of filter signal is less as compared to power of noisy signal.…”

Section: Existing Methodology 21related Workmentioning

confidence: 99%

Heart beat peak detection using signal filtering in ECG data

Rexy¹,

Velmani²,

Rajakumar³

2019

IJATEE

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The human heart is the muscular organ that pumps the blood through the circulatory system and paves way for a human to be alive. Human being loss their life if the heart malfunctions. Nowadays the death ratio of human being has been increased due to heart disease. Heart disease is the leading cause of many human deaths. The physical interpretation of the electrical behaviour throughout the cardiac cycle is recorded as electrocardiogram (ECG). ECG is used to measure the rate and rhythm of heartbeats which is the base to identify the heart beat disorders. ECG leads to monitor the heartbeat status and makes way for earlier detection of heart problems. ECG signal is a graphical representation or cardiac activity which helps to identify cardiac diseases [1].

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Section: Existing Methodology 21related Workmentioning

confidence: 99%

Heart beat peak detection using signal filtering in ECG data

Rexy¹,

Velmani²,

Rajakumar³

2019

IJATEE

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“…However, similar high pass filters have a 5 to 10 harmonic effect on the signal. This means that a high pass filter of 0.05 Hz, a lower frequency than the heart muscle, can still affect frequencies up to 5 Hz [22].…”

Section: Designing the High Pass Filtermentioning

confidence: 99%

“…For Windows-based software, the operating system is mainly used to collect data with a high sampling frequency, from 100 Hz to 2133 Hz. The data are processed by MATLAB with more complex algorithms for accurate results [2,21,22].…”

Section: Introductionmentioning

confidence: 99%

Design of a Solar-Powered Portable ECG Device with Optimal Power Consumption and High Accuracy Measurement

Bui

Kim

et al. 2019

Applied Sciences

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One of the best ways to monitor the health of the heart is to regularly record its electrical activity by using an electrocardiogram (ECG). Abnormal ECG signals may indicate conditions such as heart attack, arrhythmia, or heart defects. There are many ECG devices available which can detect and amplify this differential biological signal from the heart, allowing a lot of information to be collected quickly. The ECG is often small and easy to use, but its power is supplied from regular batteries, which need to be replaced after a certain period of use. This causes discomfort for elderly users. To overcome this limitation, in this paper, we aim to develop a solar-powered, portable Bluetooth device for ECG measurements. The device can be interfaced with smartphones or other wireless devices via Bluetooth by a distance up to 100 m. The ECG device was designed to use solar energy, which is also the main power source. Following the solar energy harvesting circuit is a solar panel with an output voltage of 2.4 V and a power out of 0.25 W. We optimized the design to have a very low power consumption and in sleep mode the current consumption is only around 40 µA. The device was designed with 24-bit resolution and a sampling frequency of up to 2133 Hz, which can allow high accuracy ECG measurements. The device is not only used for heart rate monitoring, but it can also assist doctors in analyzing ECG signals with a high accuracy via embedded operating software.

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“…However, the drawback of this method is that the end effects must be restrained effectively to achieve better performance. Digital filtering [4] and adaptive filtering [5,6] have the strong performance of removing noise. But when they are used to remove EMG, these two methods ignore the fact that the frequency between noise and ECG features is overlapped.…”

Section: Introductionmentioning

confidence: 99%

A new modified wavelet-based ECG denoising

Wang

Zhu

Yan

2019

Computer Assisted Surgery

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Purpose: Wavelet denoising is one of the denoising methods commonly used for ECG signals. However, due to the frequency overlap between the EMG and ECG, the feeble characteristics of ECG signals exists the risk of being weakened in the process of filtering noise. This paper presents a method of modified wavelet design and applies it to the denoising of ECG signals. Materials and methods: The optimized filter coefficients are obtained by approximating the amplitude-frequency response of the ideal filter, and the wavelet is constructed with the optimized filter coefficients. The algorithm is tested by clinical ECG data. Results: The results show that the proposed denoising method can remove the high-frequency noise effectively and enhance the characteristic information of P waves and T waves, and retain the characteristic information of the atrial fibrillation signals simultaneously. Compared with db4 and sym4 wavelets, the proposed wavelet can improve the signal to noise ratio and reduce the mean square error effectively at the same time. Conclusion: The modified wavelet design method proposed in this paper can effectively remove high-frequency noise while retaining and enhancing weak features. It provides a theoretical guidance for the de-noising of ECG signals in mobile medicine and also provides a way for other types of weak feature signal denoising.

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Design of Digital IIR Filter for Noise Reduction in ECG Signal

Cited by 23 publications

References 1 publication

Heart beat peak detection using signal filtering in ECG data

Heart beat peak detection using signal filtering in ECG data

Design of a Solar-Powered Portable ECG Device with Optimal Power Consumption and High Accuracy Measurement

A new modified wavelet-based ECG denoising

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