biosensors Article

Wrist Pulse Rate Monitor Using Self-Injection-Locked Radar Technology Fu-Kang Wang *, Mu-Cyun Tang, Sheng-Chao Su and Tzyy-Sheng Horng Department of Electrical Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan; [email protected] (M.-C.T.); [email protected] (S.-C.S.); [email protected] (T.-S.H.) * Correspondence: [email protected]; Tel.: +886-7-525-2000 (ext. 4182) Academic Editor: Donald Y.C. Lie Received: 1 September 2016; Accepted: 19 October 2016; Published: 26 October 2016

Abstract: To achieve sensitivity, comfort, and durability in vital sign monitoring, this study explores the use of radar technologies in wearable devices. The study first detected the respiratory rates and heart rates of a subject at a one-meter distance using a self-injection-locked (SIL) radar and a conventional continuous-wave (CW) radar to compare the sensitivity versus power consumption between the two radars. Then, a pulse rate monitor was constructed based on a bistatic SIL radar architecture. This monitor uses an active antenna that is composed of a SIL oscillator (SILO) and a patch antenna. When attached to a band worn on the subject’s wrist, the active antenna can monitor the pulse on the subject’s wrist by modulating the SILO with the associated Doppler signal. Subsequently, the SILO’s output signal is received and demodulated by a remote frequency discriminator to obtain the pulse rate information. Keywords: wrist pulse rate monitor; continuous-wave (CW) radar; self-injection-locked (SIL) radar; bistatic radar architecture

1. Introduction Heart rate variability (HRV) refers to the variation in the time interval between heartbeats. Because of HRV’s potential of providing critical information regarding mental and physical treatments and fitness tracking [1–4], the use of wearables to conduct long-term monitoring of heart/pulse rates of subjects has become increasingly commonplace [5], and various consumer products such as Fitbit wristbands and the Apple Watch have been developed in succession. Table 1 compares common techniques of vital sign detection. Accelerometers measure the variations in resistance, voltage, or capacitance caused by change in shape or position of an inertial device to obtain the motion of an object. They can detect acceleration, vibration, and angle of tilt. Recently, in combination with various smart handheld devices, the application of accelerometers has been successful in detecting the rise and fall of the chest to obtain respiratory information with low system complexity and a 1.65 mW power consumption [6]; however, the sensitivity of this technology is insufficient for monitoring the heart rate. Table 1. Comparison of vital-sign sensing techniques. Technology

Sensitivity

Sensing Style

System Complexity

Power Consumption

Accelerometer Piezoelectric device Electrocardiography (ECG) Photoplethysmography (PPG) Pulse radar CW radar SIL bistatic radar

Low Low High High High High High

Wearable Contact Contact Wearable Wearable Non-contact Wearable

Low Low High High High High Low

Low Low Low High High Medium Low

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When applying pressure to specific solid materials, a voltage difference is created across the opposite sides of the pressured surface. This conversion of mechanical force to electricity is called the “direct piezoelectric effect”. After modifying the piezoelectric material and the thickness of the substrate, a piezoelectric device can be placed at the wrist radial artery of the subject to measure the pulse rate [7]. In electrocardiography (ECG), electrodes are attached near the heart, and the potential differences captured by the electrodes are amplified by an instrumentation amplifier to obtain bioelectrical signals transmitted through nervous conduction. Consisting of a P wave, a QRS complex, and a T wave, the waveforms of such signals can show depolarization and repolarization of the atria and ventricles [8]. Piezoelectric devices and ECG both require direct skin contact to detect displacement and voltage variation. The contact may cause skin irritation and makes similar methods unsuitable for burn patients and patients with external bleeding. Although dry electrodes are expected to replace conventional wet electrodes that use gel, their widespread use is difficult because the high impedance between skin and electrode often causes the instability of signal conduction [9]. Moreover, the difficulty is further intensified by the requirement of an instrumentation amplifier with high gain, low noise, and low power consumption to amplify tiny output signals for piezoelectric and ECG devices. Another common noninvasive detection technology is photoplethysmography (PPG). First proposed in the 1930s [10], it mainly comprises a light source and sensors, illuminating the skin with red, green, or infrared light. Hemoglobin (Hgb) in the blood affects the skin’s reflection of light, and by detecting the contraction of blood vessels, it is possible to obtain the pulse rate. In recent years, applications of pulse rate monitoring have broadened from fingertip measurement and wrist-worn fitness trackers to non-contact facial detection [11–15]. However, the complexity of system architecture also leads to excessive cost and power consumption. Another drawback of PPG, however, is that it is susceptible to environmental and physical interruption in its detection [16], such as due to the tightness of the wristband, the shape of the wrist, the location of blood vessels, skin color, ambient light, and skin features including moles, birthmarks, and tattoos, all of which can affect the accuracy of detection. Moreover, detection cannot be performed on clothed bodies. In light of this, the electromagnetic wave is introduced because of its ability to penetrate non-metal materials and its beyond visual range. Radar technology was first used in non-contact vital sign detection in 1970 [17], and its applications later extended to disaster rescue [18] and remote healthcare [19,20]. Based on the signals emitted, radar systems can be categorized into pulse radars and continuous-wave (CW) radars. Pulse radars emit a series of radio frequency (RF) pulse sequences and obtain the distance and motion information of an object according to the time delay and waveform fluctuations of echo signals. With a programmable switch [21], pulse radars can emit and receive radio frequency (RF) signals only at specific intervals, thereby avoiding electromagnetic interference (EMI) issues, reducing clutter in the environment, and decreasing power dissipation. In 2013, Lin proposed a wearable pulse radar device [22], with a pulse duration of 5 ns, to conduct near-field detection on wrist veins. However, because the system required concurrency control and two independent antennas to prevent a radar blind zone in which the pulse rate could not be detected, the design involved high complexity and high cost. CW radars consistently emit signals and receive signals reflected from objects, and therefore do not suffer from blind zones. However, the clutter problem still needs to be solved. Sources of clutter include additional stationary objects and transmitter-receiver coupling in the system. Common solutions to the clutter problem include introducing a dual-antenna architecture, implementing a single antenna with high-isolation components to prevent crossover issues [23], and generating signals with the same amplitude with clutter but with an inverted phase [24]. These methods pose challenges to the battery life and the device form factor that falls within a wearable size. To the best of my knowledge, no wrist-worn pulse monitoring device based on conventional CW radar technology currently exists. In 2010, self-injection-locked (SIL) radar was first proposed and used in non-contact detection of vital signs [25]. The SIL radar is essentially a type of CW radar that transmits a signal from an oscillator to the chest of the subject and then receives the reflected signal for injection locking the

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oscillator. The Doppler effect created by respiration and heartbeats causes the oscillator’s output signals to be frequency-modulated, and vital signs of the subject can be obtained once the output signals are demodulated by the back-end frequency discriminator. In addition to outstanding sensitivity, this architecture has the advantage of not being easily affected by TX-RX coupling, making it suitable for single-antenna operation [26]. Furthermore, this technology allows the SIL oscillator (SILO) and the frequency discriminator, with an antenna installed for each of them, to be placed at different locations in a bistatic architecture [27]. Implementing the features above, a chest-worn health monitor was recently reported to be capable of monitoring the respiration, heart rate, and pace of an exercising subject at the same time by processing demodulated signals using joint time frequency analysis and moving average filtering [28]. In Section 2, this study compares remote vital sign monitoring capabilities of conventional CW radar and SIL radar, and proves that the latter achieves a similar sensitivity with much lower power consumption than the former. Section 3 discloses and analyzes a wrist pulse rate monitor based on a bistatic SIL radar architecture. Experiment results of pulse rate monitoring are presented in Section 4. The monitor implements an SILO-based active antenna on a wristband to modulate the transmitted signal using the Doppler signal generated by pulse motion, and utilizes an injection-locked oscillator (ILO)-based frequency discriminator to receive and demodulate the transmitted signal at a remote location. Section 5 of this study is its conclusion. 2. Comparison between Conventional CW Radar and SIL Radar As shown in Figure 1, the conventional CW radar architecture comprises one transmit (TX) antenna and one receive (RX) antenna, both of which are panel antennas with an antenna gain of 12 dBi, one two-stage low-noise amplifier (LNA) with a power gain of 23 dB, one voltage-controlled oscillator (VCO), two power splitters, one quadrature mixer, two lowpass filters (LPFs), and one digital signal processor (DSP). The operating principle is as follows. The VCO generates continuous RF signals that are divided into two outputs by Splitter 1. One output of the signal passes through the quadrature power splitter, which further divides the signal into two output signals to pump the quadrature mixers. The other output signal, STX (t), from Splitter 1 is radiated by the TX antenna toward the chest of the subject one meter from the radar. Next to the subject, an additional 60 × 60 cm2 metal plate is installed for stronger signal reflection. Therefore, the RX antenna will receive two types of signals. One is the Doppler signal, Sd (t), from the chest of the subject. Respiration and heartbeats cause the chest to rise and fall, which phase-modulates the emitted signal STX (t). The other is the clutter signal, Sc (t), from other body parts of the subject and the metal plate. Stationary during the detection process, Sc (t) is an attenuated and time-delayed version of STX (t). After being received by the RX antenna, Sd (t) and Sc (t) go through a two-stage LNA and are then divided into two outputs by Splitter 2 for feeding the input ports of the quadrature mixer. After the lowpass filter (LPF) filters out the high-order intermodulation components from the output signals of the quadrature mixer, the in-phase signal S I (t) and quadrature signal SQ (t) are output to the DSP with a built-in analog-to-digital converter (ADC) for subsequent signal processing and analysis from which the vital sign information of the subject can be obtained. Figure 2 shows the system architecture of the SIL radar. As opposed to Figure 1, this circuit adopts a SILO, which has an additional injection port, as compared to conventional VCO, for injection signal input. Moreover, the radar uses an additional power splitter and a delay line that provides a delay time of τd . This architecture, however, omits two-stage LNA; in other words, the SILO is the only active component in the system. In operation, the reflection signals received by the RX antenna are injected into the SILO. Meanwhile, the rise and fall of the subject’s chest causes the SILO to output frequency modulated (FM) signals as a result of the SIL effect [25]. The other output of Splitter 1 is connected to a quadrature mixer-type frequency discriminator [29]. Splitter 2 divides the FM signals from Splitter 1 into two outputs; one is used as the local oscillator (LO) signals for the quadrature mixer, and the other is entered into the cable assembly used as the delay line. The delay line provided

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27 ns of by time delay and 2.5two dB of powerthat loss.are The delayed signals further by Splitter into divided Splitter 3 into outputs fed into the inputare port of thedivided quadrature mixer.3 The divided by Splitter into two outputs thatwhich arethe fed into the input ofmixer’s the quadrature mixer.pass The two outputs that are3fed into the input port of quadrature mixer. The output signals mixer’s output signals pass through LPFs, output andport to the DSP. mixer’s output signals pass through LPFs, which output and to the DSP. through LPFs, which output S I (t) and SQ (t) to the DSP. 2-stage LNA 2-stage LNA

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Figure 1. Conventional CW radar for non-contact vital sign monitoring. Figure 1. Conventional CW radar for non-contact vital sign monitoring.

The prototypes based on conventional CW and SIL radar technology operate at the 802.11 The prototypes based conventional SIL technology operate at the b/g/n 802.11 b/g/n The frequency band of 2.4–2.5 GHz to take advantage of radar using low-cost Wi-Fi and prototypes based onon conventional CWCW andand SIL radar technology operate atcomponents the 802.11 b/g/n frequency band of 2.4–2.5 GHz to take advantage of using low-cost Wi-Fi components and antennas. VCO in Figure and theadvantage SILO in Figure 2 are self-made Figureand 3 shows the frequencyThe band of 2.4–2.5 GHz1 to take of using low-cost Wi-Ficircuits. components antennas. antennas. The VCO in Figure 1 and the SILO in Figure 2 are self-made circuits. Figure 3 shows schematic photograph of the SILO circuit,2which has a tuning rangeFigure from 2.3 to 2.65the GHz and the an The VCO and in Figure 1 and the SILO in Figure are self-made circuits. 3 shows schematic schematic and photograph of the SILO circuit, which has a tuning range from 2.3 to 2.65 GHz and an output power of 10 dBm. Notably, the design of the SILO uses the Clapp configuration along with an and photograph of the SILO circuit, which has a tuning range from 2.3 to 2.65 GHz and an output output power of 10 dBm. Notably, the design of the SILO uses the Clapp configuration along with an injection connected tothe thedesign gate ofofthe When theconfiguration injection portalong is terminated by 50 power of port 10 dBm. Notably, the transistor. SILO uses the Clapp with an injection injection port to ofThe theWhen transistor. When the portradar is byare 50 ohm, it can be connected used a regular VCO. rest ofthe theinjection components the two port connected to theasgate ofthe the gate transistor. portinjection isinterminated byterminated 50prototypes ohm, it can be ohm, it can be used as a regular VCO. The rest of the components in the two radar prototypes are basically the same commercial off-the-shelf items. In Figures 1 and 2, because the SIL radar uses one used as a regular VCO. The rest of the components in the two radar prototypes are basically the same basically theoff-the-shelf same commercial off-the-shelf items. Inthe Figures 1SIL andradar 2, are because the SIL radar uses one extra power splitter, the LO powers of the1mixers two 4 and 1 extra dBm, respectively. commercial items. In Figures and 2, in because thesystems uses one power splitter, extra power splitter, the LO powers of ZEM4300+ the mixers in the by two systems are 4with and dBm, The mixers used the experiment are Mini-Circuits, a1 conversion of the LO powers ofinthe mixers in the two systems aremade 4 and 1 dBm, respectively. The mixersrespectively. usedloss in the The mixers used in the experiment are ZEM4300+ made by Mini-Circuits, with a conversion loss of about 9 dB. are ZEM4300+ made by Mini-Circuits, with a conversion loss of about 9 dB. experiment about 9 dB.

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Figure Figure2.2.SIL SILradar radarfor fornon-contact non-contactvital vitalsign signmonitoring. monitoring. Figure 2. SIL radar for non-contact vital sign monitoring.

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Figure 3. Schematic and photograph of the S-band SILO. Figure Figure3.3.Schematic Schematicand andphotograph photographof ofthe theS-band S-bandSILO. SILO.

Figure 4 shows the in-phase/quadrature (I/Q) baseband signals measured with the architecture Figure1.4 Because shows the in-phase/quadrature (I/Q) basebandchest signals measured with architecture in Figure respiration causes more significant displacement thanthe heartbeats, the Figure 4 shows the in-phase/quadrature (I/Q) baseband signals measured with the architecture in in Figure 1.inBecause causes respiration, more significant chest displacement than waveform Figure respiration 4 mainly reflects and the minor fluctuations areheartbeats, the resultsthe of Figure 1. Because respiration causes more significant chest displacement than heartbeats, the waveform waveform in Figure 4 mainly reflects respiration, and the minor fluctuations are the results of heartbeats. Other notable aspects are clutter signals in the environment and imperfections in the in Figure 4 mainly reflects respiration, and the minor fluctuations are the results of heartbeats. Other heartbeats. Other are clutter signals the environment and imperfections in and the components, suchnotable as the aspects LO-RF feedthrough of theinmixer, mismatch between components, notable aspects are clutter signals in the environment and imperfections in the components, such as the components, suchThe as the LO-RF feedthrough of thebymixer, mismatch components, TX-RX coupling. additional DC offset caused TX-RX couplingbetween can be eliminated byand the LO-RF feedthrough of the mixer, mismatch between components, and TX-RX coupling. The additional TX-RX coupling. The proposed additionalinDC optimization method [30].offset caused by TX-RX coupling can be eliminated by the DC offset caused by TX-RX coupling can be eliminated by the optimization method proposed in [30]. optimization method proposed in [30]. q (1) − − + −
2 _ , _ ,
= min _ _ 2 − A Opt VDC_I , VDC_Q , A = min S t − V + S t − V ( ( ) ) ( ) I DC_I Q DC_Q (1)(1) − − = min + − _ , _ , _ _ In Equation (1), _ and _ are the DC offsets of the IQ baseband signals. Because of path In Equation (1), VDC_I and V arethe the DC offsetsnot of the the IQsame. basebandissignals. signals. Because ofpath path Equation (1), and are offsets of baseband Because of and In phase differences, these two areDC usually theIQ the ideal magnitude. DC_Q _ _ DCs and phase differences, these two DCs are usually not the same. A is the ideal magnitude. Substituting and phase differences, these mV twoand DCs are usually notmV theinto same. following is the formulas ideal magnitude. Substituting −79.77 _ with 159.38 _ with VDC_I with 159.38 mV and V with − 79.77 mV into the following formulas Substituting with 159.38 mV and with −79.77 mV into the following formulas DC_Q _ _ − − _ IQ Phase = tan (2)
! − − _ − _ IQ Phase = tan (2) −1 − SQ ( t ) − VDC_Q IQ Phase = tan (2) _ ) − VDC_I (S I (t) − (3) − − IQ Magnitude = + _ _ q
2 2 (3)(3) − VDC_I _ ) + _ IQ IQ Magnitude Magnitude == (S I (t) − + SQ (t− ) − VDC_Q yields the demodulated phase and magnitude, represented by the black and grey lines, respectively, yields the5a, demodulated phaseand andmagnitude, magnitude, represented bythe theblack black andgrey grey lines, respectively, respectively, yields the demodulated represented by and lines, in Figure where the phase magnitude is around 181 mV. Performing fast Fourier transform on the IQ in Figure Figure where magnitude is is around 181181 mV.mV. Performing fast fast Fourier transform on theonIQthe phase in 5a, where the magnitude around Performing transform IQ phase in 5a, Figure 5athe gives the frequency spectrum shown in Figure 5b,Fourier where the respiratory and in Figure 5a gives the frequency spectrum shown in Figure 5b, where the respiratory and heart rates are, phase in Figure 5a gives the 11.7 frequency spectrum shown in Figure where the respiratory and heart rates are, respectively, and 75.6 beats per minute and 5b,peak values 2.611 and 0.564 respectively, 11.7respectively, and 75.6 beats perand minute peak values 2.611 0.564 degrees, heart rates are, 11.7 75.6 and beatsthe per minute and theand peak values 2.611respectively. and 0.564 degrees, respectively. degrees, respectively. 30

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Figure non-contact vital sign detection using the conventional CW radar: (a) I Figure 4. 4. Baseband Basebandsignals signalsforfor non-contact vital sign detection using the conventional CW radar: signal; (b) Q signal. Figure 4. Baseband signals for non-contact vital sign detection using the conventional CW radar: (a) I (a) I signal; (b) Q signal. signal; (b) Q signal.

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(a) (b) Figure5.5.Vital Vitalsign signdetection detection resultsusing usingthe theconventional conventionalCW CWradar: radar:(a) (a)IQ IQmagnitude magnitudeand andphase; phase; Figure results (b)Spectrum Spectrumof ofIQ IQdetection phasein inFigure Figure 5a. (b) 5a. Figure results using Figure5.5.Vital Vitalsign signphase detection results usingthe theconventional conventionalCW CW radar: radar: (a) (a) IQ IQ magnitude magnitude and phase; (b) (b)Spectrum SpectrumofofIQ IQphase phaseininFigure Figure5a. 5a.

Figure 66 shows shows the the IQ IQ signals signals measured measured with with the the architecture architecture in in Figure Figure 2.2. The The additional additional DC DC Figure offsets of the two signals are 65.345 mV and −36.113 mV, respectively. Although it has been proven offsets of the two signals 65.345 mV andwith −36.113 mV,architecture respectively. itThe hasadditional been Figure 6 6shows thethe IQare signals measured the architecture in Figure 2. The2.additional DCproven offsets Figure shows IQ signals measured with the inAlthough Figure DC that clutter signals have limited influence on the SIL radar [26], hardware imperfections still cause that clutter signals have limited influence on the SIL radar [26], hardware imperfections still cause of the two signals are 65.345 mV and − 36.113 mV, respectively. Although it has been proven that clutter offsets of the two signals are 65.345 mV and −36.113 mV, respectively. Although it has been proven additional DC offset. Compared with the conventional CW radar, however, however, the additional extent additional offset. Compared the conventional CW radar, the extent isis signals haveDC limited influence oninfluence thewith SIL radar [26], imperfections still cause that clutter signals have limited on the SILhardware radar [26], hardware imperfections still cause significantly less. As shown in Figure 7a, the demodulated amplitude is around 207 mV. Figure 7b significantly less. offset. As shown in 7a, the amplitude is around mV. 7bis DC offset. Compared with theFigure conventional CW radar, however, the extent is207 significantly additional DC Compared with thedemodulated conventional CW radar, however, the Figure extentless. shows the IQ phase frequency spectrum, in which the peak values of respiration and heartbeat are shows the IQ phase frequency spectrum, in which the peak values of respiration and heartbeat are As shown in Figure 7a, the demodulated amplitude is around 207 mV. Figure 7b shows the IQ phase significantly less. As shown in Figure 7a, the demodulated amplitude is around 207 mV. Figure 7b 7.785 and 2.458 degrees, respectively, andthe thewhich respiratory and heart rates are7.785 11.4and and 76.2 beats per 7.785 and 2.458 degrees, respectively, respiratory and heart rates are 11.4 beats per frequency infrequency which thespectrum, peakand values of respiration and heartbeat and 2.458 degrees, shows thespectrum, IQ phase in the peak values of respiration and76.2 heartbeat are minute, respectively. minute, respectively. respectively, and degrees, the respiratory and heart are 11.4 and 76.2 beats perare minute, respectively. 7.785 and 2.458 respectively, andrates the respiratory and heart rates 11.4 and 76.2 beats per minute, respectively. 0

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(a) for (b) Figure Basebandsignals signals for non-contact vital sign detection using the SIL radar: (a) I signal; Figure6.6.Baseband Baseband signals for non-contact vital sign detection using theSIL SILradar: radar: (a)IIsignal; signal; (b)QQ Figure non-contact vital sign detection using the (a) (b) (b) Q signal. signal. signal. Figure 6. Baseband signals for non-contact vital sign detection using the SIL radar: (a) I signal; (b) Q signal. -130 210 9 9

Respiration@@0.190 0.190Hz Hz Respiration Peak==7.785 7.785(Deg) (Deg) Peak

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(a) (b) Figure results the SIL radar: (a) IQ magnitude and phase; (b)(b) Spectrum of Figure7. Vitalsign signdetection detection resultsusing using the SIL radar: (a) IQ magnitude and phase; (b) Spectrum Figure 7.7.Vital Vital sign detection results using the SIL radar: (a) IQ magnitude and phase; Spectrum IQ phase in Figure 6a. of IQ phase in Figure 6a. of IQ phase in Figure 6a. Figure 7. Vital sign detection results using the SIL radar: (a) IQ magnitude and phase; (b) Spectrum of IQ phase in Figure 6a.

By similar IQ magnitude and phase results, but but the the SIL SIL radar radar Bycomparison, comparison,both bothradars radarsachieve achievesimilar similarIQ IQmagnitude magnitudeand andphase phaseresults, By comparison, both radars achieve obviously consumes much less power because no LNAs are involved. The above experiment proves obviously consumesmuch much lesspower power because noIQ LNAs areinvolved. involved. Theabove above obviously consumes less because no LNAs are The experiment proves By comparison, both radars achieve similar magnitude and phase results, but the SIL radar that the SIL radar offers better sensitivity and can reduce the number of active components to that the SIL radar offers better sensitivity and can reduce the number of active components that the SIL radar offers better sensitivity and can reduce the number of active components to obviously consumes much less power because no LNAs are involved. The above experiment proves increase endurance. In addition, the SIL radar can be separated into two parts—SILO and frequency increase endurance. In addition, the SIL radar can be separated into two parts—SILO increase addition, SIL radarand can can be separated intonumber two parts—SILO and frequency that theendurance. SIL radar In offers betterthe sensitivity reduce the of active components to discriminator—for the detection of of vital signs withwith a bistatic architecture [28], which further reduces discriminator—for the detection of vital signs with a bistatic architecture [28], further discriminator—for the detection vital signs a bistatic architecture [28], which further increase endurance. In addition, the SIL radar can be separated into two parts—SILO which and frequency the size of the wearable device and therefore providesprovides improved comfort.comfort. reduces the size ofthe the wearable device andtherefore therefore provides improved comfort. reduces the size of device and improved discriminator—for thewearable detection of vital signs with a bistatic architecture [28], which further reduces the size of the wearable device and therefore provides improved comfort.

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3. 3. Wrist-Worn Wrist-WornPulse PulseRate RateMonitor MonitorBased Basedon onaaBistatic BistaticSIL SILRadar RadarArchitecture Architecture Figure showsaapulse pulserate ratemonitoring monitoring system proposed by this study. The system hasparts. two Figure 88 shows system proposed by this study. The system has two parts. The first is an active antenna on a wristband that consists of a patch antenna and a SILO. The The first is an active antenna on a wristband that consists of a patch antenna and a SILO. The SILO’s SILO’s output signal, , is transmitted by the patch antenna, and the echo signal from output signal, Sout (t), is transmitted by the patch antenna, and the echo signal from the wristthe is wrist is received by the same antenna as , which makes the SILO operate in a SIL state. It is received by the same antenna as Sinj (t), which makes the SILO operate in a SIL state. It is worth worth nostage buffer stagehigh-isolation or other high-isolation required between noting noting that no that buffer or other componentscomponents are requiredare between the SILO and the the SILO and the patch antenna to distinguish between and . The Doppler effect of pulse patch antenna to distinguish between Sout (t) and Sinj (t). The Doppler effect of pulse motion causes motion to becarrying an FM signal carryinginformation. pulse motionThe information. The partdelay is a Sout (t) causes to be an FM signal pulse motion second part is second a wireless wireless delay discriminator, which consists of one RX antenna, one LNA, one power splitter, one discriminator, which consists of one RX antenna, one LNA, one power splitter, one mixer, and one ILO. mixer, and one ILO. The output signal fromby the is received by the RX The output signal from the SILO is received theSILO RX antenna, amplified, andantenna, divided amplified, to be fed toand the divided to be fed to the input of the mixer and the ILO. Here, the ILO serves as the variable delay input of the mixer and the ILO. Here, the ILO serves as the variable delay element with high frequency element with high frequency selectivity, its output signal is used to pump themixer mixer.isAfter the selectivity, and its output signal is used toand pump the mixer. After the output of the sampled output of the mixer is sampled by the ADC and passed through the digital bandpass filter, by the ADC and passed through the digital bandpass filter, SBPF (t) can then be used to determine can then used to determine pulse rate information. pulse ratebeinformation.

Figure 8. 8. Block Blockdiagram diagramof ofthe theproposed proposed bistatic bistaticSIL SILradar radararchitecture architecture for for aa wrist wrist pulse pulse rate rate monitor. monitor. Figure

Before commencing derivation, we we first first definedefine the inherent oscillation signal, injection Before commencingtheoretical theoretical derivation, the inherent oscillation signal, signal, and output signal of the SILO as S t , S t , and S t . When not affected injection ( ) ( ) ( ) osc as inj out, and injection signal, and output signal of the SILO , . When not by affected by signals, S t is equal to S t . The SILO has a constant inherent frequency ω and an amplitude ( ) ( ) osc out osc is equal to . The SILO has a constant inherent frequency injection signals, and Eoscamplitude . When the output signal reflected from the wrist from and received be used as injection signal an . When the is output signal is reflected the wristtoand received to be used as S t with a constant amplitude, the injection frequency E . is modulated by Doppler phase shift, ( ) inj inj injection signal with a constant amplitude, the injection frequency . is modulated by represented as ω output signal, Eout , remains same, while the frequency is ). Now, the SILO’s inj ( trepresented Doppler phase shift, as . Now, the SILO’s outputthe signal, , remains the same, influenced by the SIL effect. Based on the previous study [26], the instantaneous output frequency of while the frequency is influenced by the SIL effect. Based on the previous study [26], the the SILO can be expressed as instantaneous output frequency of the SILO can be expressed as

= ωosc − − ω LR,osc sin , ωout (t) = sinα (t)..

(4) (4)

in Equation Equation (4) (4) is is the the locking locking range range of of the the SILO, SILO, which which can can be be represented represented as as , ω LR,osc in = ωosc × Einj (5) , ω LR,osc = 2 × (5) 2Q Eosc where is the quality factor of the SILO’s resonant circuit. In Equation (4), is the where Q is the quality factor of the SILO’s resonant circuit. In Equation (4), α t is the propagation ( ) propagation phase delay caused by the SIL path, which means phase delay caused by the SIL path, which means 2 (6) + =
2ωosc α (t) = R + x p (t) (6) c where and are the initial distance between the active antenna and the wrist and the skin surface displacement caused by pulse motion, respectively; denotes the speed of light. where R and x p (t) are the initial distance between the active antenna and the wrist and the skin surface In addition to being used to illuminate the location of the radial artery and to detect the slight displacement caused by pulse motion, respectively; c denotes the speed of light. displacement of the skin surface, the SILO’s output signal, , can be wirelessly transferred to the frequency discriminator, at a distance of from the patch antenna, to be demodulated. As

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In addition to being used to illuminate the location of the radial artery and to detect the slight displacement of the skin surface, the SILO’s output signal, Sout (t), can be wirelessly transferred to the frequency discriminator, at a distance of d from the patch antenna, to be demodulated. As shown in Figure 8, Sout (t) is received by the RX antenna, LNA-amplified, divided into two outputs by the power splitter, and fed to the mixer and ILO. The input signal S I N (t) can be found as 




S I N (t) = E I N cos ωosc t − τp − ω LR,osc

Z t−τp 0

0




0



sinα t dt + θ0

(7)

In Equation (7), E I N and θ0 are the constant input amplitude and initial phase, respectively; τp is the transmission delay from the active antenna to the frequency discriminator, namely d/c. When ILO is injection-locked by S I N (t), the output signal of ILO, based on the derivation above [27], is given as  Z
S ILO (t) = E ILO cos ωosc t − τp − τIL − ω LR,osc

t−τp −τIL 0


sinα t0 dt0 + θ0

 (8)

where E ILO is the constant output amplitude of S ILO (t). By comparing Equations (7) and (8), it is clear that the phase component of S ILO (t) is synchronized by S I N (t), yet injection locking provides an additional time delay, τIL , which is estimated as τIL = q

1 ω LR,ILO 2 − ∆ωosc 2

(9)

where ω LR,ILO is the locking range of the ILO; ∆ωosc is the frequency difference between the SILO and the ILO signal. The output signal of the mixer passes through the ADC and digital bandpass filter to remove DC components and high-order intermodulation components. According to Equation (9), by adjusting the inherent frequency of the SILO and the ILO, the following conditions can be fulfilled. (

ωosc τIL = (n + 0.5) × π ωosc 2d c = n×π

(10)

In Equations (10), n is a natural number. Assume that 2ωosc x p (t) /c  1, and the bandpass-filtered output signal can be approximated as SBPF (t) =


2Gc E I N ωosc ω LR,osc τIL × x p t − τp c

(11)

where Gc is the conversion gain of the mixer. Because τp is far shorter than the cycle of physiological
signals, x p t − τp can be considered as x p (t). We can therefore obtain the pulse rate information of the subject from Equation (11). 4. Experimental Results and Discussion Figure 9 presents the photograph of the implemented pulse rate monitoring system. According to the authors’ previous research [25], when the operating frequency doubles, the signal-to-noise ratio (SNR) gain of the SIL radar quadruples. Because the displacement fluctuations caused by the radial artery pulse are weaker than those caused by heartbeats, the prototype in this study operated at the 5.2 GHz unlicensed band to improve the detection sensitivity. As shown in Figure 9a, the SILO is based on a Colpitts oscillator and powered by a 3 V button battery. The current consumption is 9 mA, the operating frequency is 5.2 GHz, and the output power is 7 dBm. The size of the PCB is 2.5 × 2 cm2 . The output port of the SILO is connected to a patch antenna with a gain of 7 dBi. The antenna is attached to the inner side of the wristband, indicated by the red circle of dotted lines in the figure, to detect the pulse motion. The size of the antenna is 2.2 × 2.2 cm2 . The RF signal from the active antenna is received by the remote frequency discriminator, at a distance up to 60 cm. Figure 9b is

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a photograph of the frequency discriminator. The ILO design is similar to that shown in Figure 3, with the resonance circuit adjusted to operate at 5.2 GHz with an output power of 7 dBm. It can pump the mixer while providing a time delay to demodulate the FM signal received by the horn antenna. Other components Biosensors 2016, 6, 54 are commercially available products whose key specifications are listed in 9Table of 11 2.

(a)

(b)

Figure 9. Photograph of the wrist pulse rate monitor. (a) Active antenna wristband; (b) Frequency Figure 9. Photograph of the wrist pulse rate monitor. (a) Active antenna wristband; discriminator. (b) Frequency discriminator. Table 2. List of components used in the wrist-worn pulse rate monitor. Table 2. List of components used in the wrist-worn pulse rate monitor. Component Model Number Operating Frequency Specifications Active antenna Component Model Number Operating Frequency Specifications SILO Self-made PCB 5.1–5.3 GHz Output power: 7 dBm Active antenna Patch antenna Self-made PCB 5.1–5.3 GHz Antenna gain: 7 dBi SILO Self-made PCB 5.1–5.3 GHz Output power: 7 dBm Frequency discriminator Patch antenna Self-made PCB 5.1–5.3 GHz Antenna gain: 7 dBi Horn antenna HA-08M18G-NF 0.8–18 GHz Antenna gain: 12 dBi @ 5.2 GHz LNA ZX60-542LN-S+ Frequency 4.4–5.4 GHz Gain: 24 dB; Noise figure: 1.9 dB discriminator Splitter 0120A0220800 2–8 GHz GHz Insertiongain: loss:12 3.6dBi dB@ 5.2 GHz Horn antenna HA-08M18G-NF 0.8–18 Antenna ILO Self-made PCB 5.1–5.3 GHz Output power: 7 dBm LNA ZX60-542LN-S+ 4.4–5.4 GHz Gain: 24 dB; Noise figure: 1.9 dB Conversion loss: 5 dB; Mixer ZMX-7GR 3.7–7 GHz Splitter 0120A0220800 2–8 GHz LOInsertion power: 7loss: dBm3.6 dB ILO

Self-made PCB

5.1–5.3 GHz

Output power: 7 dBm

0

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Spectrum of Band-pass Filtered Baseband SIgnal S BPF (t) (mV)

Bandpass Filtered Baseband Signal S BPF (t) (mV)

After sampling the mixer’s output signal with NI 9215 DAQ, Matlab is used for5 dB; subsequent Conversion loss: Mixer ZMX-7GR 3.7–7 GHz power: 7 dBm signal processing and analysis. Figure 10a indicates the detection of theLO bandpass-filtered output signal when the subject, who wore a short-sleeve shirt, placed his arm flat on the table. The waveform represents skin surface displacement byDAQ, the pulse on the The After sampling thethe mixer’s output signal withcaused NI 9215 Matlab is subject’s used forwrist. subsequent passband of the digital bandpass filter is from 0.5 to 3 Hz. Figure 10b shows the frequency spectrum signal processing and analysis. Figure 10a indicates the detection of the bandpass-filtered output of Figure 10a. The pulse rate of the subject is 100.5 beats per minute, with a peak value of 1.8 mV. signal when the subject, who wore a short-sleeve shirt, placed his arm flat on the table. The waveform This system uses electromagnetic waves as the detection medium, which can penetrate non-metal represents the skin surface displacement caused by the pulse on the subject’s wrist. The passband of materials for pulse detection. Figure 11 shows the pulse detection results when wearing the active the digital bandpass filter is from 0.5 to 3 Hz. Figure 10b shows the frequency spectrum of Figure 10a. antenna wristband on a clothed target area clothed. As a detection result, the pulse rate is 93.6 beats The pulse ratewith of the subject is 100.5 beats minute, peak value of than 1.8 mV. system uses per minute, a peak value of 1.18 mV.per Though thiswith peaka value is lower thatThis in Figure 10b, electromagnetic waves as the detection medium, which can penetrate non-metal materials for pulse the pulse rate information is still accurate. detection. Figure 11 shows the pulse detection results when wearing the active antenna wristband on a clothed10 target area clothed. As a detection result, the pulse rate is 93.6 beats per minute, with a peak 2 Pulse @ 1.675 value of 1.18 mV. Though this peak value is lower than that in Figure 10b, the pulse rateHzinformation is Peak = 1.800 (mV) 5 1.5 still accurate. 1

0.5

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Figure 10. Pulse detection results for the subject wearing a short-sleeved shirt: (a) Bandpass-filtered baseband signal; (b) Spectrum of Figure 10a.

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Spectrum of Band-pass Filtered Baseband SIgnal S BPF (t) (mV)

Bandpass Filtered Baseband Signal S BPF (t) (mV)

of Figure 10a. The pulse rate of the subject is 100.5 beats per minute, with a peak value of 1.8 mV. This system uses electromagnetic waves as the detection medium, which can penetrate non-metal materials for pulse detection. Figure 11 shows the pulse detection results when wearing the active antenna wristband on a clothed target area clothed. As a detection result, the pulse rate is 93.6 beats per minute, with a peak value of 1.18 mV. Though this peak value is lower than that in Figure1010b, Biosensors 2016, 6, 54 of 12 the pulse rate information is still accurate. 2 Pulse @ 1.675 Hz Peak = 1.800 (mV) 1.5

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Figure short-sleeved shirt: shirt: (a) Figure 10. 10. Pulse Pulse detection detection results results for for the the subject subject wearing wearing aa short-sleeved (a) Bandpass-filtered Bandpass-filtered baseband signal; (b) Spectrum of Figure 10a. baseband signal; (b) Spectrum of Figure 10a.

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Spectrum of Band-pass Filtered Baseband SIgnal S BPF (t) (mV)

Bandpass Filtered Baseband Signal S BPF (t) (mV)

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1.5 Pulse @ 1.560 Hz Peak = 1.180 (mV)

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Figure the subject subject wearing wearing aa long-sleeved long-sleeved shirt: shirt: (a) (a) Bandpass-filtered Bandpass-filtered Figure 11. 11. Pulse Pulse detection detection results results for for the baseband signal; (b) Spectrum of Figure 11a. baseband signal; (b) Spectrum of Figure 11a.

The relative motion between the active antenna and the wrist, such as hand-waving, fidgeting, The relative motion between the active antenna and the wrist, such as hand-waving, fidgeting, and and random body motion, would cause large fluctuations in the baseband signals and significantly random body motion, would cause large fluctuations in the baseband signals and significantly lower lower the detection accuracy. However, compared to the vital signs, these interference signals are the detection accuracy. However, compared to the vital signs, these interference signals are temporary temporary and aperiodic, thus the joint time-frequency analysis can be utilized to establish a and aperiodic, thus the joint time-frequency analysis can be utilized to establish a reliable spectrogram reliable spectrogram for long-term monitoring of the target signal with a wide range of physical for long-term monitoring of the target signal with a wide range of physical activities [28]. Notably, activities [28]. Notably, since the modulation bandwidth of the active antenna worn on a moving since the modulation bandwidth of the active antenna worn on a moving subject’s wrist is generally subject’s wrist is generally less than 7 MHz, this remote frequency discriminator with less than 7 MHz, this remote frequency discriminator with gain-enhanced LNA could support up gain-enhanced LNA could support up to 14 active antennas to concurrently detect vital signs of 14 to 14 active antennas to concurrently detect vital signs of 14 users by simply switching the carrier users by simply switching the carrier frequency of the ILO. Moreover, the built-in battery can frequency of the ILO. Moreover, the built-in battery can provide up to four days of antenna active provide up to four days of antenna active time, and the battery will even last longer if utilizing a time, and the battery will even last longer if utilizing a pulse-width modulation (PWM) power-supply pulse-width modulation (PWM) power-supply controller, a future development possibility worth controller, a future looking forward to.development possibility worth looking forward to. 5. Conclusions 5. Conclusions This study uses bistatic SIL radar technology to monitor the pulse rate of a subject who wears This study uses bistatic SIL radar technology to monitor the pulse rate of a subject who wears an active antenna wristband. The radial artery pulse on the wrist causes the active antenna to output an active antenna wristband. The radial artery pulse on the wrist causes the active antenna to FM signals. After being demodulated by an ILO-based frequency discriminator at a remote location, output FM signals. After being demodulated by an ILO-based frequency discriminator at a remote the pulse rate information of the subject is obtained accurately. Based on the technology described location, the pulse rate information of the subject is obtained accurately. Based on the technology in this study, the proposed bistatic SIL radar architecture can effectively reduce the size and power described in this study, the proposed bistatic SIL radar architecture can effectively reduce the size consumption of wearable devices for vital sign detection. Future research will focus on using flexible and power consumption of wearable devices for vital sign detection. Future research will focus on electronics to produce more comfortable wearable radars suitable for long-term monitoring for vital using flexible electronics to produce more comfortable wearable radars suitable for long-term signs and exercise tracking. monitoring for vital signs and exercise tracking. Acknowledgments: This work was supported in part by the Ministry of Science and Technology, Taiwan, under Grants MOST 103-2221-E-110-013-MY3, MOST 105-2221-E-110-016-MY3, and MOST 105-2218-E-110-007, and by the National Sun Yat-sen University, Taiwan, under Grant #NSYSUNPUST 105-004. Author Contributions: Fu-Kang Wang designed the experiments and wrote the paper; Sheng-Chao Su performed the experiments; Mu-Cyun Tang analyzed the data; Tzyy-Sheng Horng contributed the necessary materials/components/instruments, and gave critical suggestions for the paper structure.

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Acknowledgments: This work was supported in part by the Ministry of Science and Technology, Taiwan, under Grants MOST 103-2221-E-110-013-MY3, MOST 105-2221-E-110-016-MY3, and MOST 105-2218-E-110-007, and by the National Sun Yat-sen University, Taiwan, under Grant #NSYSUNPUST 105-004. Author Contributions: Fu-Kang Wang designed the experiments and wrote the paper; Sheng-Chao Su performed the experiments; Mu-Cyun Tang analyzed the data; Tzyy-Sheng Horng contributed the necessary materials/components/instruments, and gave critical suggestions for the paper structure. Conflicts of Interest: The authors declare no conflict of interest.

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