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  • IEEE JOURNAL OF SOLID-STATE CIRCUITS, VOL. 51, NO. 10, OCTOBER 2016 2287

    A 2.89 μW Dry-Electrode Enabled Clockless Wireless ECG SoC

    for Wearable Applications Xiaoyang Zhang, Zhe Zhang, Yongfu Li, Changrong Liu, Yong Xin Guo, and Yong Lian

    Abstract— This paper presents a fully integrated wireless electrocardiogram (ECG) SoC implemented in asynchronous architecture, which does not require system clock as well as off-chip antenna. Several low power techniques are proposed to minimize power consumption. At the system level, a newly introduced event-driven system architecture facilitates the asyn- chronous implementation, thus removes the system clock leading to a true ECG-on-chip solution. A DC-coupled analog front-end is introduced together with a baseline stabilizer to boost the input impedance to 3.6 G� and mitigate the electrode offset, which is less sensitive to motion artefact and contact impedance imbal- ance, making it well suited for dry-electrode based applications. Level-crossing analog-to-digital converter (LC-ADC) is employed to take the advantage of burst nature of ECG signal leading to at least 5 times reduction in sampling points compared to Nyquist sampling. A digitally implemented impulse-radio ultra-wideband transmitter is seamlessly integrated with LC-ADC and an on-chip antenna for wireless communications. Implemented in 0.13 μm CMOS technology, the ECG-on-chip consumes 2.89 μW under 1.2 V supply while transmitting the raw ECG data, which attains one order of magnitude lower than the current state-of-the-art designs. The fully integrated ECG SoC requires no external clocks and off-chip antenna, making it a good candidate for low cost and disposable wireless ECG patches, such as epidermal electronics.

    Index Terms— Electrocardiogram (ECG), dry-electrode, high input impedance IA, DC-coupled IA, event-driven, level-crossing ADC, asynchronous, clockless, impulse-radio, wearable biomed- ical sensor, epidermal electronics.

    I. INTRODUCTION

    CARDIOVASCULAR disease (CVD) is a globalpublic health problem, affecting millions of patients and associated with significant mortality, morbidity, and healthcare expenditure. Statistics from the World Health

    Manuscript received February 8, 2016; revised April 20, 2016; accepted June 6, 2016. Date of publication July 29, 2016; date of current version September 30, 2016. This work was supported in part by the National Research Foundation, Prime Minister’s Office, Singapore under the grant NRF-CRP8-2011-01 and the Natural Sciences and Engineering Research Council of Canada Discovery Grants. This paper was approved by Guest Editor Noriyuki Miura.

    X. Zhang, Z. Zhang, Y. Li, and Y. X. Guo are with the National University of Singapore, Singapore, 117576 (e-mail: xz@u.nus.edu; a0066531@u.nus.edu; liyongfu.sg@gmail.com; yongxin.guo@nus.edu.sg).

    C. Liu is with the School of Electronic and Information Engineering, Soochow University, Jiangsu, 215006, China (e-mail: crliu@suda.edu.cn).

    Y. Lian is with the Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada (e-mail: plian@yorku.ca).

    Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org.

    Digital Object Identifier 10.1109/JSSC.2016.2582863

    Organization (WHO) show that 17.5 million people died from CVDs in the year of 2012 [1]. The direct cost of CVDs exceeds $380 billion in USA alone in 2015 [2]. According to WHO, CVD patients are on the rise, highlighting the urgent need for an effective care system to manage and support CVD patients. One of the effective tools for monitoring heart condition is the ECG (electrocardiogram). With the advancement of wearable technologies and Big Data analytics, it is possible to create an effective CVD management system that benefits the CVD patients and those at high cardiovascular risks.

    There are notable research efforts in the development of ECG chips for wearable sensors in the past 10 years. For ECG analog front-end (AFE), several low-power designs [3], [4] have shown decent performance with low power consump- tion, which are promising for wearable ECG sensors using wet electrodes. As the input impedance is relatively low for AC-coupled [3] or chopper stabilization amplifier [4], those designs are not suitable for dry-electrode. This is because the contact impedance and interference of dry-electrode are much larger than that of Ag/AgCl based wet-electrode according to the study [5]. It is possible to boost the input impedance in the chopper amplifier to mitigate the large contact impedance of dry-electrode at the cost of high power consumption [6]. The straightforward way of obtaining high input impedance is to use DC-coupled amplifier while managing the large electrode- offset caused by skin-electrode interface through compensation schemes, such as the off-chip feedback loop implemented in [7]. So far there is no perfect low power solution for ECG analog front-end design that is capable of dealing with issues caused by skin-electrode interface, i.e., electrode polarization. In this paper, we propose a DC-coupled analog front-end to maximize input impedance and introduce a baseline stabiliza- tion mechanism to deal with electrode-offset.

    Meanwhile, motion artefact (or contact potential) remains one of the most challenging issues in the design of wearable sensor. It is caused by the fluctuation in the skin potential due to stretching, deformation, and pressing on the skin. The amplitude of motion artefact could be as high as 10 times of ECG signal, which seriously affects the system dynamic range. Furthermore, the contact impedance between skin and electrode plays a crucial role in signal quality. It could selectively attenuate ECG signal in different frequencies due to its frequency dependency. Such behavior has adverse effects on low frequency components, such as P-wave, T-wave, and S-T segment. P, T, S-T are important features in ECG,

    0018-9200 © 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

  • 2288 IEEE JOURNAL OF SOLID-STATE CIRCUITS, VOL. 51, NO. 10, OCTOBER 2016

    Fig. 1. Block diagram of a typical wireless biomedical sensor.

    distorting them may lead to wrong diagnosis. In fact, changes in S-T segment may signal a heart attack (myocardial infarc- tion). Thus, being directly connected to the body, the per- formance of AFE is crucial to the signal quality. First, the noise of the whole sensor is often limited by the instru- mentation amplifier (IA) at the first stage. AFE with higher noise floor could distort the small signals in ECG, such as P-wave. Thus, a reasonable noise floor is required for the AFE. Second, the AFE should be able to reject the electrode offset effectively to avoid amplifier saturation. IEC 60601 Part 2-47 sets the minimum requirement of handling +/-300 mV electrode offset. AC-coupled amplifiers [3] and the chopper stabilized amplifiers [4] are the most common solutions for offset suppression. Third, high input impedance is necessary for mitigating the effects from motion artefact and contact impedance [8]. Unfortunately, few designs could achieve the impedance requirement without power overhead or compro- mise in noise and input dynamic range. The DC-coupled AFE in [7] has very high input impedance, but it requires off-chip digital-to-analog converter (DAC) feedback for offset cancellation. Input impedance boost technique gives T� input impedance, but the gain is unity and the power consumption is high [9]. A power-efficient active electrode using one PMOS transistor is analyzed in [10], but it has limited input range and deteriorated common-mode reject ratio due to mismatch.

    For ECG SoC, continuous effort is made to lower the power consumption in order to meet the energy constraint of wearable wireless sensors [11]–[14]. Over the years, the power is reduced from several milliwatts [11] to few microwatts [14]. Most of these designs follow the traditional signal processing flow for a wearable wireless sensor, as shown in Fig. 1, which consists of an analog front-end (AFE), an analog-to-digital converter (ADC), a microcontroller (MCU) and/or digital signal processing unit, a memory block, a wireless transceiver, and a power management unit. In such architecture, the power reduction comes from four areas: 1) lowering supply voltage; 2) minimizing data rate through feature extraction or data compression; 3) duty-cycling transmitter with the help of on- chip memory; and 4) employing impulse radio UWB (ultra- wideband) transmitter for better power efficiency. A good

    example of applying above low power strategies is the wireless SoC for ExG applications [12]. The chip consumes 19 μW on average for transmitting heart rate information, which is the result of feature extraction and heavy duty cycling of transmit- ter. Without feature extraction, the chip consumes 397 μW for transmitting raw ECG data. The design in [13] utilizes multiple voltage domains for power saving, especially for leakage power. The leakage power is reduced by more than 3 times when the supply voltage is lowered to 0.25 V for memory blocks. By allocating different voltages to different function blocks, the 3-lead wireless ECG SoC in [13] consumes only 74.8 μW for transmitting raw ECG data and 17.4 μW for transmitting heart rate. A more recent design demonstrates the benefits of using asymmetric radio and impulse radio UWB transmitter for sensor applications [14]. Biomedical sensors normally communicate in an asymmetric pattern between sensor and gateway. Exploring this asymmetric communication pattern and combinin