Abstract:There is a growing demand for low-power, small-size and ambulatory biopotential acquisition systems. A crucial and important block of this acquisition system is the analog readout front-end. We have implemented a low-power and low-noise readout front-end with configurable characteristics for Electroencephalogram (EEG), Electrocardiogram (ECG), and Electromyogram (EMG) signals. Key to its performance is the new AC-coupled chopped instrumentation amplifier (ACCIA), which uses a low power current feedback instrum… Show more
“…There are two noise settings of the proposed amplifier: 0.4µVrms, (6.3µW power) and 2.6µVrms, (0.9µW power). The proposed topology achieves better power efficiency (NEF) than the resistive feedback topology in [5] thanks to the current reuse, the optimization of the input resistance for minimum power consumption, and the signal dependent current biasing. Even compared to capacitive feedback amplifiers without current reuse technique [7][8], the NEF of this amplifier is better.…”
Section: B Benchmarking and Discussionmentioning
confidence: 99%
“…Resistive feedback amplifiers offer high Zin and high CMRR, but suffer from relatively high NEF, mainly because the feedback resistors contribute to the total noise [5]. In this paper, a noise-reconfigurable current-reuse resistive feedback amplifier that achieves high power efficiency together with high input impedance is proposed and optimized in a standard 0.18µm CMOS technology.…”
• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers.
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Citation for published version (APA):Song, S., Rooijakkers, M. J., Harpe, P., Rabotti, C., Mischi, M., Van Roermund, A. H. M., & Cantatore, E. (2016). A noise reconfigurable current-reuse resistive feedback amplifier with signal-dependent power consumption for fetal ECG monitoring. IEEE Sensors Journal, 16(23),[8304][8305][8306][8307][8308][8309][8310][8311][8312][8313]. DOI: 10.1109/JSEN.2016 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ?
Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract-This paper presents a noise-reconfigurable resistive feedback amplifier with current-reuse technique for fetal ECG monitoring. The proposed amplifier allows for both tuning of the noise level and changing the power consumption according to the signal properties, minimizing the total power consumption while satisfying all application requirements. The amplifier together with its amplitude detector and dynamical biasing circuit are implemented in a standard 0.18µm CMOS process. Measurements demonstrate that the proposed current-reuse resistive feedback topology improves the power efficiency of the conventional resistive feedback amplifier, achieving at the same time a good noise efficiency factor (NEF=2.8) and an input impedance of 20MOhm. The amplitude detector and dynamical biasing circuit, which tunes the current in the amplifier according to the signal amplitude, save up to 40% of the total power consumption. The amplifier achieves a measured noise level of 0.34µVrms in a 0.6 to 175Hz band, consuming 6.3µW power.
“…There are two noise settings of the proposed amplifier: 0.4µVrms, (6.3µW power) and 2.6µVrms, (0.9µW power). The proposed topology achieves better power efficiency (NEF) than the resistive feedback topology in [5] thanks to the current reuse, the optimization of the input resistance for minimum power consumption, and the signal dependent current biasing. Even compared to capacitive feedback amplifiers without current reuse technique [7][8], the NEF of this amplifier is better.…”
Section: B Benchmarking and Discussionmentioning
confidence: 99%
“…Resistive feedback amplifiers offer high Zin and high CMRR, but suffer from relatively high NEF, mainly because the feedback resistors contribute to the total noise [5]. In this paper, a noise-reconfigurable current-reuse resistive feedback amplifier that achieves high power efficiency together with high input impedance is proposed and optimized in a standard 0.18µm CMOS technology.…”
• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers.
Link to publication
Citation for published version (APA):Song, S., Rooijakkers, M. J., Harpe, P., Rabotti, C., Mischi, M., Van Roermund, A. H. M., & Cantatore, E. (2016). A noise reconfigurable current-reuse resistive feedback amplifier with signal-dependent power consumption for fetal ECG monitoring. IEEE Sensors Journal, 16(23),[8304][8305][8306][8307][8308][8309][8310][8311][8312][8313]. DOI: 10.1109/JSEN.2016 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ?
Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract-This paper presents a noise-reconfigurable resistive feedback amplifier with current-reuse technique for fetal ECG monitoring. The proposed amplifier allows for both tuning of the noise level and changing the power consumption according to the signal properties, minimizing the total power consumption while satisfying all application requirements. The amplifier together with its amplitude detector and dynamical biasing circuit are implemented in a standard 0.18µm CMOS process. Measurements demonstrate that the proposed current-reuse resistive feedback topology improves the power efficiency of the conventional resistive feedback amplifier, achieving at the same time a good noise efficiency factor (NEF=2.8) and an input impedance of 20MOhm. The amplitude detector and dynamical biasing circuit, which tunes the current in the amplifier according to the signal amplitude, save up to 40% of the total power consumption. The amplifier achieves a measured noise level of 0.34µVrms in a 0.6 to 175Hz band, consuming 6.3µW power.
“…The system set-up for this experiment is depicted in Figure 3 where the ECG Front-end (FE) chip [6] amplifies and filters the ECG signals that are sampled by the ADC in the MSP430. During the simulation using WSim, only the dynamic behaviour of the ADC and the MSP430 are included and the ECG FE is taken as a constant in the total power figure.…”
This paper presents a system design study for wearable sensor devices intended for healthcare and lifestyle applications based on ECG, EEG and activity monitoring. In order to meet the lowpower requirement of these applications, a dual-core signal processing system is proposed which combines an ultra-lowpower bio-medical Application Specific Instruction-set Processor (BioASIP) and a low-power general-purpose micro-controller (MSP430). To validate the merits of the proposed architecture, system-level power analysis and trade-offs are conducted using real hardware measurements of an ECG R-peak detection application. The results show that the proposed dual-core architecture consumes around 65.38µW, about 25.8x smaller than an MSP430-only approach. Out of 65.38µW, the BioASIP consumes only 11µW and the rest is used in the analog front-end, A/D conversion, and control tasks.
“…It also determines the size and duration of the battery. Power consumption could be reduced by either fully customizing the design of all the electronic blocks that form the EEG system [5] and/or coming up with strategies to reduce the amount of data that needs to be transmitted. This paper presents a data selection algorithm to identify candidate epileptic interictal activity and reject normal back- ground brain activity.…”
Abstract-Real signals are often corrupted by noise. In applications where the noise power spectrum is variable with time, dynamic noise estimation and compensation can potentially improve the performance of signal processing algorithms. One such application is scalp EEG monitoring in epilepsy, where the electrical activity generated by cranio-facial muscle contraction and expansion, often obscures the measured brainwave signals. This work presents a data reduction algorithm which is based on differentiating interictal from normal background activity, in epileptic scalp EEG signals, using a modified phase congruency technique. The modification is based on dynamically estimating muscle activity from the signal and incorporating this estimation in phase congruency computations. The proposed algorithm identifies 90% of interictal spikes whilst transmitting only 45% of EEG data. This is in the order of 15% improvement in data reduction when compared to the performance obtained with the state-of-the-art denoised phase congruency-which calculates a constant noise threshold-applied to the same dataset.
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