Literature DB >> 28186908

Pseudo Asynchronous Level Crossing adc for ecg Signal Acquisition.

T Marisa, T Niederhauser, A Haeberlin, R A Wildhaber, R Vogel, J Goette, M Jacomet.   

Abstract

A new pseudo asynchronous level crossing analogue-to-digital converter (adc) architecture targeted for low-power, implantable, long-term biomedical sensing applications is presented. In contrast to most of the existing asynchronous level crossing adc designs, the proposed design has no digital-to-analogue converter (dac) and no continuous time comparators. Instead, the proposed architecture uses an analogue memory cell and dynamic comparators. The architecture retains the signal activity dependent sampling operation by generating events only when the input signal is changing. The architecture offers the advantages of smaller chip area, energy saving and fewer analogue system components. Beside lower energy consumption the use of dynamic comparators results in a more robust performance in noise conditions. Moreover, dynamic comparators make interfacing the asynchronous level crossing system to synchronous processing blocks simpler. The proposed adc was implemented in [Formula: see text] complementary metal-oxide-semiconductor (cmos) technology, the hardware occupies a chip area of 0.0372 mm2 and operates from a supply voltage of [Formula: see text] to [Formula: see text]. The adc's power consumption is as low as 0.6 μW with signal bandwidth from [Formula: see text] to [Formula: see text] and achieves an equivalent number of bits (enob) of up to 8 bits.

Entities:  

Year:  2017        PMID: 28186908     DOI: 10.1109/TBCAS.2016.2619858

Source DB:  PubMed          Journal:  IEEE Trans Biomed Circuits Syst        ISSN: 1932-4545            Impact factor:   3.833


  3 in total

1.  On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications.

Authors:  Asma Maalej; Manel Ben-Romdhane; Mariam Tlili; François Rivet; Dominique Dallet; Chiheb Rebai
Journal:  Measurement (Lond)       Date:  2020-05-27       Impact factor: 3.927

2.  Arrhythmia Diagnosis by Using Level-Crossing ECG Sampling and Sub-Bands Features Extraction for Mobile Healthcare.

Authors:  Saeed Mian Qaisar; Syed Fawad Hussain
Journal:  Sensors (Basel)       Date:  2020-04-16       Impact factor: 3.576

3.  Backpropagation With Sparsity Regularization for Spiking Neural Network Learning.

Authors:  Yulong Yan; Haoming Chu; Yi Jin; Yuxiang Huan; Zhuo Zou; Lirong Zheng
Journal:  Front Neurosci       Date:  2022-04-14       Impact factor: 5.152

  3 in total

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