A low noise preamplifier and switched capacitor filter for heart-rate detection

Basak, Debajit; Nishanth, P; Paily, Roy

doi:10.1109/icaes.2013.6659388

Cited by 5 publications

(4 citation statements)

References 9 publications

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“…Additionally, ECG signals acquired by conventional equipment, which is at the disposal of researchers through databases like PhysioNet [99], show an SNR of 10 dB on average, which is similar to our results. Higher SNR figures can be found in ECG designs based on integrated circuits [100] (26.37 dB) but with the main drawback of higher cost. There are also relatively few studies involving EDA circuit design that include SNR in their results.…”

Section: Signal Qualitymentioning

confidence: 99%

Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables

et al. 2022

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Detecting stress when performing physical activities is an interesting field that has received relatively little research interest to date. In this paper, we took a first step towards redressing this, through a comprehensive review and the design of a low-cost body area network (BAN) made of a set of wearables that allow physiological signals and human movements to be captured simultaneously. We used four different wearables: OpenBCI and three other open-hardware custom-made designs that communicate via bluetooth low energy (BLE) to an external computer—following the edge-computingconcept—hosting applications for data synchronization and storage. We obtained a large number of physiological signals (electroencephalography (EEG), electrocardiography (ECG), breathing rate (BR), electrodermal activity (EDA), and skin temperature (ST)) with which we analyzed internal states in general, but with a focus on stress. The findings show the reliability and feasibility of the proposed body area network (BAN) according to battery lifetime (greater than 15 h), packet loss rate (0% for our custom-made designs), and signal quality (signal-noise ratio (SNR) of 9.8 dB for the ECG circuit, and 61.6 dB for the EDA). Moreover, we conducted a preliminary experiment to gauge the main ECG features for stress detection during rest.

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Section: Signal Qualitymentioning

confidence: 99%

Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables

et al. 2022

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“…Our analysis attributed a 45%, 45%, and 10% share of noise to M 1 , M 2 , and M 5 , respectively, and cascode transistor noise was ignored. We then used this noise budget distribution to formulate design equations based on (10) as written in (13) to (15). At this stage of the design process, we ignored the TN and only considered the FN.…”

Section: Case Studymentioning

confidence: 99%

“…In order to size a transistor, it is necessary to first determine its flicker noise power, and then its new size and performance need to be determined in a form of design table as discussed in section II-A1. M 1 was sized according to (13). In the first step, a design table was created using the method outlined in the preceding section in order to achieve v f n1 .…”

Section: A M 1 Sizingmentioning

confidence: 99%

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A Novel Current Density Based Design Approach of Low-Noise Amplifiers

Tarkhan

2022

IEEE Access

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The input-referred noise (IRN) is one of the most crucial performance indicators for analog front-ends (AFEs) of neural recording devices. We present in this paper, a novel design approach for a low-noise amplifier (LNA) based on the transistor optimization method in CMOS technology. Because flicker noise is predominant in neural recording applications, the AFE has been designed so as to meet input-referred flicker noise specifications, whereas thermal noise contributions are monitored and controlled by flicker noise corner frequencies. Transistor optimization is accomplished by using a lookup table that encapsulates its performance based on its current density. Initially, transistors are optimized based on flicker noise performance; later, they may be further optimized based on their size, power consumption, transconductance, or thermal noise contribution. The proposed approach has been validated by designing a folded-cascode amplifier with an IRN ranging from 2 to 8 µV rms . The results of the simulation show that the errors of our design methodology are less than 10%, which is less than those of gm /I D and the inversion coefficient methods. The proposed LNA achieves 2.1 µV rms while consuming 0.83 µW from 1.2 V supply.

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