A 172 μW Compressively Sampled Photoplethysmographic (PPG) Readout ASIC With Heart Rate Estimation Directly From Compressively Sampled Data

被引:43
|
作者
Pamula, Venkata Rajesh [1 ,2 ]
Valero-Sarmiento, Jose Manuel [3 ]
Yan, Long [4 ,5 ]
Bozkurt, Alper [3 ]
Van Hoof, Chris [1 ,2 ]
Van Helleputte, Nick [4 ]
Yazicioglu, Refet Firat [4 ,6 ]
Verhelst, Marian [2 ]
机构
[1] IMEC, B-3000 Leuven, Belgium
[2] Katholieke Univ Leuven, B-3000 Leuven, Belgium
[3] North Carolina State Univ, Dept Elect & Comp Engn, Raleigh, NC 27606 USA
[4] IMEC, B-3001 Leuven, Belgium
[5] Samsung, Hwaseong, South Korea
[6] GSK Bio, London, England
基金
美国国家科学基金会;
关键词
Compressive sampling (CS); heart rate (HR); Lomb-Scargle periodogram (LSP); low power; photoplethysmography; LOW-POWER;
D O I
10.1109/TBCAS.2017.2661701
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Acompressive sampling (CS) photoplethysmographic (PPG) readout with embedded feature extraction to estimate heart rate (HR) directly from compressively sampled data is presented. It integrates a low-power analog front end together with a digital back end to perform feature extraction to estimate the average HR over a 4 s interval directly from compressively sampled PPG data. The application-specified integrated circuit (ASIC) supports uniform sampling mode (1x compression) as well as CS modes with compression ratios of 8x, 10x, and 30x. CS is performed through nonuniformly subsampling the PPG signal, while feature extraction is performed using least square spectral fitting through Lomb-Scargle periodogram. The ASIC consumes 172 mu W of power from a 1.2 V supply while reducing the relative LED driver power consumption by up to 30 times without significant loss of relevant information for accurate HR estimation.
引用
收藏
页码:487 / 496
页数:10
相关论文
共 9 条
  • [1] A 172μW Compressive Sampling Photoplethysmographic Readout with Embedded Direct Heart-Rate and Variability Extraction from Compressively Sampled Data
    Rajesh, Pamula Venkata
    Valero-Sarmiento, Jose Manuel
    Yan, Long
    Bozkurt, Alper
    Van Hoof, Chris
    Van Helleputte, Nick
    Yazicioglu, Refet Firat
    Verhelst, Marian
    [J]. 2016 IEEE INTERNATIONAL SOLID-STATE CIRCUITS CONFERENCE (ISSCC), 2016, 59 : 386 - U541
  • [2] A time-frequency domain approach of heart rate estimation from photoplethysmographic (PPG) signal
    Islam, Mohammad Tariqul
    Zabir, Ishmam
    Ahamed, Sk. Tanvir
    Yasar, Md. Tahmid
    Shahnaz, Celia
    Fattah, Shaikh Anowarul
    [J]. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2017, 36 : 146 - 154
  • [3] Spectral estimation from irregularly sampled data for frequencies far above the mean data rate
    Broersen, Piet M. T.
    [J]. 2007 IEEE INSTRUMENTATION & MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1-5, 2007, : 287 - +
  • [4] Dual estimation: Constructing building energy models from data sampled at low rate
    Baldi, Simone
    Yuan, Shuai
    Endel, Petr
    Holub, Ondrej
    [J]. APPLIED ENERGY, 2016, 169 : 81 - 92
  • [5] A Reweighted l1-Minimization Based Compressed Sensing for the Spectral Estimation of Heart Rate Variability Using the Unevenly Sampled Data
    Chen, Szi-Wen
    Chao, Shih-Chieh
    [J]. PLOS ONE, 2014, 9 (06):
  • [6] Preprocessing Unevenly Sampled RR Interval Signals to Enhance Estimation of Heart Rate Deceleration and Acceleration Capacities in Discriminating Chronic Heart Failure Patients from Healthy Controls
    Cao, Ping
    Ye, Bailu
    Yang, Linghui
    Lu, Fei
    Fang, Luping
    Cai, Guolong
    Su, Qun
    Ning, Gangmin
    Pan, Qing
    [J]. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2020, 2020
  • [7] Extraction of fetal heart-rate signal as the time event series from evenly sampled data acquired using Doppler ultrasound technique
    Jezewski, Janusz
    Kupka, Tomasz
    Horoba, Krzysztof
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2008, 55 (02) : 805 - 810
  • [8] Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration Data
    Talukdar, Md. Toky Foysal
    Pathan, Naqib Sad
    Fattah, Shaikh Anowarul
    Quamruzzaman, Muhammad
    Saquib, Mohammad
    [J]. IEEE ACCESS, 2022, 10 : 59759 - 59771
  • [9] Expectation maximization estimation algorithm for Hammerstein models with non-Gaussian noise and random time delay from dual-rate sampled-data
    Ma, Junxia
    Chen, Jing
    Xiong, Weili
    Ding, Feng
    [J]. DIGITAL SIGNAL PROCESSING, 2018, 73 : 135 - 144