Design of digital FIR filter implemented with window techniques for reduction of power line interference from ECG signal

Mittal, Akanksha; Rege, Amit

doi:10.1109/ic4.2015.7375535

Cited by 9 publications

(4 citation statements)

References 5 publications

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“…The output signal from the analog signal conditioning circuit is connected to the ADC7, the sample captured during RED/IR LED's at On-time period, and one sample captured during LED's at OFF-time period to neglect the Unwanted light in the dark period [19]. PIC18F46K22 applying the FIR Filter [9] (Equation 4).…”

Section: Blood Pressure Signal and Circuitmentioning

confidence: 99%

Biomedical Handheld Embedded System

Soliman

Wahba

Tarrad

2021

Journal of Al-Azhar University Engineering Sector

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In recent times, most hospitals in the world are crowded and facing the problem of increasing numbers of patients, specifically with the spread of infectious viruses such as Covid-19 and other chronic diseases such as cardiac disease and Geriatrics diseases, therefore patients need continuous and accurate emergency care. The heart rhythm disturbances, unsaturated oxygen in the blood, and high-temperature may be a high risk to the life of the patient. Most hospitals and medical quarantines have a shortage of Intensive care units (ICU) rooms. This paper discusses the design and improvement of the Patient monitor device for converting it to a handheld device to be small in size (L145 x W85 x D45 mm), lite Wight (398 gm.), low-cost nearly (98USD), easy-to-use by touch screen, and secure connections to internet with (SSL) protocol [22]. The maximum errors of ECG HR is 1.408% , and SPO2 is 1.075% ,SPO2 HR is 1.408% , temperature is 0.549%, BP systolic is 2.439% , BP Diastolic is 3.448%,The patient can use the device anywhere by himself, in an easy way and safely. This device measures physiological parameters such as (blood pressure by using (MAP) method, the saturation of oxygen in the blood (SPO2) by photoplethysmograph (PPG), the electrical and muscle movement of the heart through 3Lead (ECG), temperature, and finally, Heartbeat rate by different three ways). All data are monitoring on Smart Touch TFT, and storing the Main information of patient for more than thirty days Continuously on SD. Also using (IoT) technology to transfer all patient information in real-time through ESP8266 to Android or Website to follow-up the patient directly and permanently by Doctor or Caretaker, The device gives some important Speech voice sentences and sound alerts to improve the health of the patient. to design and implement the system with low cost, we are using the traditional lowcost sensors, with changing the large bulker analog circuits to intelligent signal conditioning by using (CMRR) with Sallen-Key Active filter and low-cost successive approximation 12-bit ADC MCP3208, with DAC MCP4728 and improving the efficiency by DSP software Specifically FIR and Moving Average Filter. This paper not using any Platforms under (RTOS), but using embedded BASIC language with the wide-range microcontroller PIC18f46k22, to keep the program in small size of memory and low power consumption

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Section: Blood Pressure Signal and Circuitmentioning

confidence: 99%

Biomedical Handheld Embedded System

Soliman

Wahba

Tarrad

2021

Journal of Al-Azhar University Engineering Sector

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“…ECG signal as shown in Figure 2. In the work of [19], a digital FIR filter is developed and applied with various windowing techniques such as Hamming, Kaiser, and Chebyshev to eliminate 50 Hz power line noise in the signal of ECG. The assessment in the MATLAB setting was completed.…”

Section: Introductionmentioning

confidence: 99%

An approach of adaptive notch filtering design for electrocardiogram noise cancellation

Hidayat

Lestari

Herawati

et al. 2021

IJEECS

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An electrocardiogram (ECG) is a means of measuring and monitoring important signals from heart activity. One of the major biomedical signal issues such as ECG is the issue of separating the desired signal from noise or interference. Different kinds of digital filters are used to distinguish the signal components from the unwanted frequency range to the ECG signal. To address the question of noise to the ECG signal, in this paper the digital notch filter IIR 47 Hz is designed and simulated to demonstrate the elimination of 47 Hz noise to obtain an accurate ECG signal. The full architecture of the structure and coefficient of the IIR notch filter was carried out using the FDA Tool. Then the model is finished with the help of Simulink and the MATLAB script was to filter out the 47 Hz noise from the signal of ECG. For this purpose, the normalized least mean square (NLMS) algorithm was used. The results indicate that before being filtered and after being filtered it clearly shows the elimination of 47 Hz noise in the signal of the ECG. These results also show the accuracy of the design technique and provide an easy model to filter out noise in the ECG signal.

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“…The paper compares the results of the well-known methods of ECG signal filtration (filters with finite (FIR) [7,8] or infinite impulse response (IIR) [9,10], adaptive noise canceller (ANC) [11], wavelet transform (WT) [12,13] and empirical mode decomposition (EMD) [14,15]) between the original artificially generated ECG signal and the filtered signal after mixing with the 50 Hz PLI. The goal of ECG signal denoising is to separate the desired cardiac components from the unwanted artifacts, so to extract an ECG that facilitates easy and accurate interpretation.…”

Section: Introductionmentioning

confidence: 99%

“…The goal of ECG signal denoising is to separate the desired cardiac components from the unwanted artifacts, so to extract an ECG that facilitates easy and accurate interpretation. The MATLAB software was used for implementation of the tested filtration methods, and the signal-to-noise ratio (SNR) [16,7] and correlation coefficient were computed for the effectiveness evaluation of each method.…”

Section: Introductionmentioning

confidence: 99%

Power Line Interference Elimination in ECG Signals

Ládrová

Martínek

Jaroš

2019

JBBBE

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The recordings of electrocardiogram (ECG), as an important biological signal which provides a valuable basis for the clinical diagnosis and treatment, are often corrupted by the wide range of artifacts. One important of them is power line interference (PLI). The overlapping interference affects the quality of ECG waveform, leading to the false detection and recognition of wave groups, and thus causing faulty treatment or diagnosis. The study deals with some of the signal processing approaches frequently used for elimination of PLI in ECG signal and compares the accuracy of methods by evaluation of the power of the remaining noise and comparing a filtered ECG signal with an original. The results are compared for three levels of interference and each tested method: Butterworth filter (BF), notch filter, moving average filter (MA), adaptive noise canceller (ANC), wavelet transform (WT) and empirical mode decomposition (EMD).

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Design of digital FIR filter implemented with window techniques for reduction of power line interference from ECG signal

Cited by 9 publications

References 5 publications

Biomedical Handheld Embedded System

Biomedical Handheld Embedded System

An approach of adaptive notch filtering design for electrocardiogram noise cancellation

Power Line Interference Elimination in ECG Signals

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