a wrist watch-type cardiovascular monitoring system using

JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE, VOL.16, NO.5, OCTOBER, 2016 ISSN(Print) 1598-1657 http://dx.doi.org/10.5573/JSTS.2016.16.5.702 ISSN(Online) 2233-4866

Manuscript received Apr. 5, 2016; accepted Jun. 8, 2016 K-healthwear, Korea E-mail : [email protected]

A Wrist Watch-type Cardiovascular Monitoring System using Concurrent ECG and APW Measurement

Kwonjoon Lee, Kiseok Song, Taehwan Roh, and Hoi-jun Yoo

Abstract—A wrist watch type wearable cardiovascular monitoring device is proposed for continuous and convenient monitoring of the patient’s cardiovascular system. For comprehensive monitoring of the patient’s cardiovascular system, the concurrent electrocardiogram (ECG) and arterial pulse wave (APW) sensor front-end are fabricated in 0.18 mm CMOS technology. The ECG sensor front-end achieves 84.6-dB CMRR and 2.3-mVrms-input referred noise with 30-mW power consumption. The APW sensor front-end achieves 3.2-V/W sensitivity with accurate bio-impedance measurement lesser than 1% error, consuming only 984-mW. The ECG and APW sensor front-end is combined with power management unit, micro controller unit (MCU), display and Bluetooth transceiver so that concurrently measured ECG and APW can be transmitted into smartphone, showing patient’s cardiovascular state in real time. In order to verify operation of the cardiovascular monitoring system, cardiovascular indicator is extracted from the healthy volunteer. As a result, 5.74 m/second-pulse wave velocity (PWV), 79.1 beats/minute-heart rate (HR) and positive slope of b-d peak-accelerated arterial pulse wave (AAPW) are achieved, showing the volunteer’s healthy cardiovascular state. Index Terms—Wearable device, cardiovascular monitoring system

I. INTRODUCTION

Recently, patients suffering from a chronic disease are rapidly increasing due to irregular life cycle such as insufficient exercise and overeating [1]. Fig. 1(a) shows a statistical data about patients suffering from a chronic disease in U. S. According to the statistical data, 16% of U. S. GDP will be spent on care of a chronic disease in 2005 and by the end of 2030, half of the American will have been suffered from a chronic disease. A chronic disease is influenced by patient’s life style and eating habits. Furthermore, deterioration of a chronic disease is slow. Therefore, in order to prevent and treat a chronic disease, it is essential to continuously monitor the patient’s state. As shown in Fig. 1(b), cardiovascular disease takes the highest percentage on a chronic disease. A cardiovascular disease consists of two representative diseases; 1) arteriosclerosis, 2) arrhythmia. The definition of arteriosclerosis is a blockage and stiffening of artery. By the patient’s bad eating habits, cholesterol is stacked on the inner layer of artery which is endothelium as shown in Fig. 2(a). And then, platelet and macrophagocyte invade inner layer of artery for stimulating endothelium. Finally, inner layer of artery dramatically increases and hardens with a mass of cholesterol, blocking the patient’s artery. Arrhythmia accompanying fast and chaotic heart rate is caused by disorder of electrical impulse formation or conduction in the patient’s heart. In a normal people’s heart, electrical impulse is generated at sinoatrial (SA) node as shown in Fig. 2(b). And then, electrical impulse generated at SA node pass through atrioventricular (AV) node, Bundle of His and Purkinje’s Fiber, triggering contraction of ventricles and atrium in the heart. However, in the

JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE, VOL.16, NO.5, OCTOBER, 2016 703

patient’s heart suffering from arrhythmia, electrical impulse is not generated at SA node but atrium or ventricle of the heart. Furthermore, in the case of conduction blocking in the heart, electrical impulse generated in SA node cannot be transmitted from SA node to Purkinje’s Fiber, causing the patient’s fast and chaotic heart rate. According to WHO, abovementioned cardiovascular diseases are responsible for over 17.3

million death per year and are the leading causes of death in the world [1]. In order to prevent and care cardiovascular disease, it is essential to continuously and conveniently monitor the patient’s cardiovascular system in daily life, because cardiovascular disease is related to the patient’s life style, having slow deterioration. This work focuses on the method for continuous and convenient cardiovascular monitoring.

To continuously monitor the patient’s cardiovascular system, two kinds of bio-potential signal have been widely used; 1) electrocardiogram (ECG) shown in left of Fig. 3, and 2) arterial pulse wave (APW) shown in the right of Fig. 3. However, arteriosclerosis cannot be diagnosed with ECG because ECG reflects not the mechanical characteristics but only the electrical characteristics of the patient’s cardiovascular system.

On the other hand, APW can reflect the mechanical characteristics of the patient’s cardiovascular system so that APW can diagnose arteriosclerosis. However, Arrhythmia can be diagnosed with not APW but ECG monitoring because APW cannot reflect the electrical characteristics of the patient’s cardiovascular system. Therefore, in order to care the patient’s cardiovascular system, not only continuous and convenient monitoring in daily life but also concurrent ECG/APW measurement is important for comprehensive cardiovascular check. In order to monitor the patient’s cardiovascular system, cardiovascular monitoring device using concurrent ECG/APW measurement has been used in hospital as shown in Fig. 4(a). However, cardiovascular monitoring device used in hospital is bulky and uncomfortable so that the patient suffering from cardiovascular disease should be cared in only hospital. Moreover, cardiovascular monitoring device used in hospital adopts

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Fast & Chaotic Heart Rate

BlockageCoronary Atery

Arteriosclerosis Arrhythmia

Others16%

Cancer21%RPD**12%

Diabetes3%

CVD48%

**Respiratory Disease

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Fig. 1. Statistical data (a) Chronic disease in USA, (b) Percentage of cardiovascular disease on a chronic disease.

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Fig. 2. Cardiovascualr disesase (a) Atheriosclerosis, (b) Arrhythmia.

Fig. 3. Waveforms and measurement methods of electrocardiogram (ECG) and arterial pulse wave (APW).

704 KWONJOON LEE et al : A WRIST WATCH-TYPE CARDIOVASCULAR MONITORING SYSTEM USING CONCURRENT ECG …

photoplethysmography (PPG) in order to measure the patient’s APW. However, PPG devices are vulnerable for ambient noise causing degradation of APW signal quality and consumes too much power consumption (~10mW) due to LED driving current. Nevertheless, cardiovascular monitoring device used in hospital provides user with cardiovascular indicators such as pulse wave velocity (PWV), accelerated arterial pulse wave (AAPW) and heart rate (HR), so that the patient’s cardiovascular system can be accurately and comprehensively checked. W. Lee [2, 7] proposed another cardiovascular monitoring system as shown in Fig. 4(b). The system provides concurrent ECG/APW measurement using Bio-impedance measurement (BIM) technique so that the patient’s APW signal can be measured with low power consumption without ambient noise interference. However, this system [2, 7] is implemented in the test board level. Therefore, the patient’s cardiovascular system can be monitored in the limited area, such as

laboratory and measurement room. Furthermore, this system cannot provide comprehensive cardiovascular indicator to user. The proposed system is shown in the right of Fig. 4(c). The common drawback of the previous works is that the patient’s cardiovascular system can be monitored in limited area such as hospital and laboratory room.

In order to resolve the common drawback of the previous works, the proposed system is implemented into wrist watch type wearable device so that the patient’s cardiovascular system can be conveniently and continuously monitored in daily life. Furthermore, the proposed system provides user with concurrent ECG and APW measurement using BIM technique and cardiovascular indicator for the patient’s comprehensive cardiovascular monitoring. Therefore, the patient’s comprehensive cardiovascular state can be conveniently and continuously monitored in daily life.

The rest of this paper consists of the following Sections. In Section II, the proposed system architecture and system design considerations are introduced for implementation of the wrist watch type wearable device. Section III describes the key building blocks of the proposed system for concurrent ECG/APW measurement using BIM technique. In Section III, block level consideration is also described. In Section IV, system implementation result shows the proposed cardiovascular monitoring system in detail. After that, Section V describes analysis of cardiovascular indicator extracted from the proposed device. Finally, Section VI concludes this paper.

II. SYSTEM ARCHITECTURE

Fig. 5 shows the overall architecture of the proposed system. The proposed system consists of two main parts; 1) ECG sensor front-end, and 2) APW sensor front-end. The ECG sensor front-end measures ECG from the differential ECG electrodes attached on the patient’s chest. The APW sensor front-end measures APW from the tetra-polar APW electrodes placed on the patient’s wrist. After that, the concurrently measured ECG and APW are converted into digital data. The converted ECG and APW data is transmitted into smartphone using Bluetooth communication. Finally, android application, implemented on the smartphone, extracts and shows the

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Fig. 4. Cardiovascular monitoring system (a) Previous system 1, (b) Previous system 2, (c) Proposed system.


cardiovascular indicators from concurrently measured ECG and APW. Therefore, the patients are able to comprehensively monitor their cardiovascular system in daily life. In order to conveniently and continuously monitor patient’s cardiovascular system in daily life, it is essential to consider where the device should be located. Especially, system designer should consider the measurement point of ECG and APW to continuously and conveniently use cardiovascular monitoring device in daily life. Fig. 6(a) shows the medical reference points of APW measurement in human body. As shown in Fig. 6(a), there are four types of reference points for APW measurement; 1) carotid artery in neck, 2) brachial artery in upper arm, 3) radial artery in wrist, and 4) femoral artery in groin. However, in carotid artery and femoral artery, fine measurement of APW is very difficult because of unstable clinical apparatus as shown in Fig. 6(a). APW measurement in brachial artery is also difficult because of poor accessibility and bulky air cuff. Therefore, in order to measure APW easily and accurately, radial artery is decided as a measurement point of APW. Fig. 6(b) shows the medical reference points of ECG measurement in human body. As shown in Fig. 6(b), there are 10 ECG measurement points including neutral or ground point located in right-side of abdomen. In the hospital, in order to measure ECG, A method of 12-lead ECG method which is derived from combinations of 10 ECG reference points is used. However, electrical characteristic of the patient’s cardiovascular system can be checked from partial ECG reference point. Therefore, V4 and V6 reference points are chosen as a measurement point of ECG for large signal amplitude and clear R peak. It is important to

consider not only clinical reference point but also easily removable and compact system implementation in order to conveniently and continuously monitor patient’s cardiovascular system in daily life. Fig. 7 shows the tetra-polar APW electrodes implemented based on the Planar-Fashionable Circuit Board (P-FCB) technology [3, 4]. Thanks to the P-FCB-based tetra-polar dry electrodes for APW measurement, the proposed device can be easily removable without skin irritation. Furthermore, in order to implement compact cardiovascular monitoring system, device size and weight are limited to 100 mm × 50 mm × 20 mm and 100 g, respectively.

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Fig. 6. Clinical reference points for (a) APW measurement, (b) ECG measurement.

Fabric

Silver Paste

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P-FCB Technology Tetra-polar Electrodes

Fig. 7. Tetra-polar APW electrodes based on P-FCB technology.

WiredECG

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: 74 beat / min.: 5.8 m / sec. APW

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Fig. 5. Overall Architecture of the Proposed System.


III. KEY BUILDING BLOCKS

Fig. 8 shows overall block diagram of the proposed system. The proposed system consists of five key building blocks; 1) power management unit for digital power domain (3.3 V, 1.5 V) and analog power domain (±3.3 V, 1.5 V, 0.75 V), 2) concurrent ECG and APW sensor front-end including current source as shown in Fig. 8, 3) signal processing unit for cardiovascular indicator extraction from the concurrently measured ECG and APW, 4) Bluetooth transceiver for transmission of measured ECG, APW, and extracted cardiovascular indicators, and 5) display module in order to show the cardiovascular indicator.

In abovementioned cardiovascular monitoring system, sinusoidal current (100 kHz, 500 mAPP) is injected into the patient’s wrist through the outer pair of the tetra-polar APW electrodes. By the injected sinusoidal current, amplitude modulated voltage signal appears at inner pair of the tetra-polar APW electrodes, reflecting impedance variation of the blood vessel derived from APW.

And then, the amplitude modulated signal is demodulated and amplified in APW sensor front-end. Finally, the demodulated and amplified APW signal is converted into the digital data by 10bit successive approximation register (SAR) ADC. ECG from the patient’s chest is amplified in ECG sensor front-end as shown in Fig. 8. The amplified ECG is also converted into digital data by the 10-bit SAR ADC.

The converted ECG and APW is processed in micro controller unit (MCU) in order to extract cardiovascular indicators. After that, the processed data is transmitted to the smartphone using Bluetooth module, showing the cardiovascular indicator on the display.

As shown in Fig. 9, sensor front-end consists of two parts; 1) ECG sensor front-end, and 2) APW sensor front-end. In the ECG sensor front-end, instrumentation amplifier is located between high pass filter and low pass filter in order to amplifying ECG without out of band noise and aliasing. And then, amplified ECG is converted into digital data by the 10-bit differential SAR ADC.

In the APW sensor front-end, in order to inject sinusoidal current into the patient’s wrist, wien-bridge sinusoidal oscillator generates sinusoidal voltage (100 kHz, 500 mAPP). And then, the generated sinusoidal voltage is converted into the sinusoidal current by the Gm cell implemented with inverting amplifier topology. By the injected sinusoidal current through the outer pair of the tetra-polar APW electrodes, the amplitude modulated voltage signal appears at the inner pair of the tetra-polar APW electrodes. In order to amplify amplitude modulated voltage signal, the high frequency instrumentation amplifier is located between two high pass filters for amplifying amplitude modulated voltage signal.

The amplified amplitude modulation signal is demodulated by the envelope detector, leaving the baseband signal derived from the impedance variation of blood vessel. Finally, the baseband signal is amplified and converted into the digital data by the baseband programmable gain amplifier and 10-bit SAR ADC, respectively.

1. ECG Sensor Front-end Design

In order to design ECG sensor front-end, the

characteristic of the ECG should be considered, As shown in Fig. 10(a), the bandwidth of the ECG is 0.5~300 Hz including 60 Hz power line noise. The

Fig. 9. Key block diagram.

Fig. 8. System block diagram.


common mode rejection ratio (CMRR) of the ECG sensor front-end should be larger than 80-dB in order to remove the common power line noise. Moreover, wire loop between ECG sensor front-end and ECG electrodes should be minimized in order to remove the differential power line noise derived by magnetic coupling. The amplitude of ECG can be varied according to the measurement point. In the proposed system, ECG is measured at the chest so that amplitude of ECG is 1~2 mV. Therefore, ECG can be measured with moderate sensor front-end gain.

Fig. 10(b) shows the capacitive feedback programmable gain amplifier in ECG sensor front-end [5]. The gain is C1/C2 and can be varied from 10 V/V to 100 V/V by controlling the value of the C2 capacitor bank. The lower limit of the amplifier is 1/(2π×RPseudo×C2) set to the 0.5 Hz which is the lower bound of the ECG band. The input referred noise of the amplifier is 2.3-mVrms and CMRR is 84.6-dB, satisfying the abovementioned requirement.

2. APW Sensor Front-end Design Fig. 11(a) shows the measurement setting in order to

measure the bio-impedance of the radial artery and bio-impedance variation derived from APW. By injecting the current (500 uAPP, 100 kHz) into the patient’s wrist, sinusoidal voltage can be measured at oscilloscope channel 1 (~50 mVP-P) and channel 2 (~80 mVP-P), respectively. From the abovementioned measurement setting, the calculated bio-impedance and bio-impedance variation are ~60 W and ~100 mW, respectively. Therefore, in the low power APW sensor front-end adopting low supply voltage (1.5 V), the gain of the high

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Fig. 10. Design consideration of ECG snesor front-end (a) Frequency characteristics of ECG, (b) Capacitive feedback programmable gain amplifier.

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Fig. 11. Design consideration of APW snesor front-end (a) Measurement environment of the bio-impedance and bio-impedance variation, (b) Wien-bridge sinusoidal oscillator, (c) APW signal processing in frequency domain.


frequency instrumentation amplifier should be set to 5 V/V in order to remove saturation of the amplitude modulated signal under 500-mAPP current injection.

Fig. 11(b) shows the wien-bridge sinusoidal oscillator in the sinusoidal current source. In order to accurately measure the bio-impedance and bio-impedance variation (<1%), total harmonic distortion (THD) of the wien-bridge sinusoidal oscillator should be lower than -40dBc, which means that effective Q factor of the wien-bridge sinusoidal oscillator should be more than 10 as shown in the right of Fig. 11(b) [6]. The effective Q factor of the wien-bridge sinusoidal oscillator is (GBW/9×fOSC). Therefore, OP-AMP having 10-MHz GBW is used to implement wien-bridge sinusoidal oscillator. By setting the total loop gain of the wien-bridge sinusoidal oscillator to more than 1, sinusoidal voltage can be generated from the wien-bridge sinusoidal oscillator and the THD can be lowered by the wave shaping method as shown in the left of Fig. 11(b). From the abovementioned design considerations, the gain of the high frequency instrumentation amplifier is set to 5 V/V (14 dB). In order to amplify the demodulated APW signal, the gain of the differential baseband amplifier is set to the 50 V/V (34 dB) and the gain of the baseband programmable amplifier is set to the 40 V/V (32 dB). Furthermore, in order to remove the signal delay derived from the low cut-off frequency (~6 Hz) of the baseband low pass filter, cut-off frequency of the baseband low pass filter is shifted up to 60 Hz. By shifting the cut-off frequency of the baseband low pass filter, 60 Hz power line noise can be measured with APW. However, 60 Hz power line noise can be removed by digital filter implemented on the MCU, compensating the delay of the digital filter. As a result, 0.1 W impedance variation can be successfully measured with 320 mVP-P voltage signal without signal delay as shown in Fig. 11(c).

Fig. 12 shows the chip photograph and Table 1 shows chip performance summary of the key building blocks. ECG and APW sensor front-end are fabricated in 0.18 mm CMOS technology. Die size of ECG and APW sensor front-end is 5.0×2.5 mm2, consuming only 30 mW and 984 mW, respectively. The supply voltage of the ECG and APW sensor front-end is 1.5 V. Finally, effective number of bit (ENOB) of the SAR ADC is 9.4 bit.

System comparison results with previous works [2], [7] are shown in Table 2. The proposed system is

implemented in a wrist watch so that user can conveniently check own cardiovascular state in daily life. The proposed wrist watch has an operating time of 5.8 hours with TFT display and 14.2 hours without TFT display, respectively. Thanks to the concurrent measurement of ECG and APW, the proposed system can

Fig. 12. Chip photograph. Table 1. Chip performance summary

Die Size

Process

Supply Voltage

Power Consumption

Functionality

ECG SFE Gain

ECG SFE BW

APW SFE Gain

APW SFE LPF Cut-offFrequency

Resolution (ENOB)

Injection Current

APW SFE Sensitivity

ECG SFE Noise (RTI)

ECG SFE CMRR

0.11 m 1P6M CMOS 0.18 m 1P6M CMOS

5mm X 2.5mm2.5mm X 2.5mm (ECG SFE)

2.5mm X 2.5mm (APW SFE)

ECG, Bio-Z Variation ECG, Bio-Z Variation

1.2V 1.5V

30 W (ECG SFE)

[7] This Work

984 W (APW SFE)

1.9 VRMS (0.5 ~ 100Hz)* 2.3 VRMS (0.5 ~ 300Hz)

82 dB 84.6 dB

60 dB ~ 90 dB 20 dB ~ 40 dB

0.5Hz ~ 100Hz 0.5Hz ~ 300Hz

2V / 3.2V /

10 dB (High Freq.)

40 dB ~ 70 dB (Low Freq.)

100 Hz

14 dB (High Freq.)

66 dB (Low Freq.)

60 Hz

7.6 bits 9.4 bits

500 APP250 APP

1.28 mW (including Communication)

* Calculated Specification

Table 2. System comparison results


extract various cardiovascular indicators, such as HR, PR, PWV, and AAPW. As a result, the proposed system achieves user convenience and comprehensive cardiovascular analysis, all at once.

IV. IMPLEMENTATION RESULTS

1. Board Level Implementation Fig. 13(a) shows the implementation result of the

proposed system board. Power management unit, Bluetooth transceiver, and cardiovascular monitoring IC are implemented on the top layer. On the other hand, MCU, display interface and current source are implemented on the bottom layer as shown in the Fig. 13(a).

2. System Level Implementation

Fig. 13(b) shows the implementation result of the

proposed wrist watch type wearable cardiovascular

monitoring system. Overall system is implemented with 73 mm×48 mm×18 mm wrist watch type wearable device including 2.4-inch TFT LCD display, consuming 170 mA. On the bottom side of the proposed device, tetra-polar dry APW electrodes are implemented on the watch strap. The proposed device uses 1000-mAh lithium polymer battery and device weight is 80 g.

V. MEASUREMENT RESULTS

1. Pulse Wave Velocity Measurement Pulse wave velocity (PWV) is the cardiovascular

indicator reflecting patient’s cardiovascular state. If the patient’s artery is stiff, the patient’s PWV is high. On the other hand, if the patient’s artery is elastic, the patient’s PWV is low. With abovementioned relationship between arterial stiffness and PWV, state of the patient’s cardiovascular system can be indirectly estimated. In order to accurately measure the patient’s PWV, measurement protocol is established. The measurement protocol consists of five parts; 1) object of measurement, 2) temperature, 3) measurement time, 4) reference point for ECG and APW measurement, and 5) distance b e tween ECG measureme nt p o in t and APW measurement point. In order to remove the interference of temperature effect, indoor temperature is maintained at 25 degree Celsius during the 35 seconds of PWV measurement time. After that, ECG is measured at the healthy volunteer’s chest (V4, V6) and APW is measured at the healthy volunteer’s wrist (radial artery) in order to calculate time difference between the R peak of ECG and the foot of the APW. Finally, the measured distance between ECG reference point and APW reference point is 0.66 m. Fig. 14(a) shows the APW foot detecting method in order to calculate time difference between the R peak of ECG and the foot of APW. The R peak of ECG can be detected by using simple threshold method. However, in order to detect the foot of APW, intersecting tangential method should be used. As shown in Fig. 14(a), the point of maximum APW slope can be detected by first derivation of APW and threshold method. And then, intersecting point between tangent line at the point of maximum APW slope and minimum value of the APW amplitude can be decided as the foot of APW. With abovementioned intersecting tangential method, PWV

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Fig. 13. Implementation results (a) Measurement board, (b) Wrist watch.


can be measured. Fig. 14(b) shows measurement result of the PWV. The average value of PWV and pulse arrival time (PAT) is 5.74 m/second and 115.5 ms, respectively, showing the volunteer’s good cardiovascular state. 2. Accelerated Arterial Pulse Wave Measurement

Accelerated arterial pulse wave (AAPW) is another

cardiovascular indicator reflecting patient’s cardiovascular state. As shown in Fig. 14(c), AAPW can be extracted from the second derivation of APW. In general, AAPW has five meaningful peaks; 1) a peak, 2) b peak, 3) c peak, 4) d peak, and 5) e peak. As shown in the right of Fig. 14(c), if the slope of b-d peak is positive value, the patient’s cardiovascular system is healthy. However, if the slope of b-d peak is negative value, the patient’s cardiovascular system is unhealthy. The extracted AAPW from the measured APW in Fig. 14(c) shows five meaningful peaks and the slope of b-d peak is positive value, indicating the volunteer’s healthy cardiovascular system.

3. Heart Rate Measurement

Heart rate (HR) is another cardiovascular indicator

reflecting electrical characteristic of cardiovascular system. As shown in Fig. 14(d), the average value of HR from the volunteer’s ECG and pulse rate (PR) from the volunteer’s APW are 79.1 and 79.2, respectively. According to the clinical reference, the patient suffered from atrial flutter and atrial fibrillation shows 220~350 beats/minute and 350~650 beats/minute, respectively. Therefore, the Fig. 14(d) indicates the volunteer’s cardiovascular state.

VI. CONCLUSION

In this work, wrist watch type wearable device is realized in order to conveniently and continuously monitor the patient’s cardiovascular system in daily life. For comprehensive monitoring of the patient’s cardiovascular system, the concurrent ECG and APW sensor front-end are fabricated in 0.18 mm CMOS technology. The ECG sensor front-end achieves 84.6-dB CMRR and 2.3-mVrms input referred noise with 30-mW power consumption. The APW sensor front-end achieves

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Fig. 14. Measurement results.(a) APW foot detecting method, (b) Measurement result of pulse wave velocity, (c) Measurement result of accelerated arterial pulse wave, (d) Measurement results of the heart rate and pulse rate.


3.2-V/W sensitivity with accurate bio-impedance measurement lesser than 1% error, consuming only 984 mW. Abovementioned ECG and APW sensor front-end is combined with power management unit, MCU, display and Bluetooth transceiver so that concurrently measured ECG and APW can be transmitted into smartphone, providing patients with their cardiovascular state in real time. In order to verify operation of the cardiovascular monitoring system, cardiovascular indicator is extracted from the healthy volunteer. As a result, PWV (5.74 m/second), HR (79.1 beats/minute) and AAPW (positive slope of b-d peak) are achieved, showing the volunteer’s healthy cardiovascular state.

ACKNOWLEDGMENT

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-R7117-16-0163) supervised by the IITP (Institute for Information & communications Technology Promotion)

REFERENCES

[1] Mendis S, “Global Atlas on Cardiovascular Disease Prevention and Control,” WHO, 2011.

[2] W. Lee, and S. H. Cho, “An Integrated Pulse Wave Velocity Sensor using bio-impedance and Noise-shaped Body Channel Communication,” IEEE Symposium on VLSI Circuits, 2013.

[3] H. Kim, Y. Kim, Y. Kwon, and H.-J. Yoo, "A 1.12mW Continuous Healthcare Monitoring Chip Integrated on A Planar-Fashionable Circuit Board,” IEEE ISSCC Digest of Technical Papers, pp. 150-151, Feb. 2008.

[4] S. Lee, B. Kim, and H.-J. Yoo, “Planar Fashionable Circuit Board and its Applications,” Journal of Semiconductor Technology and Science, vol. 9, no. 3, Sep. 2009.

[5] R.R. Harrison, and C. Charles, “A Low-Power Low-Noise CMOS Amplifier for Neural Recording Applications,” IEEE Journal of Soild-State Circuits, vol. 38, no. 6, Jun. 2003.

[6] M.M. Elsayed, and E. Sanchez-Sinencio, “A Low THD, Low Power, High Output-Swing Time-

Mode-Based Tunable Oscillator Via Digital Harmonic-Cancellation Technique,” IEEE Journal of Soild-State Circuits, vol. 45, no. 5, May. 2010.

[7] W. Lee, and S. H. Cho, “Integrated All Electrical Pulse Wave Velocity and Respiration Sensors using Bio-impedance,” IEEE Journal of Soild-State Circuits, vol. 50, no. 3, Mar. 2015.

Kwonjoon Lee received the B.S. degree (summa cum laude) in electrical engineering from the Sung Kyun Kwan University (SKKU), Suwon, Korea, in 2012, and M.S. degree in electrical engineering from the Korea Advanced Institute of

Science and Technology (KAIST), Daejeon, Korea, in 2014. From 2014 to 2015, he worked at Samsung Electronics for healthcare IC design. He is currently working at K-Healthwear, Daejeon, Korea. His research interests include system design for wearable healthcare device including application searching, specification setting and bio-medical SoC design. He is also interested in bio-signal processing such as electrocardiogram (ECG), electromyogram (EMG) and arterial pulse wave (APW).

Kiseok Song received the B.S., M.S., and Ph.D. degrees in Department of Electrical Engineering from the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, in 2009, 2011, and 2015, respectively. He is currently working

as a CTO of K-Healthwear R&D Center, which is mobile healthcare solution company. His current research interests include bio-medical SoC design especially focused on mobile (wearable) healthcare application. He is also interested in body channel analysis for low power wireless-body-area-network (WBAN). As a chief researcher at the Semiconductor System Laboratory in KAIST, he developed multi-modal (electromyography and temperature) feedback electro-acupuncture stimulator SoC and bio-feedback (load impedance, tissue impedance, and skin temperature) iontophoresis controller SoC. Mr. Song received the Marconi Society’s Paul-Balan Young Scholar Award for his contribution to novel bio-medical communications in 2014.


Taehwan Roh (S’09-M’14) received the B.S., M.S., and Ph.D. degrees in Department of Electrical Engineering from the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, in 2009, 2011, and 2014, respectively. He has researched

a biomedical processor for mental health monitoring and management. He has worked for K-Healthwear to commercialize his researches since 2015. His research interests include a low-power biomedical SoC for wearable healthcare device. He is also interested in wearable healthcare systems for cardiac and mental monitoring.

Hoi-jun Yoo (M’95 – SM’04 – F’08) graduated from the Electronic Department of Seoul National University, Seoul, Korea, in 1983 and received the M.S. and Ph.D. degrees in electrical engineering from the Korea Advanced Institute of

Science and Technology (KAIST), Daejeon, in 1985 and 1988, respectively. Since 1998, he has been the faculty of the Department of Electrical Engineering at KAIST and now is a full professor. From 2001 to 2005, he was the director of Korean System Integration and IP Authoring Research Center (SIPAC). From 2003 to 2005, he was the full time Advisor to Minister of Korea Ministry of Information and Communication and National Project Manager for SoC and Computer. In 2007, he founded System Design Innovation & Application Research Center (SDIA) at KAIST. Since 2010, he has served the general chair of Korean Institute of Next Generation Computing. His current interests are computer vision SoC, body area networks, biomedical devices and circuits. He is a co-author of DRAM Design (Korea: Hongrung, 1996), High Performance DRAM (Korea: Sigma, 1999), Future Memory: FRAM (Korea: Sigma, 2000), Networks on Chips (Morgan Kaufmann, 2006), Low-Power NoC for High-Performance SoC Design (CRC Press, 2008), Circuits at the Nanoscale (CRC Press, 2009), Embedded Memories for Nano-Scale VLSIs (Springer, 2009), Mobile 3D Graphics SoC from Algorithm to Chip (Wiley, 2010), Bio-Medical CMOS

ICs (Springer, 2011), Embedded Systems (Wiley, 2012), and Ultra-Low-Power Short-Range Radios (Springer, 2015). Dr. Yoo received the Electronic Industrial Association of Korea Award for his contribution to DRAM technology in 1994, Hynix Development Award in 1995, the Korea Semiconductor Industry Association Award in 2002, Best Research of KAIST Award in 2007, Scientist/Engineer of this month Award from Ministry of Education, Science and Technology of Korea in 2010, Best Scholarship Awards of KAIST in 2011, and Order of Service Merit from Ministry of Public Administration and Security of Korea in 2011 and has been co-recipients of ASP-DAC Design Award 2001, Outstanding Design Awards of 2005, 2006, 2007, 2010, 2011, 2014 A-SSCC, Student Design Contest Award of 2007, 2008, 2010, 2011 DAC/ISSCC. He has served as a member of the executive committee of ISSCC, Symposium on VLSI, and A-SSCC and the TPC chair of the A-SSCC 2008 and ISWC 2010, IEEE Fellow, IEEE Distinguished Lecturer (’10-’11), Far East Chair of ISSCC (‘11-‘12), Technology Direction Sub-Committee Chair of ISSCC (’13), TPC Vice Chair of ISSCC (’14), and TPC Chair of ISSCC (’15).

a wrist watch-type cardiovascular monitoring system using

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