Fiber-optic smart textiles for biophysical real-time measurement of breathing pattern, blood pressure, body temperature

  • Molardi, Carlo (PI)
  • Tosi, Daniele (CoI)
  • Selleri, S. (Other Faculty/Researcher)
  • Perrone, Guido (Other Faculty/Researcher)
  • Schena, Emiliano (Other Faculty/Researcher)

Project: Research project

Call title (Call ID)

Faculty Development Competitive Research Grant Program 2018-2020

Project Description

The aim of FOSTHER project is the development and validation of a wearable smart textile technology, based on an array of optical fiber sensors, for real-time continuous monitoring of biophysical parameters, which include: breathing pattern, blood pressure, and body temperature. The goal is to obtain a wearable fabric integrated with a set of fiber optic sensors arrays, and a portable interrogation unit provided with wireless data transmission, capable of recording and processing data coming from the set of fiber optic sensors (FOS). The interest in smart textiles and wearable sensors, comes from several reasons, which can be summarized in:
1. Continuous monitoring. There is a generally growing availability of low-cost miniature technologies, together with sensor network devices such as Arduino boards, dataloggers, memories for data storage, and wireless transceivers based on modern networking protocols such as wi-fi, Zigbee, or Dash7. This advantageous technological environment leads the main conjecture that the wider is the availability of biophysical and biological parameters under monitoring, the higher is the effectiveness of healthcare in terms of prevention of diseases and treatment of current conditions. Minimal invasiveness continuous monitoring can be, not only, fundamental in infants, for preventing Sudden Infant Death Syndrome, or in elderly people, to prevent heart-related diseases, but also greatly helpful to assist athletes for reaching optimum performance.
2. Personalized medicine, including personalized drug delivery (PDD). The effectiveness of therapies may differ according to the genetic profile of patients. Different responses to therapies from each organism can be monitored with sensors, which can lead to the identification of the optimal therapy for each patient. Although PDD is mainly a genomic study, monitoring biophysical parameters can be extremely helpful. As an example, it is the possible to identify drugs effectiveness in reducing the overall blood pressure.
3. Remote healthcare. The high cost of hospital-based diagnostic, through the whole hospitalization cycle, suggests transferring as more as possible the effort for simple diagnostic and data-logging operations outside of hospitals, and digitalize as much as possible the diagnostics. Remote healthcare has been developed and successfully implemented in several cases: examples are local communities with no hospital access.
The mentioned motivations, analyzed in a more synergic perspective, represent one of the fundamental goal in the improvement of modern healthcare system. Such a goal, which is pursued by international public health agencies, is focused on treatment customization, with less invasive impact on patients. This can be obtained by reducing hospitalization in favor of remote healthcare, with additional benefits related to the reduction of infrastructures cost. This also represents one of the objective mentioned in the 2050 Strategy plan of Kazakhstan government.
A study of IDTechX [IDTechX – 2014] shows that revenues for wearable technologies are on the trajectory to grow from $14B market (2014) to $70B market by 2025, overpowering most of the “external” technologies.
Wearable technologies are now-a-day mainly addressed by MEMS technologies, particularly when operated with organic electronics. FOS, however, have critical advantages for operation in smart textiles, compared to standard MEMS technologies. They are passive devices, fire-safe, immune to electromagnetic radiation (and therefore MRI-compatible). They are biocompatible, compact in size and light weight (an optical fiber has a typical thickness 0.2 mm including the protective coating). They offer high precision, with the possibility of enabling multiplexed sensing, in fact several sensors can be fabricated on a single fiber realizing several sensing points. This latter configuration is a key asset unique for optical fiber technologies: using fiber Bragg gratings (FBGs), the most popular type of sensor [Kersey – 1997], it is possible to implement the so-called wavelength division multiplexing (WDM). In WDM, each FBG sensor inscribed in different position inside the fiber, reflects one wavelength. The overall reflection spectrum shows the combination of all the FBG sensors, each of them identified by its Bragg wavelength. The Bragg wavelength of each sensor depends on strain and temperature, according to a linear relationship (1 pm/micro-strain, 10 pm/K for a standard grating). Using a broadband spectrometer, paired with a broadband light source emitting over the third optical window, it is possible to interrogate up to 40-50 FBGs in a single array.
The idea of this project is to embed an array of 40 sensors, designed to match the lengths and the sensing regions under investigation, in a smart textile. The smart textile will be designed to monitor biophysical parameters in real time, using a portable interrogation setup. Data will be acquired and transmitted via Zigbee, making the device operative as a smart textile but with the critical advantages of miniature invasiveness, MRI-compatibility, and high-precision sensing.
State of the art
Smart textiles, or e-textiles, are clothing or fabrics which enable digital operations such as sensing and monitoring, energy harvesting, and computing. However, sensing is the main area of research, particularly for monitoring of biophysical and biological parameters.
The genesis of modern research on fiber optic sensors (FOS) for smart textiles is in the context of the European OFSETH project [Ofseth – 2006]. This project allows only optical sensing technologies to monitor vital parameters such as respiratory rate, cardiac rate, and pulse oxymetry, mainly during MRI. The project aimed at the development of devices for respiratory detection, having fibers embedded within the yarns in two specific points. The key reason of the project is that, under MRI, standard sensing technologies such as transistors, accelerometers, and other electrical devices are banned [Witt – 2012].
The team developed two sensors, both for strain detection: (1) an FBG (fiber Bragg grating) sensor embedded into an elastic textile; (2) a macro-bending sensor via OTDR (optical time-domain reflectometry). The two sensors have been combined into a harness, MRI-compatible, that allows for measurement of both thoracic (FBG) and abdominal (macro-bending) respiration.
The principle of operation of respiratory sensors is simply to convert breathing movements into strain, which is easily detectable. Most of the complication comes from the embodiment of the whole electronics in a wearable and battery-powered device: therefore, typical architectures are based on single-wavelength detection with a laser source, or portable spectrometry. Often, the system acts as a first-responder unit. Even when sensing is performed alongside an extended active length, the unit integrates all the spatial information, usually displaying a respiratory chart as in [Witt – 2012]. In the works presented so far, strain has always been detected over an extended length, and then processed as an individual data. More advanced features may in the future be enabled by spatially resolved sensors, which however are not miniaturized to a wearable format, and to date can only be used as external units limiting patient’s mobility.
On the other side, some emerging applications are starting to appear. The work from Li et al. [Li – 2012] is concerned with temperature detection, and is presented as an intelligent cloth for early detection of high body temperature in fever. In this application, accuracy is the dominant requirement, and the authors have expanded the accuracy of a standard silica FBG by using a polymer coating: with the proposed packaging, the sensitivity is 150 pm/C is achieved, 15 times higher than standard FBG, leading then to the hundredth of C accuracy. On the other hand, the polymer package is not atoxic, due to the use of naphthenate and methyl ethyl in the compound. However, packaging is low-cost and suitable for integration with the clothing.
Li et al. provided a methodology for embedment of FBG into woven fabrics; a small half-cylindrical roll with the FBG is covered by woven fabrics, creating a structure that can propagate heat from the body to the sensor.
In 2015, the first smart textile for biochemical detection has been proposed by Esmaeilzadeh et al. [Esmaeilzadeh – 2015], achieving a true milestone in this research. The study reports the sensor design, and its integration into wool fabrics. The working principle is in-fiber surface plasmon resonance (SPR). The sensor detects humidity, and is mainly addressed to detection of condensation and water evaporation.
To date, we can conclude that the operation of traditional fiber-optic sensing (FOS) technologies is demonstrated; however, several drawbacks prevent their applications into smart textiles. At first, albeit fibers exhibit a minimum invasiveness, their interrogation system does not: usually interrogators are assembled in an encumbering and heavy format, making it impossible to carry on an arm (such as a pressure Holter, well established in medical practice). Some compact formats are available, but they use a single-wavelength principle with a laser (usually in a miniature TO-28 package) and a photodiode: this however does not allow the interrogation of multiple sensors, using the wavelength division multiplexing (WDM) that is really established in current FBG sensing networks.
The co-PI, and the collaborators, has accomplished relevant groundwork in this area. In first place, the establishment of FBG sensing technology, for bio-sensing and biomedical application with advanced technological solutions, has been one of the primary research areas in the field. [Candiani - 2013] [Schena – 2016] [Tosi – 2014]. Furthermore, the co-PI has developed and optimized interrogation techniques, based on signal processing, that can estimate extremely small variations of the FBG spectrum even in disadvantageous signal to noise ratio (SNR) conditions [Tosi – 2015-1], [Tosi – 2015-2].
Finally, the Biomedical Campus of Roma, has established the preliminary design of a smart textile limited to 6-point breathing analysis [Massaroni – 2016]. This device makes a partial use of WDM, and can be used as the starting point for investigating the embodiment of optical fibers into smart textiles; however, it is applied to a limited set of points, with an only partial compensation of temperature. In addition, the interrogation device is not portable.
Scientific proposal
In FOSTHER, we aim at the development of a novel smart textile based on optical fibers. In our vision, the smart textile needs to satisfy three sensing tasks, which have an immediate application for clinical use. These tasks are accomplished with the FBG sensing network,
(1) Measurement of multi-point breathing pattern. Respiratory monitoring is essential in different medical fields. Patient’s ventilation can be monitored by accurate and continuous collection of breathing parameters like the breathing rate and the tidal volumes. Monitoring of these parameters during basic lung function tests can help identify abnormal ventilation patterns, obstructive and restrictive diseases affecting the respiratory system. Since the lung displacement results in displacements of the chest wall, the measurements of thoraco-abdominal surface movement can be used to estimate not only the lung volume changes but also the contribution of the rib cage and the abdomen to the lung volumes with high accuracy. The study of the volume of the three compartments - pulmonary rib cage, abdominal rib cage, and abdomen - in which the chest wall can be functionally divided and the analysis of how the interactions between chest wall compartments affect the global volumes can highlight abnormal pattern of the breathing as well as atypical biomechanics behavior of the chest wall. Respiration, from the sensing point of view, is converted into longitudinal strain, which can be detected via FBG upon a proper mount that allows the FBG to be bent during the respiratory cycle [Massaroni – 2016].
(2) Measurement of body temperature in several points: body temperature is an important vital sign, and its management is a key asset in preventing Sudden Infant Death Syndrome, among others. We aim at performing the body temperature measurement in several parts of the chest and the torso, and to have one sensor placed in correspondence of each strain sensor used in breathing pattern analysis. This enables compensating the breathing sensors for temperature variations, which is essential in precision sensing. Notably, we need to incorporate the body temperature sensors within the smart textile, thus the sensor themselves will be only partially capable of detecting body temperature; for this task, we will take advantage of an additional set of sensors, externally placed, which will allow compensating for the external temperature. The study presented by Li [Li – 2012] allows estimating the percentage of heat that is transferred from the body to the textile, which ranges from 8% to 32%.
(3) Central arterial blood pressure: The study from Leitao [Leitao – 2016] shows a method for central arterial blood pressure (BP) measurement carried out with FBG sensors. The probe mounts an FBG on the tip, and the transductor can convert the small displacement due to the pressure pulses into a strain, detectable by the FBG.
The goal is the integration of 2 BP sensors into our architecture: one sensor will be based on an FBG, and the fiber will travel in and out of the probe; the second sensor will terminate the FBG array. By using FBGs fabricated with the drawing tower method, we obtain a sensor inscribed in a bend-insensitive fiber, which can bend without losses on very narrow curvature radii (~2 mm). The probe, developed as in the proposed study, completes the smart textile design. In the first place (work-package 1), all the sensors will be individually tested, understanding their calibration properties: the tasks to address include the position and the strain sensitivity (in terms of breathing amplitude to strain transduction) of the strain sensor; amount of temperature transfer from the body temperature to the temperature sensors, and evaluation of the position of the external temperature sensors; position of the BP sensors and their sensitivity. Sensors will be arranged at first individually, and then altogether to form a single array; Fig. 5 shows the preliminary design of the textile. This task will come as an addition to the smart-textile design, with the possibility to increase its potential in biomedical diagnostic, particularly for continuous remote monitoring.
The design includes up to 40 sensors: respiratory sensors (blue); body temperature sensors (red), used also to compensate for temperature variations on respiratory sensors; external temperature sensors (green); BP sensors (yellow). The design is shown on a body picture, but in the practical implementation all sensors will be implemented within the fabric of a dress designed in accordance to the specifications in [Massaroni – 2016].
The second work-package involves the development of an interrogation unit. The WDM design, standardized as in [Tosi – 2014] [Kersey – 1997] will be used: each grating, having 2 nm spacing between each Bragg wavelength, is detected with a setup based on a broadband light source (Exxalos EBD series with control board, 1510-1600 nm), a 3-dB optical coupler, and a miniature spectrometer (Ibsen I-MON-OEM). The whole setup will be arranged in a portable format, using off-the-shelf OEM devices and in accordance to a low-cost criterion. The spectrometer will be controlled with a program developed in C on Raspberry, that will: (1) read the data out of the spectrometer, i.e. the spectrum of the whole sensors array; (2) divide the spectrum in blocks, and for each block use the processing described in [Tosi – 2015-1] to estimate the wavelength shift; (3) transmit data via Zigbee to an external server. The server will then perform the signal processing operations, including the temperature compensations, and the wavelength shift conversions, estimating then the final parameters and storing them for the analysis. It is essential that the interrogator is portable, but at the same time performs the spectral analysis, and for this reason we resort to well-established devices suitable for miniaturization. A previous version of a similar interrogator was developed by the co-PI at University of Limerick [Poeggel – 2015]. In the third work-package, we will work on the textile that embeds the sensor. The activity has the tasks of both maintain the sensors positioning in the textile and preserve the sensitivity, and on the other side guarantee the wearable form factor and the minimum invasiveness. It is also important to evaluate the artefact effect introduced by the textile, as opposite to the “naked sensors” format.
Project validation will be performed in a sequence of steps; at first, we will develop at NU a test chamber that allows to vary pressure and temperature simultaneously, while the textile is inflated and deflated at an arbitrary rate to simulate breathing. Sensors will be tested individually, and then altogether.
Tests will be then performed in a real-case scenario, whereas a more realistic representation of real conditions will be implemented. Initially tests will be performed indoor, to operate with minute variations of ambient temperature; only at later stages, we will aim at outdoor sensing and evaluate its performance. Log tests will be also performed.
Effective start/end date3/20/1812/31/20


Blood pressure
Time measurement
Fiber optics
Fiber Bragg gratings
Fiber optic sensors
Temperature sensors
Smart textiles
Wavelength division multiplexing
Magnetic resonance imaging
Optical fibers
Pressure sensors
Sensor arrays


  • Optical Bio-sensing
  • smart-texile