A low-noise low-power MOSFET only electrocardiogram amplifier

Ghamati, Maryam; Maymandi-Nejad, Mohammad

doi:10.1109/iraniancee.2013.6599849

Cited by 9 publications

(5 citation statements)

References 8 publications

(6 reference statements)

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“…Leon Fay used capacitors to replace the resistors, effectively reducing the power consumption and output noise [11]. Based on the previous two studies, Maryam Ghamati proposed using MOSCAP to replace the resistors, which solves the power and noise problem and minimizes the size of the amplifier compared to capacitors [12]. In general, the main idea of solving the noise problem caused by resistors is using other kinds of electronic components which can be used as a divider in the amplifying circuit and reduce the noise.…”

Section: Amplifier Optimizingmentioning

confidence: 99%

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Highly Efficient Low Noise Solutions in ECG Signals

Liu

Yuan

2022

J. Phys.: Conf. Ser.

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This paper aims at helping researchers develop low-noise ECG monitors and analyze existing solutions for eliminating noise in ECG signals. A brief introduction of ECG signal, main kinds of noise in ECG signal and a summary of different kinds of low noise solutions is given. The components of the ECG signal and the origin of noise in the ECG signal are analyzed first. In order to find optimized solutions for eliminating the noise, highly effective solutions are listed and analyzed. Solutions are divided into three main directions, which are circuit design, signal processing and machine learning. Specific practical examples from former research and analyses for each direction help the reader understand and select different ways of eliminating noise in ECG signals. After introducing three directions, a summary and further improvement are given to help readers have a horizontal comparison between solutions.

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Section: Amplifier Optimizingmentioning

confidence: 99%

“…A driven rightleg circuit can solve this problem, as shown in Figure 8. The buffer and OTA provide common mode feedback to reject the common-mode voltage [12]. Using DRL can reduce the electrode-skin impedance, which will also help reject the common-mode voltage [18].…”

Section: Driven Right-leg (Drl) Circuitmentioning

confidence: 99%

Highly Efficient Low Noise Solutions in ECG Signals

Liu

Yuan

2022

J. Phys.: Conf. Ser.

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“…Typical raw ECG sensor signals have an amplitude of a few millivolts and are generally amplified and noise-filtered. Suitable low-power, low-noise amplifiers have been proposed, for instance, in [37] and [38], each with a power consumption of less than 50 µW. Similarly, lowpass and notch filters are proposed in [39] and [40], requiring less than 4 µW power.…”

Section: Preprocessing and Conversion To Eventsmentioning

confidence: 99%

Real-Time Ultra-Low Power ECG Anomaly Detection Using an Event-Driven Neuromorphic Processor

Bauer¹,

Muir²,

Indiveri

2019

IEEE Trans. Biomed. Circuits Syst.

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Accurate detection of pathological conditions in human subjects can be achieved through off-line analysis of recorded biological signals such as electrocardiograms (ECGs). However, human diagnosis is time-consuming and expensive, as it requires the time of medical professionals. This is especially inefficient when indicative patterns in the biological signals are infrequent. Moreover, patients with suspected pathologies are often monitored for extended periods, requiring the storage and examination of large amounts of non-pathological data, and entailing a difficult visual search task for diagnosing professionals.In this work we propose a compact and sub-mW low power neural processing system that can be used to perform on-line and real-time preliminary diagnosis of pathological conditions, to raise warnings for the existence of possible pathological conditions, or to trigger an off-line data recording system for further analysis by a medical professional. We apply the system to real-time classification of ECG data for distinguishing between healthy heartbeats and pathological rhythms.Multi-channel analog ECG traces are encoded as asynchronous streams of binary events and processed using a spiking recurrent neural network operated in a reservoir computing paradigm. An event-driven neuron output layer is then trained to recognize one of several pathologies. Finally, the filtered activity of this output layer is used to generate a binary trigger signal indicating the presence or absence of a pathological pattern. We validate the approach proposed using a Dynamic Neuromorphic Asynchronous Processor (DYNAP) chip, implemented using a standard 180 nm CMOS VLSI process, and present experimental results measured from the chip.

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“…This unwanted signal comes from power lines and noise of power supply. The common‐mode voltage amplitude is much larger than the ECG amplitude 15 . Therefore, the amplifier should have a high CMRR to eliminate the effect of this unwanted signal.…”

Section: Amplifier Designmentioning

confidence: 99%

An ultra‐low‐power, low‐noise tunable electrocardiogram amplifier

Saeidian

Ashraf

2020

Circuit Theory & Apps

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Summary The objective of this research work is to propose an innovative low‐power, low‐noise, tunable three‐stage capacitive instrumentation amplifier, capable of receiving and magnifying the electrocardiogram (ECG) signals. This is done by adding an extra stage to the second stage of the conventional capacitive instrumentation amplifier. The results show similar midband gain with lesser capacitor usage and smaller chip occupancy area with provision of concurrent tunable gain and bandwidth. The proposed amplifier is designed and implemented using TSMC 0.18‐μm CMOS technology scale under a 1‐V supply voltage with the simulation process carried out using Cadence Virtuoso tool. Post‐layout simulation results show that the amplifier has a tunable midband gain of 55 to 65.6 dB, low‐cutoff frequency tuned from 377 mHz to 4.5 Hz and high‐cutoff frequency tuned from 86.8 to 263.6 Hz. The simulated value of the input‐referred noise and noise efficiency factor (NEF) of the amplifier are 9.6 μVrms and 6.1, respectively, with the total power consumption of 71.2 nW.

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A low-noise low-power MOSFET only electrocardiogram amplifier

Cited by 9 publications

References 8 publications

Highly Efficient Low Noise Solutions in ECG Signals

Highly Efficient Low Noise Solutions in ECG Signals

Real-Time Ultra-Low Power ECG Anomaly Detection Using an Event-Driven Neuromorphic Processor

An ultra‐low‐power, low‐noise tunable electrocardiogram amplifier

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