Ultra-Low Power Non-Uniform SAR ADC based ECG detector for Early Detection of Cardiovascular Diseases

被引:1
|
作者
Ramkumar, Aditya [1 ]
Verma, Anshul [1 ]
Das, Bishnu Prasad [1 ]
机构
[1] IIT Roorkee, Dept ECE, Roorkee, Uttar Pradesh, India
关键词
SAR-ADC; non-Uniform quantizer; ECG; cardiovascular diseases; ultra-low power; EVENT-DRIVEN; COMPARATOR; CMOS;
D O I
10.1109/VLSID57277.2023.00032
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cardiovascular diseases are a leading cause of death worldwide which motivates to design the smart wearable healthcare devices to monitor the condition of the heart in real time. In this paper, we present an analog front-end circuit to process the Electrocardiogram (ECG) signal which can be used to detect the R-R interval and other parameters of the ECG signal. The proposed circuit mainly consists of a non-uniform quantizer-based successive approximation register analog-to-digital converter (SAR-ADC). Due to the non-uniform quantization of the signal, the proposed circuit consumes very less power which is needed for wearable healthcare devices. The non-uniform quantizer is designed based on the non-uniform nature of the ECG signal and is implemented by modifying the SAR algorithm. The parasitic extracted netlist of the proposed analog front end is simulated in TSMC 65-nm process node at a supply voltage of 0.6V. It is found that our circuit consumes an average power of 167 nW at a supply voltage of 0.6V. It operates at 2 kS/s with a DNL/INL of 0.288/0.869 and 8 bits of resolution. It is tested with ECG data from the MIT-BIH Arrhythmia database. The non-uniform ADC presents a 29.09% reduction in power over a uniform SAR-ADC of the same resolution operating at the same supply voltage.
引用
收藏
页码:92 / 97
页数:6
相关论文
共 50 条
  • [41] Ultra-Low Power Render-Based Collision Detection for CPU/GPU Systems
    de Lucas, Enrique
    Marcuello, Pedro
    Parcerisa, Joan-Manuel
    Gonzalez, Antonio
    PROCEEDINGS OF THE 48TH ANNUAL IEEE/ACM INTERNATIONAL SYMPOSIUM ON MICROARCHITECTURE (MICRO-48), 2015, : 445 - 456
  • [42] Real-Time Ultra-Low Power ECG Anomaly Detection Using an Event-Driven Neuromorphic Processor
    Bauer, Felix Christian
    Muir, Dylan Richard
    Indiveri, Giacomo
    IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2019, 13 (06) : 1575 - 1582
  • [43] TDPRO: Time-Domain-Based Computing-in Memory Engine for Ultra-Low Power ECG Processor
    Chang, Liang
    Yang, Siqi
    Chang, Zhiyuan
    Fan, Haodong
    Zhou, Junlu
    Zhou, Jun
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2023, 70 (10) : 3908 - 3919
  • [44] A Charge-Based Ultra-Low Power Continuous-Time ADC for Data Driven Neural Spike Processing
    Maslik, Michal
    Liu, Yan
    Lande, Tor Sverre
    Constandinou, Timothy G.
    2017 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2017,
  • [45] Novel low resolution ADC-DSP optimization based on non-uniform quantization and MLSE for data centers interconnects
    Yoffe, Yaron
    Sadot, Dan
    OPTICS EXPRESS, 2016, 24 (05): : 5346 - 5355
  • [46] Ultra-Low Power Schottky Barrier TFT-Based Neurotransmitter Detection and Regenerative Studies
    Barua, Abhijeet
    White, Ryan J.
    Leedy, Kevin D.
    Chidambaran, Vidya
    Jha, Rashmi
    IEEE SENSORS JOURNAL, 2022, 22 (08) : 7550 - 7561
  • [47] A 6.3 pJ/b Ultra-low Power Energy Detector for Non-Coherent UWB Impulse Radio Receiver
    Sparrow, O. Ramos
    Bourdel, S.
    Jacquemod, G.
    Gaubert, J.
    PROCEEDINGS OF THE 37TH CONFERENCE ON DESIGN OF CIRCUITS AND INTEGRATED SYSTEMS (DCIS 2022), 2022, : 296 - 301
  • [48] Design Exploration of Ultra-Low Power Non-volatile Memory based on Topological Insulator
    Wang, Yuhao
    Yu, Hao
    PROCEEDINGS OF THE 2012 IEEE/ACM INTERNATIONAL SYMPOSIUM ON NANOSCALE ARCHITECTURES (NANOARCH), 2012, : 30 - 35
  • [49] Design and Analysis of Ultra-Low Power Glitch-Free Programmable Voltage Detector Based on Multiple Voltage Copier
    Someya, Teruki
    Fuketa, Hiroshi
    Matsunaga, Kenichi
    Morimura, Hiroki
    Sakurai, Takayasu
    Takamiya, Makoto
    IEICE TRANSACTIONS ON ELECTRONICS, 2017, E100C (04): : 349 - 358
  • [50] An Ultra-Low Power QRS Complex Detection Algorithm Based on Down-Sampling Wavelet Transform
    Zou, Yao
    Han, Jun
    Weng, Xinqian
    Zeng, Xiaoyang
    IEEE SIGNAL PROCESSING LETTERS, 2013, 20 (05) : 515 - 518