Review Papers

Fiber-optic sensors for monitoring patient physiological parameters: a review of applicable technologies and relevance to use during magnetic resonance imaging procedures

[+] Author Affiliations
Łukasz Dziuda

Military Institute of Aviation Medicine, Technical Department of Aeromedical Research and Flight Simulators, Krasińskiego 54/56, Warszawa, 01-755 Poland

J. Biomed. Opt. 20(1), 010901 (Jan 16, 2015). doi:10.1117/1.JBO.20.1.010901
History: Received August 15, 2014; Accepted December 8, 2014
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Abstract.  The issues involved with recording vital functions in the magnetic resonance imaging (MRI) environment using fiber-optic sensors are considered in this paper. Basic physiological parameters, such as respiration and heart rate, are fundamental for predicting the risk of anxiety, panic, and claustrophobic episodes in patients undergoing MRI examinations. Electronic transducers are generally hazardous to the patient and are prone to erroneous operation in heavily electromagnetically penetrated MRI environments; however, nonmetallic fiber-optic sensors are inherently immune to electromagnetic effects and will be crucial for acquiring the above-mentioned physiological parameters. Forty-seven MRI-tested or potentially MRI-compatible sensors have appeared in the literature over the last 20 years. The author classifies these sensors into several categories and subcategories, depending on the sensing element placement, method of application, and measurand type. The author includes five in-house-designed fiber Bragg grating based sensors and shares experience in acquiring physiological measurements during MRI scans. This paper aims to systematize the knowledge of fiber-optic techniques for recording life functions and to indicate the current directions of development in this area.

Continuous monitoring of human physiological parameters throughout a 24-h activity cycle is becoming more common, and new application areas are continually being developed. Devices for recording vital functions have long been used outside of the doctor’s office, e.g., athletes use personal recorders to control their training intensity.1 Moreover, the development of wireless data transmission technologies and teletransmission has resulted in the creation of many home monitoring systems, which are capable of recording and independently transmitting medical parameters to a patient service center.2 If clinically significant changes are observed in the analyzed data, the supervising doctor is notified by a short message service, e-mail, or fax so that an appropriate treatment can be specified.

Similar systems have been implemented for monitoring drivers, machine operators, and technological systems operators. For example, if symptoms of fatigue, falling asleep, or fainting have been detected, an alarm signal would be triggered to stop the vehicle or device.3 In addition, both military and civil aviation utilize systems for monitoring pilots to monitor their psychophysiological state,4 ensuring pilot and passenger safety as well as the mission outcome, aircraft condition, and load being transported.

When monitoring seated individuals, the sensors and associated measuring equipment can be placed directly in the back or base of the seat, enabling monitoring without attaching electrodes or the recorder to the body.5 On the other hand, special requirements are imposed on systems that must be able to operate in harsh environments without failing, such as high-temperature or high-humidity environments, which prevail in nonair-conditioned cockpits, and environments with high electromagnetic (EM) interference caused by radio or on-board radar systems.

Magnetic resonance imaging (MRI) examination presents another situation in which devices used for monitoring physiological parameters must be capable of operating in an environment with a strong EM field.6,7 For example, monitoring changes in basic physiological parameters can enable the early detection of a claustrophobic episode, allowing the test to be immediately interrupted to remove the patient from unpleasant sensations.8

In this paper, the author justifies the need for monitoring basic physiological parameters in patients undergoing MRI scans, systematizes the knowledge of fiber-optic techniques purposed for recording life functions, which are potentially suitable for an MRI environment, and indicates the current directions of development in this area.

Description of the MRI Environment

The MRI environment is distinguished by high levels of magnetic induction density: 1.5 to 3.0 Tesla (T) in typical appliances. However, systems achieving densities of 9.4 T or even 21.1 T have also been developed.9,10 Strong penetration by the magnetic field is accompanied by high EM field strength, inducing radio frequency impulses. Conventional measuring equipment was not designed to work in such an environment.1113 Placing metal elements, which are common electronic components in typical recorders, in a strong magnetic field can induce eddy currents in these elements and cause them to heat up. This, in turn, can cause skin burns in patients.1416 Moreover, metal elements inside an MRI scanner affect the distribution of the EM field and could, therefore, impair the image quality. Additionally, the electrical signal transmitted by typical copper wires in conventional measurement equipment is sensitive to a strong EM field. As a result, the measured parameter information may be altered before reaching the MRI system operator, rendering the measurements unusable.

Optical sensors can provide an alternative solution for measurement equipment.17,18 Because optical sensors are free from metal elements, they are fully penetrable by the EM radiation used in MRI and cause no interference.19 Fiber-optic sensors2022 transmit signals using optical fibers, providing them with immunity to EM fields. Moreover, there are fiber-optic sensors23 that are able to acquire a patient’s physiological signals and subsequently extract the chosen parameters2428 if they are configured in an appropriate manner, i.e., connected with mechanical elements and placed near the patient.

Episodes of Claustrophobic Reactions During MRI Examinations

Along with computed tomography (CT), MRI has become one of the most common methods for detecting lesions in tissues.29 Despite its high diagnostic efficiency and prospects for further advancement, e.g., functional magnetic resonance imaging, MRI has a major disadvantage because the patient must be placed in a narrow cylindrical tube for a few dozen minutes, which can induce claustrophobia or panic attacks. Furthermore, during brain scans, the patient’s head is immobilized with a special collar, exacerbating the patient’s discomfort. Attempts to minimize these reactions using open-type MRI systems have produced poor results. The patient’s knowledge that the examination requires assuming a certain position for a length of time invades the patient’s personal and mental space. As a result, an estimated 5 to 10% of patients undergoing an MRI experience high stress related to their restriction in the MRI chamber.30,31 Moreover, 10% or more of all examinations using MRI cannot be commenced or completed due to claustrophobia.32 The acute manifestation of anxiety symptoms immediately before or during MRI examinations can also occur in persons who have been taught anxiety and stress management techniques.33 In the case of a 26-year-old man who was referred for an MRI due to back pain,34 the MRI examination very likely contributed to the patient’s development of posttraumatic stress disorder, which is, according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), an anxiety disorder caused by exposure to high stress.35

The reasons reported by patients for experiencing anxiety and (often) fear of MRI examinations include not only the space limitation and movement restriction, but also the high noise levels generated by the equipment, long duration of the examination, total isolation from the staff, and equipment that moves slowly toward the patient.36,37 As many as 30% of patients undergoing MRI examinations experience mild symptoms of anxiety and stress. Such episodes usually result in the examination being stopped or extended. Moreover, these episodes may result in the administration of anxiolytics and sedatives to the patient, which is not always advised, possible, or safe.32 Such actions may ultimately increase the examination cost as a result of the extended equipment use and involvement of additional medical and technical staff. Therefore, the early detection of anxiety or panic attacks is a significant issue in medicine and a considerable challenge for both equipment designers and all persons involved in examinations requiring any type of chamber, such as those employed in modern neuroimaging techniques.

Basic Physiological Parameters and Their Link to Claustrophobia

While a multipoint acquisition of physiological parameters, e.g., using a Holter-type system, is applied for diagnosis in hospitalized patients, the simple monitoring of basic vital functions is sufficient for persons monitored during regular activities. The respiration rate (RR), which specifies the number of ventilations per minute (vpm),38 as well as the heart rate (HR), i.e., the number of heart beats per minute (bpm),39 are basic physiological parameters. In general, RR is estimated using a respiration curve, while HR, coincident with pulse and heart rhythm, can be estimated based on an electrocardiogram, ballistocardiogram, or plethysmogram. Prophylactic examinations allow for the early detection of increased and/or irregular RR or HR, which can indicate emerging health disorders. Alarming trends in basic physiological parameters can justify a precautionary outpatient examination; likewise, similar trends observed during an MRI examination should lead to the completion or suspension of the examination and its adjustment in line with the current situation of the patient.

Respiration monitoring can be used to detect hyperventilation. Hyperventilation, i.e., an increased rate of pulmonary ventilation and considerably decreased depth of breathing, often leading to syncope,40,41 is closely related to anxiety and panic disorders.42,43 Breathing patterns in persons experiencing panic attacks are distinguished by high variability and irregularity.44 Therefore, panic attacks can be predicted or monitored in terms of the course, intensity, and the speed at which the symptoms resolve.

One aspect in the study of hyperventilation concerns the mechanisms as well as physiological and psychological factors responsible for anxiety symptoms. In addition, conscious and controlled breath management has been analyzed for the treatment of various anxiety disorders. Because attempts to control and normalize breathing helped to reduce symptoms of anxiety and panic,45 therapeutic programs have been developed to teach patients how to cope efficiently with hyperventilation during MRI examinations.46

The patient’s heart function should also be measured during examinations47 because HR indicators are considerably higher in persons suffering from general anxiety, panic, and hyperventilation in comparison with those who do not experience such discomfort. Therefore, that continuous, online monitoring of patients’ circulatory parameters during MRI examinations will allow for the prediction and assessment of anxiety, panic, and claustrophobia closely related to the circumstances of examination.

Although patients likely to experience claustrophobic anxiety attacks are the most common group classified to be monitored inside an MRI magnet, there are many other patient categories that require monitoring and support during MRI procedures. These are patients who are unable or may not be able to communicate or to use the alarm button:7

  • neonatal and pediatric patients,
  • sedated or anesthetized patients,
  • disabled and insensible patients,
  • patients in coma,
  • patients with mental disorders,
  • patients with impaired physiological functions,
  • critically ill or high-risk patients,
  • patients developing reactions to contrast media,
  • patients with implanted pacemakers.

Categorization of Monitoring Principles

Most of the fiber-optic sensors23,4850 configured for delivering information on vital functions have been developed over the last 20 years and the results have been published in almost 100 papers.41,51145 Though only some of these sensors have been tested in an MRI environment, fiber-optic sensors are inherently immune to EM radiation and can be MRI-compatible. For these reasons, we consider all of the sensors discussed in the next section as potentially suitable for an MRI environment.

Forty-two fiber-optic sensors constructed by other groups41,51133 and five in-house-designed sensors134145 for monitoring vital signs can be easily classified into three major categories with several subcategories each, according to the location of the sensor application. In addition, we can distinguish seven sensor classes regarding the type of measurand as follows:

  1. Sensors placed in (1a) a nostril or (1b) oxygen mask, measuring (I) humidity, (II) temperature, or (III) force of inhaled/exhaled air (flow);
  2. Sensors embedded into (2a) expandable belts or (2b) special garments as well as affixed directly to (2c) the body, measuring (IV) the elongation/contraction, (V) strain (including curvature), or (VI) lateral pressure caused by respiration and/or heart work;
  3. Sensors attached to (3a) the back of a chair, placed on/in/under (3b) a bed mattress, or embedded into (3c) a pneumatic cushion, measuring (V) the strain, (VI) pressure, or (VII) force caused by respiration and/or heart function.

Figure 1 illustrates this classification by showing the number of sensors in relation to the placement of the sensing element and the type of measurand. The largest groups are sensors embedded into a textile belt or bed mattress, which measure lung- and/or heart-induced elongation/contraction and strain, respectively.

Graphic Jump LocationF1 :

Sensor classification depending on the placement of the sensing element and the type of measurand.41,51145

To illustrate how trends in the area of fiber-optic sensors for recording physiological functions have changed over the last 20 years,41,51145Fig. 2 shows the number of articles published in any individual year in each of the three categories. In the 1990s and at the beginning of the new millennium, the first devices placed in a nostril or oxygen mask were proposed. A significant development has occurred since the mid-2000s, when it was noted that the measuring elements could be embedded into wearable textiles, ensuring the immediate proximity of the sensors to the lungs and heart. However, due to the wide range of clothing sizes required to accommodate different patients, the interest in textile-based sensors has decreased in recent years. Wearable-textile sensors are now being replaced by sensors embedded into a bed or seat that do not require preparing the patient for monitoring. In addition to the literature review, the author describes his group’s work on embedded sensors.134140,142145

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Publishing activity in the field of fiber-optic sensors for monitoring vital signs.41,51145

Results of Literature Review
Intensity-modulated fiber-optic sensors

In recent years, different research groups have presented dozens of fiber-optic sensor designs suitable for use in an MRI environment that allow the RR and/or HR to be obtained after processing the recorded signal. An RR-monitoring device that detected the evaporated humidity from the mouth and/or nose was one of the first sensors to be studied.5155 The condensed humidity substantially alters the interaction between the light from the optical fiber and the surrounding medium, which can be monitored by a photodetector. As shown in Fig. 3(a), during expiration, a water film (many hemispherical water drops) is formed at the optical fiber end with a refractive index >1, and the amount of light reflected back into the fiber decreases. During inspiration [Fig. 3(b)], the dry and cool air next to the fiber does not produce condensation at the tip. As the refractive index at the boundary approaches 1, the amount of light reflected back into the fiber increases. These changes in light reflection can be measured by a photodetector positioned at the opposite end of the optical fiber, and the RR can be monitored by counting the cyclic variations in the light reflection.

Graphic Jump LocationF3 :

Operation of an intensity-modulated fiber-optic sensor during (a) expiration and (b) inspiration.51,52

Table 1 lists the major properties of intensity-modulated fiber-optic sensors designed for monitoring respiration and/or heart function, which were studied in an MRI environment or are suitable for use in the presence of strong EM fields. In the first column, the category and subcategory of the sensor, according to above classification, are provided together with the reference paper(s) describing each of the mentioned devices. The second column presents the form of the sensor and the physiological parameter(s) that can be monitored. The third column summarizes the experimental studies and their results, including the number of participants, testing procedure, and quantitative data on the sensor efficiency. The last column shows the MRI compatibility of the individual sensors verified at a given magnetic induction and/or for given imaging sequences.

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Table 1Intensity-modulated fiber-optic sensors for respiration monitoring.
Interferometric fiber-optic sensors

At the same time, solutions also emerged that were based on phase interferometry, where the optical signal that was directed to the measurement area of the optical fiber (placed near the monitored person, e.g., in the back or base of the seat) was compared with the output signal, which was modified by disrupting factors, such as respiration and heartbeats.5675 Body movements caused by the function of the lungs and heart cause phase changes between signals (sensing and reference) and could be identified as a series of time-variable interference patterns. Thus far, in research on the acquisition of physiological signals, fiber-optic interferometers have been tested in their most popular configurations, i.e., Michelson, Mach-Zehnder, and Sagnac interferometers.5860 The popular Michelson interferometer has been the most widely studied.6172 As shown in Fig. 4, the Michelson interferometer consists of two optical paths (arms), i.e., the sensing and reference fibers. Both fibers have mirrored ends, and the sensing region is formed by the differential path length between the two parallel fibers. Minute lung- and/or heart-induced changes in the sensing fiber length cause significant changes in the phases of reflected light, which subsequently produces changes in the optical power monitored by the photodetector and allows for the determination of RR and/or HR.

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Configuration of a fiber-optic Michelson interferometer.6169

Human vital signs have also been monitored using fiber-optic speckle interferometry.7375 Speckle patterns can be observed in the laser light output of coherently illumined multimode fibers (MMFs), as shown in Fig. 5. The fiber output is projected onto a complementary metal-oxide semiconductor imaging sensor. Consecutive speckle images arise from the interference between propagating fiber modes and are highly sensitive to external fiber perturbations, such as those caused by the mechanical impact of human activity.

Graphic Jump LocationF5 :

Configuration of a fiber-optic speckle interferometer.

Recently, interferometric sensors have been developed in which a segment of photonic crystal fiber (PCF) was used as the measuring element.76,77 As shown in Fig. 6, the collapsed region within the PCF allows the excitation and recombination of modes, thus creating an interferometer. The reflection spectrum of this device displays a sinusoidal interference pattern that instantly shifts when water molecules, which are present in exhaled air, are adsorbed on or desorbed from the PCF surface. Therefore, these sensors detect the difference between the humidity of inhaled and exhaled air, which allows a respiration curve and RR to be obtained.

Graphic Jump LocationF6 :

Basic system with a photonic crystal fiber segment for monitoring breathing humidity.76,77

A cornerstone for the development of the photonic crystal based interferometer was the Fabry-Pérot (FP) etalon interferometer shown in Fig. 7, which was formed by placing alternating multilayer thin films of polymers and inorganic nanoclusters on the cleaved end of a single-mode fiber (SMF).7880 However, the patient is required to wear a mask with built-in sensors, which presents a notable obstacle of the PCF- and FP-based fiber-optic interferometers for respiration monitoring. Table 3 lists the major results obtained using these devices.

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Fabry-Pérot-based breathing sensor: (a) basic system and (b) sensing head.79,80

The key advantage of interferometric methods is their high sensitivity; however, this can imply instabilities in the signal amplitude if the monitored person moves, changes his/her position, or simply coughs.59,60 Then, the signal amplitude can reach relatively high values, which bring difficulties in the demodulation of the phase signal. Therefore, systems for the elimination or compensation of body movements are required, and advanced signal analysis techniques have to be able to detect miniature signal changes carrying information on respiration activity and heart function. Major outcomes obtained using these interferometric fiber-optic sensors for respiration and/or heart function monitoring are listed in Table 2, using a column layout identical to that presented in Table 1.

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Table 2Interferometric fiber-optic sensors for respiration and/or heart function monitoring.
Sensors in modalmetric configuration

While the vital activity information is contained within the phase changes in fiber-optic interferometers, the so-called modalmetric configuration of a sensor detects the vibrations related to vital functions as light intensity modulations proportional to those functions (sensor category: 3a.V).60,81 Such sensors consist of (1) an SMF transmitting segment, (2) an MMF segment sensitive to mechanical stress, and (3) an SMF receiving segment, as shown in Fig. 8. The single-mode transmitting fiber delivers optical radiation to the MMF section, in which the layout of the mode field is dependent on mechanical deflections caused, for example, by respiration and heart function. In other words, the signal loss is primarily due to the bending loss when the MMF section is deformed. The amount of light reaching the single-mode receiving fiber reflects the layout of the mode field. Thus, the receiving section of the sensor serves as a detector for the radiation propagated within the MMF section, i.e., the measurement head. As described in the solutions involving interferometry, the measurement of vital functions with a modalmetric sensor is accomplished using ballistography.60,81 The main disadvantage in the use of this type of sensor is that it is difficult to simultaneously record respiration and heart function. So far, no comprehensive evaluation of the modalmetric sensor has been performed in the MRI environment.

Graphic Jump LocationF8 :

Schematic layout of the mode field in the modalmetric sensor configuration.

Micro- and macrobending fiber-optic sensors

In sensors measuring transmission loss caused by slight (miniscule) deflections of an optical fiber or in fiber bends with a radius of curvature well above the fiber diameter (>10mm), i.e., in so-called micro-8288 and macrobend89107 sensors, respectively, the intensity of the light reaching the receiver is also measured. As in the cases described above, body movements (caused by respiration and heart function, among other things) are a complicating factor since these movements produce micro- and macrobends of fibers with a variable radius of curvature. Thus, along the axis of a bent fiber, the layout of the mode fields continuously changes as the energy radiates; this is seen in the form of light intensity changes at the receiver. The measuring system for micro- and macrobend sensors is distinguished by a simple design for the sensors alone as well as for the associated transceiver modules (light source and photodetector). Nevertheless, due to their relatively low sensitivity, the sensors have to be embedded in a special mat82,83 or cushion,8588 on which the patient lies during monitoring, or in textiles, such as a vest, T-shirt, or belt, which are worn by the monitored person,89107 to ensure immediate proximity to the lungs and heart. An example of a microbend sensor system is shown in Fig. 9(a). The sensor mat is constructed by means of two microbenders with MMF passed between them, as shown in Fig. 9(b). The whole setup is covered with a textile material to protect the sensor. A macrobend sensor embedded into an expandable belt is illustrated in Fig. 10 in its most common arrangements, i.e., half-loop (half-oval-form), figure-eight loop, and U-shape.

Graphic Jump LocationF9 :

Microbend fiber-optic sensor: (a) basic system and (b) microbender structure.83,84

Graphic Jump LocationF10 :

(a) Macrobend sensor in an expandable belt. Arrangement of the optical fiber in the macrobend sensor: (b) half-loop, (c) figure-eight loop, and (d) U-shape.92107

Another method for improving the sensitivity is the use of a standard MMF41 or SMF108 into which a short section of SMF with a narrower diameter core is inserted. In this hetero-core sensor segment, the transmitted beam is partially leaked into the cladding layer. Additionally, as shown in Fig. 11, the leaked light changes with the bending action of the hetero-core segment, and the bending property can be measured from the changes in transmission.

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Operation of a hetero-core fiber sensor.108

Table 3 characterizes the major properties of these micro- and macrobend fiber-optic sensors obtained during experimental studies.

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Table 3Micro- and macrobending fiber-optic sensors for respiration and/or heart function monitoring.
Plastic optical fiber-based sensors

A variation of the microbend sensor is a system in which the intensity of light falling onto a plastic (polymer) optical fiber (POF) head is measured; this light was previously reflected from a mirror surface whose distance from the fiber front changes according to the respiration rhythm.109Figure 12(a) shows the structure of the abdomen-attached respiration sensor. The polymethyl-methacrylate (PMMA) tube fastens the aluminum mirror and one end of the spring, while the other end of the PMMA tube is attached to the POF tip.

Graphic Jump LocationF12 :

The plastic (polymer) optical fiber (POF)-based sensors for detecting (a) abdominal respiratory movements, (b) humidity, and (c) temperature of the exhaled air.109,111

Other solutions utilizing POF allow RR monitoring based on the temperature difference between inhaled and exhaled air109,110 or the force with which the air is exhaled immediately in front of the nose or mouth.111 In the first case, shown in Fig. 12(b), the intensity of the reflected light is changed upon the color variation of the temperature-sensing film, and the modulated light is guided to a photodetector via the POF link. In the second device, depicted in Fig. 12(c), the force of the exhaled air pushes a vertical flap, and the coupling of light from the fixed fiber becomes disturbed. The change in coupled power can be easily measured by a photodetector.

Breathing condition sensors also utilized POF as a substrate for the cladding layer, which swells when it comes into contact with water molecules within the exhaled air, as shown schematically in Fig. 13.112,113 Under the dry-state conditions in Fig. 13(a), the refractive index of cladding layer, n2, is slightly larger than that of the PMMA fiber core (n1=1.489), and the sensor head is a leaky-type head. For the humid state in Fig. 13(b), the sensor head becomes a guided-type head as n2 decreases, and the output light power, Pout, through the sensor head will increase remarkably, i.e., Pout2>Pout1.

Graphic Jump LocationF13 :

Operation of a POF-type breathing sensor in the (a) dry state and (b) humid air.113

Table 4 characterizes the major outcomes obtained using the above-mentioned POF-based sensors.

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Table 4The plastic (polymer) optical fiber based sensors for respiration monitoring.
Optical time domain reflectometry based sensors

Another known solution is based on optical time domain reflectometry (OTDR), where the propagation of a light impulse (introduced into the POF and dispersed with partial reflection at the location of the mechanical disturbance of the fiber) is measured as a function of time (sensor category: 2a.IV).96101,114Figure 14 illustrates a basic system employing a POF-OTDR-type sensor for respiration monitoring. The preliminary results show sufficient sensitivity for detecting respiratory movements, i.e., cyclic strain between 0 and 3%. Moreover, steps of 0.25% strain could be measured, demonstrating a quadratic correlation between the sensor signal and the applied strain. However, the sensor has not been evaluated in the MRI environment. The disadvantages of this type of sensor are a relatively low sampling rate for the signal and the need for complex and expensive transceivers.

Graphic Jump LocationF14 :

Basic system with a POF optical time domain reflectometry type sensor for detecting respiration.96

The list of sensors allowing the acquisition of the respiration curve with the ballistocardiographic (BCG) signal is completed by solutions based on fiber Bragg gratings (FBGs) whose properties are described in the next section. The author also devotes Sec. 5.1 and 5.2 to explore the literature and present his work on FBG-based vital signs sensors, respectively.

Principle of Operation of FBG Sensors

In recent years, FBGs have been the subject of much research and are some of the most widely utilized optical elements, serving a wide range of applications in telecommunications as well as in laser and measurement technology. The applications in which FBGs serve solely as sensors cover many fields,146 e.g., the monitoring of structural health,147150 operating conditions of electrical plants,151153 or life processes in the human body.2628,154158 Furthermore, FBGs are popular for their resistance to modulations in the optical signal intensity, which is possible because of the so-called spectral encoding, i.e., the information is contained not in the light intensity but in a spectral parameter (wavelength).159 This property, along with its so-called self-reference capability, i.e., a return to the referential values of spectral parameters after achieving the initial conditions, allow multiple Bragg gratings to be contained within one optical fiber.160,161 Exhibiting the standard advantages of fiber technologies, FBG-based sensors are immune to EM effects, chemically inert, small-scale, lightweight, and provide electrically safe modes of operation.162,163

A typical FBG sensor operates as a stop-band filter, where part of the light falling onto the grating is not retained but reflected. The Bragg grating is formed by a portion of the SMF core where periodic modulation is introduced in the refractive index value.164 Beams of light reflected from individual grating layers, with the same phases, are subject to interference. This phenomenon occurs at only one wavelength, called the Bragg wavelength or the central wavelength, λB: Display Formula

where neff is the effective refractive index,165 and Λ is the modulation period of this index.

The spectrum of light reflected from the grating forms a pointed intensity peak, the maximum value of which is located at the Bragg wavelength, whereas the spectrum of light transmitted through the grating is a narrow intensity trough with its minimum value at the Bragg wavelength. An example of the signal reflected from a Bragg grating simulated using the T-matrix method166168 in Mathcad software is shown in Fig. 15. The simulated FBGs have the Bragg wavelength of 1550 nm with 4000 [Fig. 15(a)] or 12,000 [Fig. 15(b)] index modulation periods, which is equivalent to a grating length of 2 or 6 mm, respectively. The peak sharpness, full-width at half-maximum (FWHM), and the corresponding reflectance can be adjusted by the number of refractive index perturbations. In most sensor applications, the central wavelength is determined from the peak position because the shape of the reflected signal is easier to demodulate. Therefore, FBG-based sensors have one crucial advantage: they can be connected to a transceiver with a single fiber cable. This means that the sensor can be connected using only one of its terminals.

Graphic Jump LocationF15 :

Reflected spectrum simulated using the T-matrix method for (a) 2-mm fiber Bragg grating (FBG) and (b) 6-mm FBG.

Strain and Temperature Sensitivity of FBGs

The FBG susceptibility to strain, which is manifested as a shift of the Bragg wavelength, ΔλB, motivated our first FBG sensor model for monitoring respiration and heart function. The Bragg shift148,169 has the following relationship: Display Formula

where p11 and p12 are the photoelasticity coefficients of silica (fiber core), v is Poisson’s coefficient, Δε is the strain change, and ρe is the effective photoelasticity coefficient. When a 1550-nm-wavelength light is injected into the FBGs inscribed into the core of a germanium (Ge)-doped fiber, the effective elasticity coefficient is 0.218.169 The strain change, expressed in the units of microstrain (με), is given by:168,170Display Formula
where the FBG strain responsivity, kε, is 1.212pm/με.

Due to the phenomenon of thermal expansion, the Bragg wavelength is also affected by temperature changes, ΔT, as follows: Display Formula

where α and ζ are the thermal expansion and thermo-optic coefficients, respectively. Typically, α ranges from 0.54 to 0.55×106/°C, while ζ usually ranges from 8.3 to 8.6×106/°C for the Ge-doped silica fiber core.150,153,171173 Therefore, for a wavelength of 1550 nm, the temperature change is given by: Display Formula
where the FBG temperature responsivity, kT, is 13.7pm/°C.150,174,175 Due to the considerable difference between the fiber diameter (125μm for common optical fibers) and the FBG length (5 to 10 mm for a standard grating inscribed in an SMF core), the effects of the fiber diameter are assumed to be negligible. Finally, the expected strain- and temperature-induced wavelength shift of an FBG can be calculated as follows: Display Formula

Mathcad Simulations

As the heart and lungs work, deformations occur on the surface of the torso, which can be measured by strain gauges, such as FBG sensors. Preliminary testing with an FBG applied to the chest near the heart showed that heartbeats cause peak-to-peak strains with values not less than 4με. At the same time, breathing-induced strains were detected at least four times greater than the heart beats, i.e., >16μεpk-pk. These values were taken as the amplitudes of the BCG signal and the respiration curve, respectively, to demonstrate how the working heart and lungs affects the Bragg wavelength when an FBG makes physical contact with the subject’s torso. Figures 161718 show the results of simulations performed using Mathcad software. Figure 16 demonstrates changes in the Bragg wavelength caused only by cardiac function, e.g., during apnea. The upper graph shows a 1-s window (2-s window shown in the still image) representing the animated curve of the heart-induced strain during the 30-s measurement duration. The signal was obtained by the superposition of several sine functions whose amplitudes and periods were chosen so that the resultant signal shape was similar to a ballistocardiogram.176,177 In other words, the BCG signal expressed in microstrains with a 4-με amplitude and 1-s period (60 bpm) is presented in the upper graph. The middle graph shows the strain-induced Bragg wavelength shifts of the FBG peak synchronized with the strain changes. To facilitate the calculation, the reflected spectrum is represented by a Gaussian with a reflectance close to 1 and with an FWHM of 0.1nm. The lower graph demonstrates how changes in the heart-induced strain modulate the Bragg wavelength in time. The axes are intentionally inverted to emphasize synchronization with the middle graph. Moreover, this result reveals that the maximum value of the FBG reflected spectrum could be used for drawing the ballistocardiogram shape in wavelengths. According to Eq. (3), the strain-induced wavelength shift changes linearly with the heart-induced strain, hence the heart-induced Bragg wavelength shift.

Graphic Jump LocationF16 :

Demonstration of Bragg wavelength shift with heart-induced strain (MOV, 2.51 MB) [URL:].

Graphic Jump LocationF17 :

Demonstration of Bragg wavelength shift with heart- and lung-induced strain (MOV, 2.36 MB) [URL:].

Graphic Jump LocationF18 :

Demonstration of Bragg wavelength shift with heart- and lung-induced strain as well as a temperature increase of 30°C (MOV, 2.11 MB) [URL:].

Figures 17 and 18 show the same BCG signal additionally supplemented with the effects of breathing and temperature changes, respectively. The videos are presented in a similar convention as Fig. 16, except that the upper graph in Fig. 18 shows a 5-s window representing the animated curve of the heart- and lung-induced strain along with the temperature trace (rate increase of 1°C/s). The characteristic shape for the breathing signal was obtained using a superposition of the sine function and its second harmonic. The resultant signal has a 16με amplitude and 5-s period (12 vpm). Finally, the ballistocardiogram and respiration curve signals are superposed to form the time-varying trace of the strain exerted on the FBG sensor. Fig. 18 clearly shows that gradual heating of the grating does not disturb the measurement of heart- and lung-induced strain because the temperature growth influences the mean value of the measured wavelength (signal), whereas the heart- and lung-induced vibration causes changes to the instantaneous value. The temperature-induced drift can be removed by appropriate signal processing, and hence, further considerations could treat the effects associated with temperature fluctuations without affecting the heart- and lung-induced Bragg wavelength shift measurements.

Literature Exploration

The literature provides a number of descriptions in which a single FBG115118 or multiple FBGs97106,114,119123 act as the main sensing elements for acquiring body movements caused by respiratory and/or heart function. In both cases, FBGs can be embedded in the clothing worn by the patient during monitoring 97106,115122 or mounted in the bed on which the person lies, as shown in Fig. 19.123

Graphic Jump LocationF19 :

Sample locations of FBGs: (a) single sensing element sewn in a T-shirt116 and (b) bed sensor array.123

Furthermore, FBGs are used as sensors for detecting sounds produced by a working heart.124,125 Preliminary studies of long-period gratings (LPGs), a variation of Bragg gratings, for recording ventilatory movements and/or volumes have been performed because these gratings are particularly sensitive to any deformations in the LPG section.126132 Change in thorax curvature is sensed as bending of an LPG attached to the thorax. Bending induces strain and stress across the fiber and, in consequence, a change in its refractive index via the strain-optic effect, which manifests as a change in position, shape and amplitude of resonant bands in the transmission spectrum. The cladding modes generated by an LPG are more affected by bend-induced refractive index changes across the fiber than the backpropagating core modes generated by an FBG. Until recently, complex and expensive transceiving systems were used to handle LPG-based sensors, although the latest studies present a monochromatic measurement scheme that requires only a photodiode as a detector.132 Moreover, a fiber LPG curvature sensing scheme has been presented lately as a system capable for detecting the mechanical motions and/or sounds of the human heart from surface of the torso.133Table 5 lists the major properties of FBG-based sensors for respiration and/or heart function monitoring. In general, fiber gratings provide many benefits with relatively few disadvantages, therefore, these elements have been of interest to the author for application to physiological measurements.

Table Grahic Jump Location
Table 5The fiber Bragg grating (FBG) based sensors for respiration and/or heart function monitoring.