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Design and experiment of an optical fiber micro bend sensor for respiration monitoring
Sensors and Actuators A 251 (2016) 126–133
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Sensors and Actuators A: Physical journal homepage: www.elsevier.com/locate/sna
Design and experiment of an optical fiber micro bend sensor for respiration monitoring Hai-feng Hu a , Si-jia Sun a , Ri-qing Lv a , Yong Zhao a,b,∗ a b
College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, 110819, China
a r t i c l e
i n f o
Article history: Received 15 May 2016 Received in revised form 10 October 2016 Accepted 10 October 2016 Available online 12 October 2016 Keywords: Optical fiber micro bend sensor Transmission loss of multimode fiber Respiration monitoring Seat-back type sensor
a b s t r a c t A new fiber optic micro bend sensor has been proposed in this paper for respiration monitoring. The detected respiration rate was verified by counting the breathing manually. Therefore the purpose of this paper is to find the appropriate gear numbers and cycles of the optical fiber micro bend modulator in order to enhance the accuracy of the measurement result. The relevant improvement measures will be applied to the medical field in the future. The number of the fiber optic micro bend sensor’s teeth has been determined by the simulation results and based on which the micro bend modulator tooth structure were designed. The size of the tooth is 6 mm, and the number of teeth is 15. This structure is a kind of seat-back type fiber optic micro bend sensor. This sensors can be used to measure vital signs because it possess several advantages, such as real-time and accuracy, low cost and convenient operation. © 2016 Elsevier B.V. All rights reserved.
1. Introduction With the development of scientific research and the continuous improvement of people’s living standard and with the increase of the accuracy of medical diagnosis, people’s pursuit for health is also increasing. Breathing rate is an important physiological parameter of human body. It’s the great important to detect the parameter conveniently and accurately. However, the respiratory monitoring methods have some defects and it should be improved, even if some other methods can realize accurate measurement, but its structure is very large. Various types of fiber-optic bending sensors have been developed, including long period fiber gratings [1–3], tilted fiber Bragg gratings (FBGs) [4,5], gratings written in specific fibers [6–9], and a variety of inline interferometers [10–13]. These configurations have their own advantages and can realize accurate bending measurements. In recent years, a novel fiber Bragg grating (FBG) structure based on an eccentric core fiber (ECF) and a single-mode fiber (SMF) was proposed and experimentally demonstrated for distinguishing the bending effect from the axial strain effect and measuring the pure directional bending. The structure is fabricated
∗ Corresponding author at: College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China. E-mail addresses: [email protected] (H.-f. Hu), m13804045032 [email protected] (S.-j. Sun), [email protected] (R.-q. Lv), [email protected] (Y. Zhao). http://dx.doi.org/10.1016/j.sna.2016.10.013 0924-4247/© 2016 Elsevier B.V. All rights reserved.
by writing a FBG on the fusion splice junction between an ECF and a SMF. Experimental results show that the bending sensitivities of the FBG in the ECF part are 49.3 and −50.3 pm/m (−1) [14]. In addition, some curvature measurement experiments have been carried out [15]. A highly sensitive bend and temperature sensor has been proposed employing a micro cavity incorporated solid core PCF (SCPCF) concatenated with tapered single mode fiber (SMF) based on intensity interrogation [16]. A maximum curvature sensitivity of 10.4 dB/m−1 is observed in the curvature range 0–1 m−1 for a second taper diameter of 18 m. The sensing setup is highly stable and shows very low temperature sensitivity [17,18]. In this study, the fiber optic micro bend loss modulator has been designed and analyzed the effect of multimode optical fiber bending loss. The studies have shown that with the decrease of the small bending radius, the bending loss increases sharply. Then, the multimode optical fiber was placed into the optical fiber micro bend modulator, and it is time to measure the light power. The different weights were put onto the fiber optic micro bend modulator in order to simulate the different intensity of respiration. At last, the structure has been improved in order to realize the respiration monitoring. This article is based on the principle of fiber optic micro bend, the fiber optic modulator has been proposed for realtime monitoring of respiration intensity. The noise of the signal is to use the software filtering, and a friendly man-machine interface has achieved satisfactory properties. In 1980, in Applied Fields Jacqueline Nottingham and Cole, J.H published an article entitled “fiber optic micro bend acoustic sen-
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127
Fig. 1. Sketch map of fiber optic micro bend sensor.
sors”, this paper introduces the structure and characteristics of fiber optic micro bend hydrophone. This is the first report about fiber optic micro bend sensor (here after FOMBS). In recent years, fiber Bragg grating sensors were used to monitor the cardiac activity and respiration, but they are still have limitations owing to the cost and complication [15–18]. Several research groups reported vital signs monitoring based on fiber interferometry method for heartbeat and respiration monitoring [19–22]. In 2004, W. B. Spillman, Jr. et al. [23,24] distributed integrating multimode fiber optic sensors and developed a smart bed for non-intrusively monitoring patient respiration, heart rate and movement. The micro bend fiber optic sensors developed by the group for the measurement of vital signs were studied and were embedded in pillows/cushions or on bed, because of its simplicity and low cost. It can measure the breathing rate, heart rate, and body movement simultaneously and non-invasively. It is suitable for long term continuous monitoring without the limit to the user’s activity and the need for skin contact. In 2009, Z. H. Chen et al. [25–27] have previously presented works on a micro bend optical fiber sensor for vital signs. In January 2014, J. Wo.et al. [28] reported a non-invasive respiration sensor based on fiber laser in the J. of Biomedical Optics, but the fiber laser sensor only monitored heartbeat and the sensor system was too complicated and expensive. In 2015, Chen Z et al. [29] have to study the “Textile Fiber Optic Microbend Sensor Used for Heartbeat and Respiration Monitoring”. The sensing textile is relatively simple, cost-effective, wearing more comfortable, because the sensing textiles can be placed in the chest. This paper mainly applied the principle of fiber optic micro bend in respiratory monitoring system. Lau D et al. found that the distance between the two teeth of fiber optic micro bend modulator has obvious influence on light power losses, and the number of tooth
Fig. 2. Structure diagram of micro bend modulator.
about fiber optic micro bend modulator has big influence on the optical power loss. This paper presents the design of a denticulate laminas sensing scheme. Micro bend optical fiber sensors have been explored for physical and chemical detection of parameters such as pressure, strain, displacement, vibration, temperature, humidity, pH, etc., with good sensitivity [16–18]. Similar to other successful healthcare sensors, our micro bend sensor technology has been commercialized for home-based healthcare sensing. However, to our knowledge, no publication has reported the use of micro bend optical fiber sensor for respiratory monitoring. 2. Principle and structure of the optical fiber micro bend respiration sensor The FOMBS consists of light source, micro bending modulator, fiber-optical and photo- detector. The He-Ne laser, laser diode and light-emitting diode are usually used in the experiment. At present, the micro bending modulator structure which has been used of saw tooth, waviness, spiral, elastic cylinder or cylindrical shape, frame-tape, hand posture and other types.
Fig. 3. Design of the zigzag shape of the micro bending modulator and the optical fiber bending.
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Bending easily is one of the most important advantages of optical fiber. Now the saw tooth takes as an example and the principle of FOMBS should be analyzed. Considering the saw tooth of FOMBS, micro bend modulator is composed of two denticulate laminas that the mechanical cycles are . Sensitive fiber passes from the middle of the denticulate laminas and will bend due to the effect of saw tooth. If the denticulate laminas suffer external disturbance, the bending degree of sensitive optical fiber will be changed correspondingly, causing the energy of core mode leaks into the cladding, which will lead to the change of the output power. Therefore it can be measured the degree of the disturbance by recording the output power. Under normal circumstances, beta, the constant coefficient of the optical fiber in the optical fiber should satisfy this formula: n2k0 < ˇ < n1k0(n1, n2 are the refractive index of fiber core and cladding, k0 = 2/ is the number of waves in a vacuum condition). FOMBS is a typical intensity modulation fiber optic sensor which uses fiber optic micro bend loss effect to detect the changes of the external physical quantities. The sensor sketch map and the structure diagram of micro bend modulator are respectively shown in Figs. 1 and 2. Micro bend modulator (E.T. micro bending deformation) is composed of two denticulate laminas that mechanical cycles are . Its principle has been introduced in the above paragraph. This saw tooth type micro bend modulator is composed of two upper and below lamina denticulate. The upper lamina denticulate is a cube that the thickness, length and width are respectively 8 mm, 260 mm and 210 mm. The middle part of the lamina has 15 teeth and around each there is a cylinder. The size of the below lamina is the same as the upper one’s. And the only difference is that the middle part of the below has 14 teeth. But it is worth noting that the upper and below lamina denticulate should match each other well. The optical fiber clamping is in the middle of the lamina. The upper lamina denticulate produces a displacement by outside disturbance and it will make the optical fiber periodically bend. And the bending degree of optical fiber will be changed correspondingly with the outside disturbance. Then the change of the parameter can be detected by the change of light power loss. The steps below were taken when the micro bend modulator come into use. First of all, the fiber was penetrated on both sides of the fiber spacing hole of the lamina denticulate. Then the spring was loaded well. At last, the last four limit column was fitted with screws in order to make the saw tooth away from the optical fiber, but they must be kept in an appropriate distance. Input the light source to the optical fiber after completing the above actions. Now the working principle of fiber is briefly described as follows. A corresponding displacement will be produced by the upper lamina denticulate when the force of breath has been acted on the upper lamina denticulate. And a micro bending loss will be produced by the optical fiber. The upper lamina denticulate will back to original position by the elastic force of the spring with the force disappearances. Therefore the times of generating optical loss can be detected in one minute to monitor the frequency of breath.
3. The parameter design of the micro bending modulator The tooth shape was designed according to the normal tooth shape design of the reference GB192-1981. At last, the basic outline of an equilateral triangle was given after considering other influence factors. And a certain arc chamfer on the cusp was designed in order to prevent the fiber from being broken. The specific design is shown in Fig. 3. The height of the triangle is deduced as follows. The assumption of the height of the micro bending modulator and triangle ABC are respectively H and h. The tooth pitch is . The triangular tooth on both sides of the tangent to the arc curvature radius is R. The
following equation can be obtained according to the geometrical relationship. AO h = H /2
(1)
ABO’ AOO’, so, AO h
R = AB
=
AB =
/2 = H
h=
R
AO 2 + h2
(3)
R
AO 2
+ h2
=
R 2 ( ·h ) 2H
= + h2
2HR
h
R 1+
(4) 2 4H 2
(5)
1+
2 4H 2
H=
√ 3 , 2
so
h=
(2)
AO 2 + h2
3 R 2
(6)
In order to get the curve equation, the displacement is set to X, that is, the micro bending modulator moves down the distance is X. According to the actual bending of the fiber, it assumed that the trajectory of the bending fiber as the cosine, and the equation of the bending part was f(x).
⎧ X 2 ⎪ ⎪ ⎨ f (x) = 2 cos( t)t ∈ [0, N]
(7)
3/2 2 ⎪ ⎪ ⎩ R = (1 + f (x))
|f (x)|
In the formula, N, R and are respectively micro bending cycles, bending radius and bending cycle. The micro bending period number N has great influence on the micro bending loss. If the times of micro bending cycle are more, when the T (T = 6) is constant, the slope of the curve is larger, and the sensor is more sensitive. Therefore, it should increase the number of the teeth as far as possible while the size of the sensor is available. The relationship can be obtained between displacement and micro bend loss through the relationship between the micro bending loss of multimode fiber and the bending radius and the relationship between the displacement and the bending radius of the micro bending modulator. The loss of the micro bending modulator is:
t=N
Loss = −10
−2˛ ·
1 + f 2 (x)dt
(8)
t=0
According to the micro bending modulator, the bending loss is affected only by the bending period, so that the effects of different bending period number and bending period on the bending loss need analyze. The Fig. 4 shows the influence of the micro bending cycle numbers on the loss. When the bending period is constant, the bending loss and sensitivity increases with the increase of the bending cycle numbers. The Fig. 5 shows the influence of the micro bending period on the loss of the curve. From the graph, the conclusion is consistent with the above equality. According to the simulation results are showed, the micro bending period is 6 mm and the micro bending cycles is 15. Due to the limitation of craftsmanship the sensor is fabricated as the following specification, the length of the side of sawtooth is 6 mm, the number of sawtooth is 15. The experiment has been carried out applying this sensor.
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T=6 35 30
Loss (dB)
25 20 15 10 5 0 0.4
0.6
0.8 1 1.2 Displacement (mm)
1.4
N=6 N=8 N=10 N=12 N=15 N=20 1.6
Fig. 4. Influence of the number of micro bending cycles on the loss. N=15
Fig. 6. Fitting curve of pressure and output power.
35 30
Loss (dB)
25 20 15 10 5 0 0.5
1
1.5
2 2.5 3 Di spl acement (mm)
3.5
4
t=4 t=5 t=6 t=7 t=8 4.5
Fig. 5. Influence of the micro bending period on the loss of the curve.
4. Experimental result analysis 4.1. the pressure of micro bend modulator and output power measurement experiment In order to detect the feasibility of micro bend modulator device, the simple experiment has been carried on. The fiber was linked to the 1550 nm DFB light source, and the other end was linked with a handheld power meter. The weights (each weight about 1 kg) were added onto the micro bend modulator, as shown in Fig. 1, in order to increase the pressure acted on the micro bend modulator. It should be placed it gently, and tried to locate it in the center of the micro bend modulator, it could make spring stable as much as possible. With the purpose of reducing the jitter of generating error, the denticulate laminas should be made parallel moving at the same time. The forward and backward experiments had been verified for many times, and the result about the four groups of fitting curve has been shown in Fig. 6. It can be seen that the output power decreases with the increase of pressure, the same group of the forward and backward experiment coincide well, but the repeatability between multiple groups need to be improved. The reason is that spring is not installed on the limit column which lead to increase or decrease weight. When the denticulate laminas moves, the limit column here will generate the friction, and the force area of weight is small. The repeatability problem is appeared in the verification experiment, we use weights for simulating the pressure of back. Because the contact area of the weight is not large enough, we can’t make sure putting the weights at the exactly same position every time, it may cause tooth plate moving deviation. When the people sit on the chair and do the experiment, the contact area can cover the
sensor, so the influence of friction is decreased, the idea waveform figure could be present, and the repeatability problems are well improved. It can largely reduce the limit column of the friction. When the toothed plate was leant on the back to breathe that can increase the reaction area.The sensor link the photoelectric conversion module and the breathing waveform display on the oscilloscope. In addition to this, it can be seen that when people breathe, the waveform changes obviously. Due to the fact that oscilloscope cannot export the real-time waveform; the next step is to improve the experimental structure. The photoelectric detection and the acquisition circuit module have been applied into the experiment; with the extract the output waveform to computer, the data and the real-time drawing have been analyzed by using LabView. 4.2. Experimental research and data analysis In order to display the real-time waveform on screen, the LabView serial port communication and the data acquisition function are used to do the experiment (Fig. 7). On the base of the experiment platform, this paper has measured the different testers under the different conditions of breathing measurements. It is a good way to use the FFT to calculate the value and get the frequency spectrum distribution curve. According to the frequency distribution, the appropriate filter frequency is set in the figure. FFT is the fast Fourier transform. It is the fast algorithm of discrete Fourier transform, and it is based on discrete Fourier transform (odd, even, imaginary, real), in this way, the discrete Fourier transform algorithm is used to improve the analyzed waves. The following is analysis of data about tester 1 s respiratory signal. As you can see from Fig. 8(a), the respiratory signal gathered had abundant noise, and the respiratory waveform can be easily distinguished. The value of two waveform valley show the frequency is 0.345 Hz, Some information also can get from the spectrum that the frequency of 0.364 Hz signal and the respiratory signal frequency is almost coincident. With the extracted waveform from figure Fig. 8(c) and Fig. 8(d), the 0.0364 Hz waveform and the respiratory waveform gathered are more coincident. Therefore, the waveform signal frequency of 0.364 Hz is useful signal, and it should be retained. The frequency of 0.044 Hz signal is the noise signal, and the further analysis should be carried on. The high-pass filter is a good choice to remove noise. In addition, there are many smaller amplitude frequency components, the low-pass filter can remove
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Fig. 7. Test structural drawing of fiber optic micro bend respiratory sensor system.
it. In general, in order to get good breathing waveform the band pass filter should be used. For furthering validate the analysis, the next task is carrying on the different testers and different respiratory signal acquisition. The Three testers in two different conditions of respiratory waveform as shown in Fig. 9, from the experimental data it can draw a conclusion. The sampling time of experiments is 60s, the Fourier transform of the sampling frequency is 20 Hz, every 20 points for a breath. The peak amplitude of experiments is the respiration signal, for the rest of the signal is noise. According to the figures above, the results can be determined: the breathing rate frequency is between 0.18 Hz and 0.5 Hz. Furthermore, the data collected have the low frequency noise signal obviously. Some small amplitude of high frequency signal is mixed in it as well. In order to get a better waveform of the breathing rate, the noise signal should be removed. In amplitude, from the order of high to low are deep breath, normal breath and rapid breath. It matches the real behaviors condition. The differences of respiratory waveform is relatively obvious, the frequency of fast respire- troy waveform is faster than the frequency of normal respiratory waveform, low amplitude, which proved that the micro bend modulator structure designed can distinguish normal respiratory waveform and fast respiratory waveform. In the following, it is considered about the data characteristics by different situations. First of all, the optical fiber used in the experiment is not sensitive with the temperature. In addition, the temperature signal is slowly changed signal, so the Fourier transform could filter the temperature signal. In that reason, the results won’t be changed a lot under different temperature condi-
Fig. 8. Spectrum of tester 1 s respiratory signal.
tions. Because of the advantage of the fiber optical,this device can resistance to electromagnetic interference. In this paper, the designed filter has the unit impulse response, it retains damped oscillation which lasts about 20s. If the signal was analyzed may cause certain influence at this time, It is not necessary to analyze respiratory data in this 20s. After this 20s, it begins to record the data. The analytical method of the signal is the Fourier transform, the useful respiratory frequency signal could be separated by this
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Fig. 10. The device of standard error bar.
Fig. 11. The device of stability curve.
Fig. 9. Spectrum of 3 testers’ respiratory signal.
way. The respiratory signal frequency range from 0.18 to 0.5 Hz, the band-pass filter can filter the signal. The Fourier transform have no influence on the wave of direct component. It needs to be satisfied in the time domain what the frequency domain requires. The shifting of the direct component and the dynamics changing have no influence on the measurement as well. The stability of the proposed sensor is relatively good. In general, the breathing rate for people is around 16–20 times per minute, the volunteer took the breathing experiments many times. The result of the breathing rate was counted by manual and sensor. The 18 times per minute the manual counted was chosen as the standard of the breathing rate. The 50 groups of data was been collected from the breathing experiments. It has been compared with the sensor counting. According to the experimental result, it can be seen that there are 3 groups of data differ from the manual counting. The stability curve of the sensor is demonstrated. In addition, the error bar is showed as follows (Figs. 10 and 11). 5. Conclusion The design of lamina denticulate scheme was proposed on this paper and analyzed the experiment principle. The optical fiber
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micro bend mechanism is used in the experiment. When the different powers act on the optical fiber, the optical axis will produce a series of irregular tiny crook which can result in the loss of the power. Therefore it can be detected the respiratory rate by the change of the power loss. The principle is simple summarized that FOMBS monitors the optical fiber’s change by the external factor’s influence which can cause the transmission light intensity changes of optical fiber. It can be conducted the following experiment. Based on this study, in the first place, the influence of FOMBS’s number of teeth on optical power have realized by the principle of FOMBS technology. Then an elaborate plan and a simulation were designed, which aim to study the effect of the sensor. At last, the number of teeth of the fiber optic micro bend modulator has been determined by the simulation and the data analysis. Finally, it concluded that the improvement measure can improve the real-time performance by the experimental verification. Since the optical fiber micro bend is proposed in recent years, so this paper just has a superficial insight and it is hoped that it can provide solid information and vision for future study. Acknowledgments This work was supported in part by the National Natural Science Foundation of China under Grant 61425003 and 61403074, the Fundamental Research Funds for the Central Universities under Grant N150401001 and N140404023, the China Post-Doctoral Science Foundation Project under Grant 2014M560219, and in part by the State Key Laboratory of Synthetical Automation for Process Industries under Grant 2013ZCX09.
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Hai-feng Hu was born in Liaoning, China, in 1984. He received his Ph.D degrees in the Institute of Semiconductors, Chinese Academy of Sciences, China, in 2013. He is currently working in the College of Information and Engineering at Northeastern University. His research interests are nano-optics, plasmonics, fiber-optic sensors and their applications in biosensing. He has authored and co-authored more than 20 scientific papers, 2 patents and 5 conference presentations.
Si-jia Sun was born in Liaoning, China, in Feb. 1993. She received her B.A. degrees in the College of Information Science and Engineering from the Shenyang University of Technology, China, in 2015. She is now a graduate student of Northeastern University. Her research interests are fiber optical sensors, fiber Bragg grating sensors, regenerated fiber Bragg grating sensors.
Ri-qing Lv was born in Guangdong, China, in 1985. He received his B.S, M.A. and Ph.D. degrees, respectively, in biomedical engineering, circuit and system, detection technology and automatic equipment from Northeastern University, Shenyang, China, in 2008, 2010 and 2014. He is currently working in the College of Information Science and Engineering at Northeastern University as a postdoctor. His research interests are magnetic fluid and fiber-optic sensors. He has authored and co-authored about 30 scientific papers, patents and conference presentations.
H.-f. Hu et al. / Sensors and Actuators A 251 (2016) 126–133
Yong Zhao received his M.A. and Ph.D. degrees, respectively, in precision instrument & automatic measurement with laser and fiber-optic techniques from the Harbin Institute of Technology, China, in 1998 and 2001. He was awarded a first prize scholarship in 2000 by the China Instrument and Control Society and the Sintered Metal Corporation (SMC) scholarship in Japan. He was a scholarship in Japan. He was a postdoctoral fellow in the Department of Electronic Engineering of Tsinghua University from 2001 to 2003, and then worked as an associate professor in the Department of Automation, Tsinghua University of China. In 2006, he was a visiting scholar of University of Illinois in Urbana and Champagne, USA. In 2008, he was awarded as the “New Century Excellent Talents in University” by the Ministry of Education of China. In 2009, he was awarded as the “Liaoning Bai-QianWan Talents” by Liaoning Province. In 2011, he was awarded by the Royal Academy
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of Engineering as an academic research fellow of City University London. In 2014, he was awarded by the National Science Foundation for Distinguished Young Scholars of China. In 2015, he was honored as the Yangtze River Scholar Distinguished Professor by the Ministry of Education of China. Now he is working in Northeastern University as a full professor. As the academic leader and director of his research institute, his current research interests are the development of fiber-optic sensors and device, fiber Bragg grating sensors, novel sensor materials and principles, slow light and sensor technology, optical measurement technologies. He has authored and co-authored more than 200 scientific papers and conference presentations, 19 patents, and 5 books. He is a member in the Editorial Boards of the international journals of Sensor Letters, Instrumentation Science & Technology, Journal of Sensor Technology, and Advances in Optical Technologies.
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Sensors and Actuators A: Physical journal homepage: www.elsevier.com/locate/sna
Design and experiment of an optical fiber micro bend sensor for respiration monitoring Hai-feng Hu a , Si-jia Sun a , Ri-qing Lv a , Yong Zhao a,b,∗ a b
College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, 110819, China
a r t i c l e
i n f o
Article history: Received 15 May 2016 Received in revised form 10 October 2016 Accepted 10 October 2016 Available online 12 October 2016 Keywords: Optical fiber micro bend sensor Transmission loss of multimode fiber Respiration monitoring Seat-back type sensor
a b s t r a c t A new fiber optic micro bend sensor has been proposed in this paper for respiration monitoring. The detected respiration rate was verified by counting the breathing manually. Therefore the purpose of this paper is to find the appropriate gear numbers and cycles of the optical fiber micro bend modulator in order to enhance the accuracy of the measurement result. The relevant improvement measures will be applied to the medical field in the future. The number of the fiber optic micro bend sensor’s teeth has been determined by the simulation results and based on which the micro bend modulator tooth structure were designed. The size of the tooth is 6 mm, and the number of teeth is 15. This structure is a kind of seat-back type fiber optic micro bend sensor. This sensors can be used to measure vital signs because it possess several advantages, such as real-time and accuracy, low cost and convenient operation. © 2016 Elsevier B.V. All rights reserved.
1. Introduction With the development of scientific research and the continuous improvement of people’s living standard and with the increase of the accuracy of medical diagnosis, people’s pursuit for health is also increasing. Breathing rate is an important physiological parameter of human body. It’s the great important to detect the parameter conveniently and accurately. However, the respiratory monitoring methods have some defects and it should be improved, even if some other methods can realize accurate measurement, but its structure is very large. Various types of fiber-optic bending sensors have been developed, including long period fiber gratings [1–3], tilted fiber Bragg gratings (FBGs) [4,5], gratings written in specific fibers [6–9], and a variety of inline interferometers [10–13]. These configurations have their own advantages and can realize accurate bending measurements. In recent years, a novel fiber Bragg grating (FBG) structure based on an eccentric core fiber (ECF) and a single-mode fiber (SMF) was proposed and experimentally demonstrated for distinguishing the bending effect from the axial strain effect and measuring the pure directional bending. The structure is fabricated
∗ Corresponding author at: College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China. E-mail addresses: [email protected] (H.-f. Hu), m13804045032 [email protected] (S.-j. Sun), [email protected] (R.-q. Lv), [email protected] (Y. Zhao). http://dx.doi.org/10.1016/j.sna.2016.10.013 0924-4247/© 2016 Elsevier B.V. All rights reserved.
by writing a FBG on the fusion splice junction between an ECF and a SMF. Experimental results show that the bending sensitivities of the FBG in the ECF part are 49.3 and −50.3 pm/m (−1) [14]. In addition, some curvature measurement experiments have been carried out [15]. A highly sensitive bend and temperature sensor has been proposed employing a micro cavity incorporated solid core PCF (SCPCF) concatenated with tapered single mode fiber (SMF) based on intensity interrogation [16]. A maximum curvature sensitivity of 10.4 dB/m−1 is observed in the curvature range 0–1 m−1 for a second taper diameter of 18 m. The sensing setup is highly stable and shows very low temperature sensitivity [17,18]. In this study, the fiber optic micro bend loss modulator has been designed and analyzed the effect of multimode optical fiber bending loss. The studies have shown that with the decrease of the small bending radius, the bending loss increases sharply. Then, the multimode optical fiber was placed into the optical fiber micro bend modulator, and it is time to measure the light power. The different weights were put onto the fiber optic micro bend modulator in order to simulate the different intensity of respiration. At last, the structure has been improved in order to realize the respiration monitoring. This article is based on the principle of fiber optic micro bend, the fiber optic modulator has been proposed for realtime monitoring of respiration intensity. The noise of the signal is to use the software filtering, and a friendly man-machine interface has achieved satisfactory properties. In 1980, in Applied Fields Jacqueline Nottingham and Cole, J.H published an article entitled “fiber optic micro bend acoustic sen-
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127
Fig. 1. Sketch map of fiber optic micro bend sensor.
sors”, this paper introduces the structure and characteristics of fiber optic micro bend hydrophone. This is the first report about fiber optic micro bend sensor (here after FOMBS). In recent years, fiber Bragg grating sensors were used to monitor the cardiac activity and respiration, but they are still have limitations owing to the cost and complication [15–18]. Several research groups reported vital signs monitoring based on fiber interferometry method for heartbeat and respiration monitoring [19–22]. In 2004, W. B. Spillman, Jr. et al. [23,24] distributed integrating multimode fiber optic sensors and developed a smart bed for non-intrusively monitoring patient respiration, heart rate and movement. The micro bend fiber optic sensors developed by the group for the measurement of vital signs were studied and were embedded in pillows/cushions or on bed, because of its simplicity and low cost. It can measure the breathing rate, heart rate, and body movement simultaneously and non-invasively. It is suitable for long term continuous monitoring without the limit to the user’s activity and the need for skin contact. In 2009, Z. H. Chen et al. [25–27] have previously presented works on a micro bend optical fiber sensor for vital signs. In January 2014, J. Wo.et al. [28] reported a non-invasive respiration sensor based on fiber laser in the J. of Biomedical Optics, but the fiber laser sensor only monitored heartbeat and the sensor system was too complicated and expensive. In 2015, Chen Z et al. [29] have to study the “Textile Fiber Optic Microbend Sensor Used for Heartbeat and Respiration Monitoring”. The sensing textile is relatively simple, cost-effective, wearing more comfortable, because the sensing textiles can be placed in the chest. This paper mainly applied the principle of fiber optic micro bend in respiratory monitoring system. Lau D et al. found that the distance between the two teeth of fiber optic micro bend modulator has obvious influence on light power losses, and the number of tooth
Fig. 2. Structure diagram of micro bend modulator.
about fiber optic micro bend modulator has big influence on the optical power loss. This paper presents the design of a denticulate laminas sensing scheme. Micro bend optical fiber sensors have been explored for physical and chemical detection of parameters such as pressure, strain, displacement, vibration, temperature, humidity, pH, etc., with good sensitivity [16–18]. Similar to other successful healthcare sensors, our micro bend sensor technology has been commercialized for home-based healthcare sensing. However, to our knowledge, no publication has reported the use of micro bend optical fiber sensor for respiratory monitoring. 2. Principle and structure of the optical fiber micro bend respiration sensor The FOMBS consists of light source, micro bending modulator, fiber-optical and photo- detector. The He-Ne laser, laser diode and light-emitting diode are usually used in the experiment. At present, the micro bending modulator structure which has been used of saw tooth, waviness, spiral, elastic cylinder or cylindrical shape, frame-tape, hand posture and other types.
Fig. 3. Design of the zigzag shape of the micro bending modulator and the optical fiber bending.
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Bending easily is one of the most important advantages of optical fiber. Now the saw tooth takes as an example and the principle of FOMBS should be analyzed. Considering the saw tooth of FOMBS, micro bend modulator is composed of two denticulate laminas that the mechanical cycles are . Sensitive fiber passes from the middle of the denticulate laminas and will bend due to the effect of saw tooth. If the denticulate laminas suffer external disturbance, the bending degree of sensitive optical fiber will be changed correspondingly, causing the energy of core mode leaks into the cladding, which will lead to the change of the output power. Therefore it can be measured the degree of the disturbance by recording the output power. Under normal circumstances, beta, the constant coefficient of the optical fiber in the optical fiber should satisfy this formula: n2k0 < ˇ < n1k0(n1, n2 are the refractive index of fiber core and cladding, k0 = 2/ is the number of waves in a vacuum condition). FOMBS is a typical intensity modulation fiber optic sensor which uses fiber optic micro bend loss effect to detect the changes of the external physical quantities. The sensor sketch map and the structure diagram of micro bend modulator are respectively shown in Figs. 1 and 2. Micro bend modulator (E.T. micro bending deformation) is composed of two denticulate laminas that mechanical cycles are . Its principle has been introduced in the above paragraph. This saw tooth type micro bend modulator is composed of two upper and below lamina denticulate. The upper lamina denticulate is a cube that the thickness, length and width are respectively 8 mm, 260 mm and 210 mm. The middle part of the lamina has 15 teeth and around each there is a cylinder. The size of the below lamina is the same as the upper one’s. And the only difference is that the middle part of the below has 14 teeth. But it is worth noting that the upper and below lamina denticulate should match each other well. The optical fiber clamping is in the middle of the lamina. The upper lamina denticulate produces a displacement by outside disturbance and it will make the optical fiber periodically bend. And the bending degree of optical fiber will be changed correspondingly with the outside disturbance. Then the change of the parameter can be detected by the change of light power loss. The steps below were taken when the micro bend modulator come into use. First of all, the fiber was penetrated on both sides of the fiber spacing hole of the lamina denticulate. Then the spring was loaded well. At last, the last four limit column was fitted with screws in order to make the saw tooth away from the optical fiber, but they must be kept in an appropriate distance. Input the light source to the optical fiber after completing the above actions. Now the working principle of fiber is briefly described as follows. A corresponding displacement will be produced by the upper lamina denticulate when the force of breath has been acted on the upper lamina denticulate. And a micro bending loss will be produced by the optical fiber. The upper lamina denticulate will back to original position by the elastic force of the spring with the force disappearances. Therefore the times of generating optical loss can be detected in one minute to monitor the frequency of breath.
3. The parameter design of the micro bending modulator The tooth shape was designed according to the normal tooth shape design of the reference GB192-1981. At last, the basic outline of an equilateral triangle was given after considering other influence factors. And a certain arc chamfer on the cusp was designed in order to prevent the fiber from being broken. The specific design is shown in Fig. 3. The height of the triangle is deduced as follows. The assumption of the height of the micro bending modulator and triangle ABC are respectively H and h. The tooth pitch is . The triangular tooth on both sides of the tangent to the arc curvature radius is R. The
following equation can be obtained according to the geometrical relationship. AO h = H /2
(1)
ABO’ AOO’, so, AO h
R = AB
=
AB =
/2 = H
h=
R
AO 2 + h2
(3)
R
AO 2
+ h2
=
R 2 ( ·h ) 2H
= + h2
2HR
h
R 1+
(4) 2 4H 2
(5)
1+
2 4H 2
H=
√ 3 , 2
so
h=
(2)
AO 2 + h2
3 R 2
(6)
In order to get the curve equation, the displacement is set to X, that is, the micro bending modulator moves down the distance is X. According to the actual bending of the fiber, it assumed that the trajectory of the bending fiber as the cosine, and the equation of the bending part was f(x).
⎧ X 2 ⎪ ⎪ ⎨ f (x) = 2 cos( t)t ∈ [0, N]
(7)
3/2 2 ⎪ ⎪ ⎩ R = (1 + f (x))
|f (x)|
In the formula, N, R and are respectively micro bending cycles, bending radius and bending cycle. The micro bending period number N has great influence on the micro bending loss. If the times of micro bending cycle are more, when the T (T = 6) is constant, the slope of the curve is larger, and the sensor is more sensitive. Therefore, it should increase the number of the teeth as far as possible while the size of the sensor is available. The relationship can be obtained between displacement and micro bend loss through the relationship between the micro bending loss of multimode fiber and the bending radius and the relationship between the displacement and the bending radius of the micro bending modulator. The loss of the micro bending modulator is:
t=N
Loss = −10
−2˛ ·
1 + f 2 (x)dt
(8)
t=0
According to the micro bending modulator, the bending loss is affected only by the bending period, so that the effects of different bending period number and bending period on the bending loss need analyze. The Fig. 4 shows the influence of the micro bending cycle numbers on the loss. When the bending period is constant, the bending loss and sensitivity increases with the increase of the bending cycle numbers. The Fig. 5 shows the influence of the micro bending period on the loss of the curve. From the graph, the conclusion is consistent with the above equality. According to the simulation results are showed, the micro bending period is 6 mm and the micro bending cycles is 15. Due to the limitation of craftsmanship the sensor is fabricated as the following specification, the length of the side of sawtooth is 6 mm, the number of sawtooth is 15. The experiment has been carried out applying this sensor.
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T=6 35 30
Loss (dB)
25 20 15 10 5 0 0.4
0.6
0.8 1 1.2 Displacement (mm)
1.4
N=6 N=8 N=10 N=12 N=15 N=20 1.6
Fig. 4. Influence of the number of micro bending cycles on the loss. N=15
Fig. 6. Fitting curve of pressure and output power.
35 30
Loss (dB)
25 20 15 10 5 0 0.5
1
1.5
2 2.5 3 Di spl acement (mm)
3.5
4
t=4 t=5 t=6 t=7 t=8 4.5
Fig. 5. Influence of the micro bending period on the loss of the curve.
4. Experimental result analysis 4.1. the pressure of micro bend modulator and output power measurement experiment In order to detect the feasibility of micro bend modulator device, the simple experiment has been carried on. The fiber was linked to the 1550 nm DFB light source, and the other end was linked with a handheld power meter. The weights (each weight about 1 kg) were added onto the micro bend modulator, as shown in Fig. 1, in order to increase the pressure acted on the micro bend modulator. It should be placed it gently, and tried to locate it in the center of the micro bend modulator, it could make spring stable as much as possible. With the purpose of reducing the jitter of generating error, the denticulate laminas should be made parallel moving at the same time. The forward and backward experiments had been verified for many times, and the result about the four groups of fitting curve has been shown in Fig. 6. It can be seen that the output power decreases with the increase of pressure, the same group of the forward and backward experiment coincide well, but the repeatability between multiple groups need to be improved. The reason is that spring is not installed on the limit column which lead to increase or decrease weight. When the denticulate laminas moves, the limit column here will generate the friction, and the force area of weight is small. The repeatability problem is appeared in the verification experiment, we use weights for simulating the pressure of back. Because the contact area of the weight is not large enough, we can’t make sure putting the weights at the exactly same position every time, it may cause tooth plate moving deviation. When the people sit on the chair and do the experiment, the contact area can cover the
sensor, so the influence of friction is decreased, the idea waveform figure could be present, and the repeatability problems are well improved. It can largely reduce the limit column of the friction. When the toothed plate was leant on the back to breathe that can increase the reaction area.The sensor link the photoelectric conversion module and the breathing waveform display on the oscilloscope. In addition to this, it can be seen that when people breathe, the waveform changes obviously. Due to the fact that oscilloscope cannot export the real-time waveform; the next step is to improve the experimental structure. The photoelectric detection and the acquisition circuit module have been applied into the experiment; with the extract the output waveform to computer, the data and the real-time drawing have been analyzed by using LabView. 4.2. Experimental research and data analysis In order to display the real-time waveform on screen, the LabView serial port communication and the data acquisition function are used to do the experiment (Fig. 7). On the base of the experiment platform, this paper has measured the different testers under the different conditions of breathing measurements. It is a good way to use the FFT to calculate the value and get the frequency spectrum distribution curve. According to the frequency distribution, the appropriate filter frequency is set in the figure. FFT is the fast Fourier transform. It is the fast algorithm of discrete Fourier transform, and it is based on discrete Fourier transform (odd, even, imaginary, real), in this way, the discrete Fourier transform algorithm is used to improve the analyzed waves. The following is analysis of data about tester 1 s respiratory signal. As you can see from Fig. 8(a), the respiratory signal gathered had abundant noise, and the respiratory waveform can be easily distinguished. The value of two waveform valley show the frequency is 0.345 Hz, Some information also can get from the spectrum that the frequency of 0.364 Hz signal and the respiratory signal frequency is almost coincident. With the extracted waveform from figure Fig. 8(c) and Fig. 8(d), the 0.0364 Hz waveform and the respiratory waveform gathered are more coincident. Therefore, the waveform signal frequency of 0.364 Hz is useful signal, and it should be retained. The frequency of 0.044 Hz signal is the noise signal, and the further analysis should be carried on. The high-pass filter is a good choice to remove noise. In addition, there are many smaller amplitude frequency components, the low-pass filter can remove
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Fig. 7. Test structural drawing of fiber optic micro bend respiratory sensor system.
it. In general, in order to get good breathing waveform the band pass filter should be used. For furthering validate the analysis, the next task is carrying on the different testers and different respiratory signal acquisition. The Three testers in two different conditions of respiratory waveform as shown in Fig. 9, from the experimental data it can draw a conclusion. The sampling time of experiments is 60s, the Fourier transform of the sampling frequency is 20 Hz, every 20 points for a breath. The peak amplitude of experiments is the respiration signal, for the rest of the signal is noise. According to the figures above, the results can be determined: the breathing rate frequency is between 0.18 Hz and 0.5 Hz. Furthermore, the data collected have the low frequency noise signal obviously. Some small amplitude of high frequency signal is mixed in it as well. In order to get a better waveform of the breathing rate, the noise signal should be removed. In amplitude, from the order of high to low are deep breath, normal breath and rapid breath. It matches the real behaviors condition. The differences of respiratory waveform is relatively obvious, the frequency of fast respire- troy waveform is faster than the frequency of normal respiratory waveform, low amplitude, which proved that the micro bend modulator structure designed can distinguish normal respiratory waveform and fast respiratory waveform. In the following, it is considered about the data characteristics by different situations. First of all, the optical fiber used in the experiment is not sensitive with the temperature. In addition, the temperature signal is slowly changed signal, so the Fourier transform could filter the temperature signal. In that reason, the results won’t be changed a lot under different temperature condi-
Fig. 8. Spectrum of tester 1 s respiratory signal.
tions. Because of the advantage of the fiber optical,this device can resistance to electromagnetic interference. In this paper, the designed filter has the unit impulse response, it retains damped oscillation which lasts about 20s. If the signal was analyzed may cause certain influence at this time, It is not necessary to analyze respiratory data in this 20s. After this 20s, it begins to record the data. The analytical method of the signal is the Fourier transform, the useful respiratory frequency signal could be separated by this
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Fig. 10. The device of standard error bar.
Fig. 11. The device of stability curve.
Fig. 9. Spectrum of 3 testers’ respiratory signal.
way. The respiratory signal frequency range from 0.18 to 0.5 Hz, the band-pass filter can filter the signal. The Fourier transform have no influence on the wave of direct component. It needs to be satisfied in the time domain what the frequency domain requires. The shifting of the direct component and the dynamics changing have no influence on the measurement as well. The stability of the proposed sensor is relatively good. In general, the breathing rate for people is around 16–20 times per minute, the volunteer took the breathing experiments many times. The result of the breathing rate was counted by manual and sensor. The 18 times per minute the manual counted was chosen as the standard of the breathing rate. The 50 groups of data was been collected from the breathing experiments. It has been compared with the sensor counting. According to the experimental result, it can be seen that there are 3 groups of data differ from the manual counting. The stability curve of the sensor is demonstrated. In addition, the error bar is showed as follows (Figs. 10 and 11). 5. Conclusion The design of lamina denticulate scheme was proposed on this paper and analyzed the experiment principle. The optical fiber
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micro bend mechanism is used in the experiment. When the different powers act on the optical fiber, the optical axis will produce a series of irregular tiny crook which can result in the loss of the power. Therefore it can be detected the respiratory rate by the change of the power loss. The principle is simple summarized that FOMBS monitors the optical fiber’s change by the external factor’s influence which can cause the transmission light intensity changes of optical fiber. It can be conducted the following experiment. Based on this study, in the first place, the influence of FOMBS’s number of teeth on optical power have realized by the principle of FOMBS technology. Then an elaborate plan and a simulation were designed, which aim to study the effect of the sensor. At last, the number of teeth of the fiber optic micro bend modulator has been determined by the simulation and the data analysis. Finally, it concluded that the improvement measure can improve the real-time performance by the experimental verification. Since the optical fiber micro bend is proposed in recent years, so this paper just has a superficial insight and it is hoped that it can provide solid information and vision for future study. Acknowledgments This work was supported in part by the National Natural Science Foundation of China under Grant 61425003 and 61403074, the Fundamental Research Funds for the Central Universities under Grant N150401001 and N140404023, the China Post-Doctoral Science Foundation Project under Grant 2014M560219, and in part by the State Key Laboratory of Synthetical Automation for Process Industries under Grant 2013ZCX09.
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Hai-feng Hu was born in Liaoning, China, in 1984. He received his Ph.D degrees in the Institute of Semiconductors, Chinese Academy of Sciences, China, in 2013. He is currently working in the College of Information and Engineering at Northeastern University. His research interests are nano-optics, plasmonics, fiber-optic sensors and their applications in biosensing. He has authored and co-authored more than 20 scientific papers, 2 patents and 5 conference presentations.
Si-jia Sun was born in Liaoning, China, in Feb. 1993. She received her B.A. degrees in the College of Information Science and Engineering from the Shenyang University of Technology, China, in 2015. She is now a graduate student of Northeastern University. Her research interests are fiber optical sensors, fiber Bragg grating sensors, regenerated fiber Bragg grating sensors.
Ri-qing Lv was born in Guangdong, China, in 1985. He received his B.S, M.A. and Ph.D. degrees, respectively, in biomedical engineering, circuit and system, detection technology and automatic equipment from Northeastern University, Shenyang, China, in 2008, 2010 and 2014. He is currently working in the College of Information Science and Engineering at Northeastern University as a postdoctor. His research interests are magnetic fluid and fiber-optic sensors. He has authored and co-authored about 30 scientific papers, patents and conference presentations.
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Yong Zhao received his M.A. and Ph.D. degrees, respectively, in precision instrument & automatic measurement with laser and fiber-optic techniques from the Harbin Institute of Technology, China, in 1998 and 2001. He was awarded a first prize scholarship in 2000 by the China Instrument and Control Society and the Sintered Metal Corporation (SMC) scholarship in Japan. He was a scholarship in Japan. He was a postdoctoral fellow in the Department of Electronic Engineering of Tsinghua University from 2001 to 2003, and then worked as an associate professor in the Department of Automation, Tsinghua University of China. In 2006, he was a visiting scholar of University of Illinois in Urbana and Champagne, USA. In 2008, he was awarded as the “New Century Excellent Talents in University” by the Ministry of Education of China. In 2009, he was awarded as the “Liaoning Bai-QianWan Talents” by Liaoning Province. In 2011, he was awarded by the Royal Academy
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of Engineering as an academic research fellow of City University London. In 2014, he was awarded by the National Science Foundation for Distinguished Young Scholars of China. In 2015, he was honored as the Yangtze River Scholar Distinguished Professor by the Ministry of Education of China. Now he is working in Northeastern University as a full professor. As the academic leader and director of his research institute, his current research interests are the development of fiber-optic sensors and device, fiber Bragg grating sensors, novel sensor materials and principles, slow light and sensor technology, optical measurement technologies. He has authored and co-authored more than 200 scientific papers and conference presentations, 19 patents, and 5 books. He is a member in the Editorial Boards of the international journals of Sensor Letters, Instrumentation Science & Technology, Journal of Sensor Technology, and Advances in Optical Technologies.