Microbend Fiber Optic Sensor Research Articles

Noncontact Sensors for Vital Signs Measurement: A Narrative Review.

Vital signs are crucial for monitoring changes in patient health status. This review compared the performance of noncontact sensors with traditional methods for measuring vital signs and investigated the clinical feasibility of noncontact sensors for medical use. We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE) database for articles published through September 30, 2023, and used the key search terms "vital sign," "monitoring," and "sensor" to identify relevant articles. We included studies that measured vital signs using traditional methods and noncontact sensors and excluded articles not written in English, case reports, reviews, and conference presentations. In total, 129 studies were identified, and eligible articles were selected based on their titles, abstracts, and full texts. Three articles were finally included in the review, and the types of noncontact sensors used in each selected study were an impulse radio ultrawideband radar, a microbend fiber-optic sensor, and a mat-type air pressure sensor. Participants included neonates in the neonatal intensive care unit, patients with sleep apnea, and patients with coronavirus disease. Their heart rate, respiratory rate, blood pressure, body temperature, and arterial oxygen saturation were measured. Studies have demonstrated that the performance of noncontact sensors is comparable to that of traditional methods of vital signs measurement. Noncontact sensors have the potential to alleviate concerns related to skin disorders associated with traditional skin-contact vital signs measurement methods, reduce the workload for healthcare providers, and enhance patient comfort. This article reviews the medical use of noncontact sensors for measuring vital signs and aimed to determine their potential clinical applicability.

Noninvasive measurement of the vital signs of cancer patients with a dual-path microbend fiber sensor.

A novel dual-path microbend fiber optic sensor is designed for noninvasive measurement of respiratory rate (RR) and heart rate (HR) for cancer patients. The performance of the microbend fiber sensor is assessed in two groups of cancer patients, cancer patients with pain and without pain, ranging from eighteen to ninety-six years old in a daily observational measurement with the sensor mattress under the mattress of the clinical bed. All the patients received standard clinical monitoring for evaluating the accuracy of our measurement results. The results of our study showed good consistency in the experimental results of RR and HR between the dual-path fiber sensor we proposed and the hospital equipment with average errors of 3.60 beats per minute (bpm) and 1.02 respiration per minute (rpm) in HR and RR measurement in cancer patients with pain and 1.87bpm and 1.27rpm in HR and RR measurement in cancer patients without pain, respectively. In HR monitoring, the single path microbend fiber optic sensor has 8035 minutes of data with a false report rate of 19.09%, while the dual-path microbend fiber optic sensor has 6188 minutes of data with a false report rate of 12.87%. The dual-path sensor has a smaller false report rate compared with the single path sensor due to pre-judgments of data with path 1 and path 2. To our best knowledge, it is the first time to propose and demonstrate a dual-path sensor to reduce the false report rate for HR and RR measurements. The results of the Blend-Altman method showed great agreement between our sensor and hospital standard monitor in HR and RR measurements. The independent sample t-test indicates that the HR of cancer patients may be an effective way to judge whether or not they have cancer pain. Our noninvasive dual-path microbend fiber sensor also showed the advantages of an easy fabrication process, simple structure, and low false report rate.

Low-cost real-time fiber optic sensor for intrusion detection

PurposeThe purpose of this paper is to introduce a novel intensity-modulated fiber optic sensor for real-time intrusion detection using a fiber-optic microbend sensor and an optical time-domain reflectometer (OTDR).Design/methodology/approachThe proposed system is tested using different scenarios using person/car as intruders. Experiments are conducted in the lab and in the field. In the beginning, the OTDR trace is obtained and recorded as a reference signal without intrusion events. The second step is to capture the OTDR trace with intrusion events in one or multiple sectors. This measured signal is then compared to the reference signal and processed by matrix laboratory to determine the intruded sector. Information of the intrusion is displayed on an interactive screen implemented by Visual basic. The deformer is designed and implemented using SOLIDWORKS three-dimensional computer aided design Software.FindingsThe system is tested for intrusions by performing two experiments. The first experiment is performed for both persons (>50 kg) in the lab and cars in an open field with a car moving at 60 km/h using two optical fiber sectors of lengths 200 and 500 m. For test purposes, the deformer length used in the experiment is 2 m. The used signal processing technique in the first experiment has some limitations and its accuracy is 70% after measuring and recording 100 observations. To overcome these limitations, a second experiment with another technique of signal processing is performed.Research limitations/implicationsThe system can perfectly display consecutive intrusions of the sectors, but in case of simultaneous intrusions of different sectors, which is difficult to take place in real situations, there will be the ambiguity of the number of intruders and the intruded sector. This will be addressed in future work. Suitable and stable laser power is required to get a suitable level of backscattered power. Optimization of the deformer is required to enhance the sensitivity and reliability of the sensor.Practical implicationsThe proposed work enables us to benefit from the ease of implementation and the reduced cost of the intensity-modulated fiber optic sensors because it overcomes the constraints that prevent using the intensity-modulated fiber optic sensors for intrusion detection.Originality/valueThe proposed system is the first time long-range intensity-modulated fiber optic sensor for intrusion detection.

A comparison of three heart rate detection algorithms over ballistocardiogram signals

Heart rate (HR) detection from ballistocardiogram (BCG) signals is challenging because the signal morphology can vary between and within-subjects. Also, it differs from one sensor to another. Hence, it is essential to evaluate HR detection algorithms across several datasets and under different experimental setups. In this paper, we studied the potential of three HR detection algorithms across four independent BCG datasets. The three algorithms were as follows: the multiresolution analysis of the maximal overlap discrete wavelet transform (MODWT-MRA), continuous wavelet transform (CWT), and template matching (TM). The four datasets were obtained using a microbend fiber optic sensor, a fiber Bragg grating sensor, electromechanical films, and load cells, respectively. The datasets were gathered from: a) 10 patients during a polysomnography study, b) 50 subjects in a sitting position, c) 10 subjects in a sleeping position, and d) 40 subjects in a sleeping position. Overall, CWT with derivative of Gaussian provided superior results compared with the MODWT-MRA, CWT (frequency B-spline), and CWT (Shannon). That said, a BCG template was constructed from DataSet1. Then, it was used for HR detection in the other datasets. The TM method achieved satisfactory results for DataSet2 and DataSet3, but it did not detect the HR of two subjects in DataSet4. The proposed methods were implemented on a Raspberry Pi. As a result, the average time required to analyze a 30-second BCG signal was less than one second for all methods. Yet, the MODWT-MRA had the highest performance with an average time of 0.04 s.

A New Approach for Detecting Sleep Apnea Using a Contactless Bed Sensor: Comparison Study.

BackgroundAt present, there is an increased demand for accurate and personalized patient monitoring because of the various challenges facing health care systems. For instance, rising costs and lack of physicians are two serious problems affecting the patient’s care. Nonintrusive monitoring of vital signs is a potential solution to close current gaps in patient monitoring. As an example, bed-embedded ballistocardiogram (BCG) sensors can help physicians identify cardiac arrhythmia and obstructive sleep apnea (OSA) nonintrusively without interfering with the patient’s everyday activities. Detecting OSA using BCG sensors is gaining popularity among researchers because of its simple installation and accessibility, that is, their nonwearable nature. In the field of nonintrusive vital sign monitoring, a microbend fiber optic sensor (MFOS), among other sensors, has proven to be suitable. Nevertheless, few studies have examined apnea detection.ObjectiveThis study aims to assess the capabilities of an MFOS for nonintrusive vital signs and sleep apnea detection during an in-lab sleep study. Data were collected from patients with sleep apnea in the sleep laboratory at Khoo Teck Puat Hospital.MethodsIn total, 10 participants underwent full polysomnography (PSG), and the MFOS was placed under the patient’s mattress for BCG data collection. The apneic event detection algorithm was evaluated against the manually scored events obtained from the PSG study on a minute-by-minute basis. Furthermore, normalized mean absolute error (NMAE), normalized root mean square error (NRMSE), and mean absolute percentage error (MAPE) were employed to evaluate the sensor capabilities for vital sign detection, comprising heart rate (HR) and respiratory rate (RR). Vital signs were evaluated based on a 30-second time window, with an overlap of 15 seconds. In this study, electrocardiogram and thoracic effort signals were used as references to estimate the performance of the proposed vital sign detection algorithms.ResultsFor the 10 patients recruited for the study, the proposed system achieved reasonable results compared with PSG for sleep apnea detection, such as an accuracy of 49.96% (SD 6.39), a sensitivity of 57.07% (SD 12.63), and a specificity of 45.26% (SD 9.51). In addition, the system achieved close results for HR and RR estimation, such as an NMAE of 5.42% (SD 0.57), an NRMSE of 6.54% (SD 0.56), and an MAPE of 5.41% (SD 0.58) for HR, whereas an NMAE of 11.42% (SD 2.62), an NRMSE of 13.85% (SD 2.78), and an MAPE of 11.60% (SD 2.84) for RR.ConclusionsOverall, the recommended system produced reasonably good results for apneic event detection, considering the fact that we are using a single-channel BCG sensor. Conversely, satisfactory results were obtained for vital sign detection when compared with the PSG outcomes. These results provide preliminary support for the potential use of the MFOS for sleep apnea detection.

Nonintrusive heart rate measurement using ballistocardiogram signals: a comparative study

Nonintrusive monitoring and long-term monitoring of vital signs are essential requirements for early diagnosis and prevention due to many reasons, one of the most important being improving the quality of life. In this paper, we present a comparative study using various algorithms, i.e., wavelet analysis, cepstrum, fast Fourier transform, and autocorrelation function for heart rate measurement. The heart rate was measured from noisy ballistocardiogram signals acquired from 50 subjects in a sitting position using a massage chair. The signals were unobtrusively collected from a microbend fiber-optic sensor embedded within the headrest of the chair and then transmitted to a computer through a Bluetooth connection. The multiresolution analysis of the maximal overlap discrete wavelet transform was implemented for heart rate measurement. The error between the proposed method and the reference electrocardiogram is estimated in beats per minute using the mean absolute error in which the system achieved relatively good results ( $$10.12\pm 4.69$$ ) despite the remarkable amount of motion artifact produced owing to the frequent body movements and/or vibrations of the massage chair during stress relief massage. In contrast, the error between the proposed method and the reference signal was very large when other algorithms, i.e., cepstrum, fast Fourier transform, and autocorrelation function, were implemented for heart rate measurement.

Nonintrusive Vital Signs Monitoring for Sleep Apnea Patients: A Preliminary Study

Sleep is a fundamental and vital physiological function. Getting enough quality sleep is necessary to a person’s mental health, physiological well-being, quality of life, and safety. Sleep-disordered breathing, specifically obstructive sleep apnea can result in serious health issues, including hypertension and stroke. The current approaches for diagnosing sleep disorders are burdensome, intrusive, and can affect the patient’s sleep quality. As a result, there is a crucial need for less cumbersome systems to diagnose sleep-related problems. In this paper, we evaluated the capacity of the microbend fiber optic sensor to monitor heart rate and respiration in a nonintrusive manner. In addition, we tested the capacity of the sensor in discriminating between shallow breathing and no breathing. The proposed sensor was compared with the three-channel portable monitoring device (ApneaLink) in a clinical setting during a drug-induced sleep endoscopy. Across all ten patients recruited for our study, the system achieved satisfactory results in the mean heart rate and the mean respiratory rate with an error of 0.55 ± 0.59 beats/minute and 0.38 ± 0.32 breaths/minute, respectively. Besides, the Pearson correlation coefficient between the proposed sensor and the reference device was 0.96 and 0.78 for heart rate and respiration, respectively. On the contrary, the proposed sensor provided a very low sensitivity (24.24 ± 12.81%) and a relatively high specificity (85.88 ± 6.01%) for sleep apnea detection. It is expected that this preliminary research will pave the way toward unobtrusive detection of vital signs in real time.

Study of Wavelength-Dependent Bend Loss in Step-Index Multimode Fiber-Optic Microbend Displacement Sensor

In this article, the wavelength dependence of bend loss in a step-index multimode optical fiber (100 µm core diameter; fused silica) was investigated for fiber bend radii ranging between 2.0 and 4.5 mm using six excitation wavelengths, namely, 337.1, 470, 590, 632.8, 750 and 810 nm. The results obtained from fitting the bend loss measurements to Kao's model and utilizing MATLAB indicate that bend loss is wavelength dependent and transmission loss in multimode optical fibers increases with the decrease in the fiber bend radius. Furthermore, the response of a microbend fiber optic displacement sensor was characterized at 337.1, 470, 632.8, 750 and 810 nm. Measurements obtained from the microbend sensor indicate that the sensor output power is linear with the applied displacement and the sensor output is wavelength dependent.

Sensor data quality processing for vital signs with opportunistic ambient sensing.

Opportunistic ambient sensing involves placement of sensors appropriately so that intermittent contact can be made unobtrusively for gathering physiological signals for vital signs. In this paper, we discuss the results of our quality processing system used to extract heart rate from ballisto-cardiogram signals obtained from a micro-bending fiber optic sensor pressure mat. Visual inspection is used to label data into informative and non-informative classes based on their heart rate information. Five classifiers are employed for the classification process, i.e., random forest, support vector machine, multilayer, feedforward neural network, linear discriminant analysis, and decision tree. To compute the overall effectiveness of quality processing, the informative signals are processed to estimate interbeat intervals. The system was used to process, data collected from 50 human subjects sitting in a massage chair while performing different activities. Opportunistically collected data was obtained from the fiber optic sensor mat placed on the headrest of the massage chair. Using our classification approach, 57.37% of the dataset was able to provide informative signals. On the informative signals, random forest classifier achieves the best classification accuracy with a mean accuracy of 98.99%. The average of the mean absolute error between the estimated heart rate and the reference ECG is reduced from 13.2 to 8.47. Therefore, the proposed system shows a good robustness for opportunistic ambient sensing.

Textile Fiber Optic Microbend Sensor Used for Heartbeat and Respiration Monitoring

This paper reports on a textile fiber optic microbend sensor for heartbeat and respiration monitoring. A section of multimode optical fiber sandwiched between parallel strips acting as a microbender is being integrated onto an elastic substrate. Its design is based on fiber microbending effects. The textile sensor can be used to measure heartbeat and respiration rate simultaneously during standing and sitting position. The detected heart rates from our sensor are in good agreement with that from the commercial SpO2, whereas the respiration rate is verified by counting the breathing manually. We characterize the frequency response of the sensor with a simulation setup and find that the sensitivity of the sensor is large enough at 105 r/min although it decreases with the increase of the motor speed. The textile fiber optic sensor is very comfortable to wear due to the elastic nature of the substrate.

Application of Improved BP Neural Networks Based on LM Algorithm in Characteristic Curve Fitting of Fiber-Optic Micro-Bend Sensor

As a key factor in a testing system, sensor nonlinearity has always been the study focus in the field of engineering and techniques. In order to accurately reflect the practical characteristics of a fiber-optic micro-bend sensor, Levenberg-Marguardt (LM) algorithm is used to optimize the correction of the weight values of standard back propagation neural network (BPNN). The learning process of improved BPNN based on LM algorithm (LM-BPNN) is also illustrated mathematically, and LM-BPNN is applied in fitting the input and output characteristic curve of a fiber-optic micro-bend sensor. The simulation results show that LM-BPNN is superior both in its convergence rate and fitting precision over standard BPNN.

Microbend fiber optic detection of continuously varying refractive index of chlorinated water

In this paper we report a simple microbend fiber optic sensor using a plastic fiber, LED and photodetector assembly for sensing minute variation of refractive index of chlorinated water. Chlorinated water has slightly higher refractive index and gradual release of chlorine from bleaching powder treated water causes a temporal decrease in refractive index of the solution. The evaporation of chlorine from water and the change in refractive index is found to follow a first order exponential decay function of time. Introducing microbends in an optical fiber is easier and less complex than etching of fiber cladding for traditional optical fiber sensors.

Intensity-Modulated Microbend Fiber Optic Sensor for Respiratory Monitoring and Gating During MRI

This paper describes a novel microbend fiber optic sensor system for respiratory monitoring and respiratory gating in the MRI environment. The system enables the noninvasive real-time monitoring and measurement of breathing rate and respiratory/body movement pattern of healthy subjects inside the MRI gantry, and has potential application in respiratory-gated image acquisition based on respiratory cues. The working principle behind this sensor is based on the microbending effect of an optical fiber on light transmission. The sensor system comprises of a 1.0-mm-thin graded-index multimode optical fiber-embedded plastic sensor mat, a photoelectronic transceiver, and a computer with a digital signal processing algorithm. In vitro testing showed that our sensor has a typical signal-to-noise ratio better than 28 dB. Clinical MRI trials conducted on 20 healthy human subjects showed good and comparable breathing rate detection (with an accuracy of ±2 bpm) and respiratory-gated image quality produced using the sensor system, with reference to current predicate hospital device/system. The MRI safe, ease of operation characteristics, low fabrication cost, and extra patient comfort offered by this system suggest its good potential in replacing predicate device/system and serve as a dual function in real-time respiratory monitoring and respiratory-gated image acquisition at the same time during MRI.

Prediction of Force Measurements of a Microbend Sensor Based on an Artificial Neural Network

Artificial neural network (ANN) based prediction of the response of a microbend fiber optic sensor is presented. To the best of our knowledge no similar work has been previously reported in the literature. Parallel corrugated plates with three deformation cycles, 6 mm thickness of the spacer material and 16 mm mechanical periodicity between deformations were used in the microbend sensor. Multilayer Perceptron (MLP) with different training algorithms, Radial Basis Function (RBF) network and General Regression Neural Network (GRNN) are used as ANN models in this work. All of these models can predict the sensor responses with considerable errors. RBF has the best performance with the smallest mean square error (MSE) values of training and test results. Among the MLP algorithms and GRNN the Levenberg-Marquardt algorithm has good results. These models successfully predict the sensor responses, hence ANNs can be used as useful tool in the design of more robust fiber optic sensors.

Comparative analysis of classical and special single-mode microstructured optical fibers as a sensing element for fiber optic microbend sensors

The influence of microbends on a phase shift and attenuation in a classical Corning SMF-28 fiber and in a special microstructured single-mode fiber with a limited number of air-hole rings in the cladding has been investigated. The largest measured phase shift of 750 deg/mm was obtained for the classical fiber at displacement mag- nitude of 117 m. This corresponds to 1.310 �3 change in the effective refractive index of the fundamental LP01 mode in a microbent optical fiber section with length of 24 mm. The phase shift for the investigated microstructured fibers is in 3.9 times less. The cutoff of radiation intensity takes place at displacement magnitudes of 55 and 270 m for the mi- crostructured fiber and for the SMF-28 fiber, respectively. It is shown that the sensitivity of the microstructured fiber to the displacement magnitude is in about five times higher than that of the Corning SMF-28 fiber. © 2009

OTDR Based Fiber Optic Microbend Sensor for Distributed Sensing Applications in Structural Pressure Monitoring

The ability to understand and monitor the distributed behaviour of extended, critical structures is recognized as a matter of increasing importance. Optical fibres offer unique advantages for spatially distributed measurement. An especially important feature is the one dimensional nature of the medium, since this offers unique advantages for spatially distributed measurement. This article describes the principle of operation, the design and performance of a novel single mode fiber based multipoint microbend pressure sensor architecture, which may be utilized in distributed measurement. The actual sensor element is a single mode fiber coupled to the measurand field through the usual microbend inducing structures. The sensor uses optical time domain reflectometry (OTDR) to detect pressure induced charges of backscatter power at many separate locations in the fiber as a function of length along a single fiber with no taps or branches. The sensitivity of this structure to microbend induced losses has been thoroughly characterized. This feature greatly increases the information from a single instrument and hence decreases the cost-benefit ratio.

SMS fiber optic microbend sensor structures: effect of the modal interference

We examine the effect of modal interference on the performance of a single mode–multimode–single mode (SMS) fiber optic microbend sensor structure. The study shows that if the coupling from higher order modes of the sensing multimode fiber to the lead-out single mode (SM) fiber is not zero, the output power and hence the microbend sensitivity of the structure depends strongly on the position of the microbends in the fiber. A simple experiment is carried out to study the above effect whose results agree very well with the theoretical predictions.

Transmission characteristics of SMS fiber optic sensor structures

We examine theoretically the transmission characteristics of the Single mode–Multimode–Single mode (SMS) fiber structures when the spot sizes of the fundamental modes of the single and multimode fibers do not match. It is observed that in such cases, the transmitted power becomes highly sensitive to the wavelength of operation and the length of the multimode fiber used. The study should be useful in the design of efficient fiber optic microbend sensors and novel wavelength filters using SMS structures.

A fiber optic microbend sensor for distributed sensing application in the structural strain monitoring

A fiber optic microbend sensor with an elastic, arched sensing diaphragm has been developed for structural strain measurement. The combination of multiple microbend sensors can form a sensor array for the quasi-distributed sensing application in the monitoring of local strain or deformation along structures, and the optical time domain reflectometry can be conveniently used for interrogation of each sensor unit. The sensor sensitivity can be set at a specific value according to the requirements of the measurement condition. Connected with multiplexed sensing processing schemes, the sensor array may find an application in the real-time monitoring and damage detection of large and critical engineering structures.

Fiber optic microbend sensor for detection of dynamic fluid pressure at gear interfaces

An intensity-based microbend fiber optic pressure sensor has been developed and tested that is capable of detecting the dynamic fluid pressure between spinning gears. The microbend response of various fibers was measured in order to select the best fiber for the application and to determine the optimum deformer periodicity. The sensing fiber was embedded into the root of a modified gear, using a deformer method based on the compression of silicone rubber under pressure. Embedded gear sensors were calibrated under static pressure to 100 psi, yielding consistent results with different sensors. Gearbox tests demonstrated successful detection of dynamic fluid pressures at gear interfaces, and the ability to perform in a highly rugged environment.