Sri Venkata Surya Teja Jonnalagadda, Durga Prasad Mishra, Santanu Kumar Behera
©SHUTTERSTOCK.COM/JACKIE NIAM
Radio-frequency identification (RFID) technology is prominent in detecting and tracking objects using low-power wireless transmissions. By integrating sensing and identification functions into the RFID reader/interrogator, the system can be capable of monitoring vital parameters, such as temperature, blood pressure, heartbeat, glucose content, the information of individual patients, and so forth in real time. It is also critical for the younger generation besides the elderly to pay attention to vital signs monitoring for diseases, such as cardiac arrest, myocardial infarction, sleep apnea, and tachypnea. Conventional vital signs monitoring methods like sophisticated anesthesia machines, in which different systems are integrated to monitor a patient’s heart rate, blood pressure, oxygen saturation, and temperature, are intrusive in nature and cause inconvenience to the users since more dedicated sensors need to be worn. For the enabling of continuous and comfortable monitoring of vital signs, chipless RFID is the best-suited technology because of its tremendous optimization in hardware, lower cost, ease of design, and installation. This article presents various noninvasive methods of monitoring vital signs, like sleep apnea, heart rate, respiration rate, body temperature, and posturography with the help of chipless RFID technology. The article discusses literature related to vital signs monitoring with chipless RFID sensors, smart-sensing materials, and their classification and applications. Chipless RFID data coding techniques like frequency shift coding and hybrid coding are also discussed. Furthermore, some recently published review articles are compared with the proposed article, showing the multifarious features.
A conventional wireless sensor network (WSN) consists of components like an RF transceiver module, a sensor, a microcontroller, and a power source like a battery for supplying continuous power to the sensor, which helps in the continuous operation of long-distance communication. The sensor used in WSN senses real physical parameters, like light, pressure, humidity, and temperature. The presence of a power source in WSN makes the network complex and possesses some maintenance problems, which also decreases the life span and operating temperature range of the nodes present in the network. The problems that are present in traditional Wi-Fi networks can be overcome by chipless RFID sensors. A typical chipless RFID system includes a tag, reader, and middleware, which can be either assimilated with a reader or separately installed with the required software in the user’s desktop that reads and manipulates data to and from the reader. The reader and accessories are controlled by the middleware. The reader supplies power to the tag by scattering electromagnetic (EM) energy. The reader collects information from the tag and sends it to the middleware.
Different kinds of reader architecture and their working procedures are elaborately discussed in [38]. In [38], the authors categorized the RFID reader into three types based on the reading principle. The categorized types are frequency-domain chipless readers, time-domain chipless readers, and hybrid chipless RFID readers for higher-order encoding techniques. A frequency-domain chipless reader uses a series of continuous waves, such as frequency-modulated continuous wave that consists of different frequencies in the ultrawideband (UWB) range. A time-domain chipless reader emits a short-duration RF UWB interrogation signal. The performance of the time-domain chipless reader is superior to that of the frequency-domain chipless reader. In the case of a hybrid chipless RFID reader, only a phase and polarization control unit is added in addition to the frequency-domain reader architecture. The complexity of the hybrid chipless RFID reader is high in comparison to frequency and time-domain readers. A typical reader is a transceiver that consists of three important and typical parts, named antenna, an RF section, and a control section or a digital section. The reader antenna transmits an interrogation signal from the reader to the tag and it receives the backscattered signal from the tag and passes it to the reader. The design of the reader antenna is also a crucial task because it has to be suited for the better detection of the tag in any environment.
Various RFID reader antenna designs are presented in [39], [40], and [41]. In [39], the authors proposed a circular patch antenna with dual-band circular polarization (CP) at ultrahigh frequency (UHF)-RFID/wireless local area network (WLAN) for RFID readers. The antenna structure has two perpendicular slots on the patch surface and four slits on the ground plane that help to achieve dual-band operability and CP at both bands, specified as the UHF-RFID (915 MHz) and WLAN band (2.45 GHz). The designed antenna has compact dimensions and is fabricated using an FR-4 epoxy substrate. In [40], the authors presented a compact circularly polarized slot antenna for UHF-RFID reader applications. The antenna is coplanar waveguide-fed by an L-shaped feeding line. Two L-shaped strip lines are placed in the circular slot of the ground plane to get good impedance matching and broadband CP operation. In [41], the authors designed a combination of loop and dipole antennas into a Yagi-like structure to be implemented as a wearable antenna that is used as an RFID reader antenna.
The RF section in the reader consists of components like low noise amplifiers, filters, mixers, power dividers, and gain or phase detectors. This RF section carries two subsets of components that are responsible for transmitting and receiving the interrogation and backscattered signal, respectively. The control or digital section present in the reader consists of components like analog-to-digital converters, digital-to-analog converters, microprocessors, and memory. The transponder or tag acts as an identification device that is affixed to the body of the tracked object. The tag that is attached to the object surface should be read from any orientation with respect to the reader. It is not possible to read the tag unless and until it is an orientation-insensitive tag. Orientation insensitivity is an important attribute that affects the performance of the detection of tags. Orientation insensitivity is the ability to read the tag from any orientation with respect to the reader. The attribute of orientation insensitivity can be incorporated into the chipless RFID system in two ways: by designing orientation-independent tags or using suitable reader architecture that can read the tag in any orientation. In [44], the authors proposed an orientation-insensitive and normalization-free reading chipless RFID system based on CP interrogation. In this method, CP is used to filter out the reflections from the background other than that from the tag. This CP-based reading approach guarantees tag detection irrespective of orientation. In [45], the authors designed cross-polar resonators and unit cells that give similar resonating responses irrespective of the orientation angle. In that article, the authors designed strip coupled line resonators that are arranged in a triangular fashion, and flower-shaped resonator unit cells. The above designs are measured and the performance of detection at rotation angles of 45°, 135°, 225°, and 315° in the roll axis is verified. In [46], chipless RFID reader classification and different commercially available RFID readers are presented.
RFID systems are generally classified into passive and active types. In the active type, a battery unit is integrated with a tag that acts as a power source to the tag, unlike in the passive type, where the tag makes use of the EM energy supplied from the reader and backscatters the identification information to the reader. The basic differences between chip-based RFID and chipless RFID are presented in Table 1. Although chip-based RFID has the advantages of signal processing capability, noise immunity, and long read range, the cost of chip-based RFID increases. Chipless RFID uses low-cost substrates and doesn’t require any maintenance, unlike chip-based RFID. Noise cancelation algorithms and other signal-processing techniques can be done at the reader side in a chipless RFID system. Because of the outstanding features of chipless RFID, the focus of this article is shifted toward it.
Table 1. Comparison of chip-based and chipless RFID.
The typical structure of the chipless RFID system is presented in Figure 1. Because of our interest in health-care monitoring, recent technologies like anesthesia machines provide wireless sensing of vital parameters, like heart rate, respiration rate, and temperature accurately, but these methods have their limitations, like the restricted movement of the patient, limited operating range, and inability to differentiate multiple signals. Chipless RFID sensors overcome these challenges faced by Wi-Fi networks in the case of noninvasive vital signs monitoring. Chipless RFID technology is superior to the above-described methods because of its low cost, long life, less weight, less radiative, and compact structure. Other unique characteristics of RFID are multiple signal detection from different tags, absence of chips, large operating range, and no requirement of line of sight for communication. The low-cost feature of RFID can be explained by the ease of design of the tag with the absence of a ground plane or structure and the absence of an application specific integrated circuit (ASIC) chip. Since there are no maintenance problems, RFID tags will be long-lasting. Because of the frequency and hybrid coding techniques, multiple detections of signals from different tags are possible in RFID technology. Coding capacity is improved by the hybrid coding technique, which is presented in [3]. Chipless RFID tags of passive nature that are pertinent to the planar technology have cut down fabricating and other costs. In significant real-time applications, including medical, military, health care, commercial, packaging, and food safety, they play a significant role. Passive sensors have outstanding qualities, including perfect blending with garment materials, continuous monitoring, increased longevity or durability, environmental friendliness, and affordability. Additionally, chipless sensors can respond precisely under challenging conditions when chip-based RFID sensors are limited by the usage of ASIC chips. Without using an active component like an ASIC chip, the RFID sensor tracks, recognizes, and gathers data of interest from a distantly located device. Chipless sensors differ from chip-based sensors in appearance since an ASIC chip is absent. Different chipless sensors, which are used in sensing different physical parameters, their frequency ranges of operation, materials used for fabrication, and their applications are presented in Table 2.
Figure 1 . Basic block diagram of a chipless RFID system.
Table 2. Chipless RFID sensing materials used in different applications.
There is not much difference between an RFID tag and an RFID sensor. The tag is used for tracking and identification of an object with which the tag is attached, whereas the sensor supplies the physical information of the object and its environment or surroundings by modifying the properties of the EM signal that the tag receives from the reader. Therefore, tags and sensors can be used interchangeably in the literature. There will be a pair of resonators that are printed on the sensor, of which one is responsible for generating identification responses and the other one is for generating information about sensing parameters. In the case of sensing application, whenever there is a physical parameter variation, the structural variation of the resonators present on the sensor takes place, by which the frequency information of the sensing parameter differs, whereas the frequency information of the identification doesn’t change since the resonators that are responsible for identification purpose don’t undergo structural variations.
An EM signal is transmitted by the reader toward the sensor or tag. The sensor backscatters the unique ID of the tag and sensed data. The sensor converts the physical parameters—like heart rate, respiration rate, blood pressure, and temperature—into EM properties with the help of resonators present on the sensor and by EM characterization of materials used for sensor design. The properties of the backscattered EM signal are dependent on the conductivity, quality factor (Q-factor), radar cross-section (RCS), and other factors. The backscattered EM signal is modified due to the change in EM characteristics of the sensing material, like loss tangent, dielectric constant, Q-factor, conductivity, and change in the resonator’s physical footprint. The information transferred by the tag can be encoded in two different ways: time-domain approach (TDA)-based and frequency-domain approach (FDA). In the TDA method, the identification is done based on the delay produced by the tag. The TDA-based tags are power efficient and more compact in nature. In the FDA method, the identification of the tag is done by decoding the resonant peak information. The frequency domain-based tags can achieve higher bit capacity. In frequency domain-based tags, the information can be encoded as “0” in the absence and “1” in the presence of resonators, but to achieve high coding capacity we have to use more resonators in the tag, which is space-consuming.
Resonators can enhance the number of bits with compact dimensions. Split ring resonators and fractal shape resonators can provide higher bit coding capacity with compact dimensions. In [2], the authors explained how resonating structures like the split ring and fractals can improve the bit capacity and compactness of an RFID tag. The higher the bit capacity, the higher the information rate. In a vital signs monitoring scenario, several vital signs of a patient are to be monitored simultaneously. To achieve this, higher coding capacity is helpful. With higher bit encoding more tags can be installed in a small environment in which each tag can be differentiated from other tags accurately. The capacity of the coding is depended on the physical footprint of the resonators placed in the tag [3]. The sensing information sent by the tag to the reader can be affected by noise from the surrounding environment. Therefore, the phase encoding of the tag overcomes this drawback. To improve the coding efficiency and noise immunity we can use both frequency and phase encoding. Also, the hybrid coding technique is proposed in [3]. In much of the existing initial literature, the coding is done as the presence and absence of the resonators. The presence of the resonator is coded as a bit “high” and the absence is coded as a bit “low.” But this type of coding includes more resonators needing to be placed on the tag, which reduces compactness. At the advanced level, the coding is done by changing the frequency position of the resonators. Each peak is coded as a different code based on the number of peaks produced by a particular resonator. If we can incorporate more parametric changes like magnitude, phase, or Q-factor of a resonator, then a higher number of combinations can be achieved. The gap between the resonators can also be changed for obtaining good coding efficiency in terms of phase or frequency shift. As the article focuses on the frequency coding of the tag, the data encoding of the tag using the frequency-modulated method is explained in a later section.
The proposed article can be multifarious in different aspects in comparison to the recently published article. In this article, RFID is proposed as a dominating technology that can be employed for the Internet of Things. Several readers, tag structures, printing, fabrication techniques, and applications in several fields are discussed. Physical RFID sensors are used to sense physical parameters, like temperature and humidity. Smart packaging solutions are provided with the help of RFID technology that tracks the changes in the contents of the package. The idea of smart-skin is discussed in the scenario of structural health monitoring.
The applications of chipless RFID sensors in food packaging were discussed earlier by several authors in their articles. Several types of sensing materials, like pH, gas, humidity, and temperature-sensitive materials are presented. The potential of chipless RFID sensors in food packaging applications is discussed. Temperature-sensitive materials like phenanthrene, ionic plastic crystal, stanyl polyamide, and alumina are investigated for chipless RFID suitability. In [19], the authors described RCS-based chipless tag usage for relative humidity (RH) monitoring of packaged food products. The authors used a dual-band, dual-polarized annular slot ring chipless RFID tag for moisture sensing in food products. In [20], the authors proposed a way of RH sensing with the help of a dual-polarized keratin-based UWB chipless RFID sensor. The designed biocompatible, compact, and robust keratin biopolymer-based chipless RFID sensor is used to sense RH. Keratin is an excellent biocompatible material that is sensitive to moisture and is appropriate for usage in noninvasive humidity sensors. In [21], the authors tried to monitor both temperature and humidity using a chipless RFID sensor. There is a similar effect on resonant frequency when there is a variation in temperature and humidity, hence the authors tried to integrate them into a single sensor. The maximum backscattered energy at a resonant frequency, f for a loop resonator is given by: \[{f}\left({T},{RH}\right) = \frac{c}{{2}\sqrt{{\in}_{\text{eff}}\left({T},{RH}\right){L}\left({T}\right)}} \tag{1} \] where c is the speed of light, ${\in}_{\text{eff}}\left({T},{RH}\right)$ is effective permittivity, and L(T) is the effective length of the loop resonator.
In [22], the authors provided a review of chipless RFID measurement and response detection methods. Measurement quantities like S-parameters and RCS based are compared. In [23], the authors presented an RFID approach to sense the distance based on a planar spiral resonator passive tag and a probing loop using an FR-4 epoxy substrate. In [47], the authors classified the RFID sensors and their applications in different domains. By comparing the above review articles, the proposed article provides several approaches to monitor vital signs in terms of physical parameters, like temperature, respiration rate, and heart rate with the help of chipless RFID sensors. This article discusses how vital signs are monitored with the help of chipless RFID sensor technology in the “Vital Parameters and Their Monitoring Techniques Using RFID Sensors” section.
This article is organized into six sections. In the “Chipless RFID SensorTechnology” section, an introduction to chipless RFID technology is presented. A comparison of traditional Wi-Fi networks with RFID is discussed and unique characteristics of chipless RFID are mentioned. In the “Data Encoding Using the Frequency Domain Approach in Chipless RFID Sensors” section, data encoding of the tag in frequency domain-based tags is explained. In the “RFID Printing Technologies for Vital Sign Monitoring” section, several RFID printing technologies for vital signs monitoring are discussed. The next two sections describe smart materials for vital signs monitoring and vital parameters and their monitoring techniques, respectively. The “Challenges and Future Directions for Vital Signs Monitoring” section presents the challenges and opportunities of RFID.
Data encoding will be done at the reader side according to the presence and the absence of the resonant peaks in an RCS plot. Structural variations in the resonators produce resonant peaks that will be used in coding, also called structural coding. In the initial literature, coding is done with the presence and absence of resonators. Directly, the presence of the resonator produces a corresponding peak in the RCS plot. If the resonator is removed, then the corresponding peak is not produced in the RCS plot. The higher the coding capacity of the tag, the higher the data rate. Hence, to achieve a higher data rate with this type of coding, more resonators need to be present on the tag, which will affect the compactness of the tag. To meet the needs of the ever-increasing hunger for a higher data rate, high-bit capacity tags need to be designed and deployed in retail and other commercial applications. Hence, other types of coding techniques, like frequency shift coding (FSC) and hybrid coding, are used to improve the coding capacity of the tag [24]. In [24], the authors presented a hybrid resonator-based RFID tag design that has a bit capacity of 10 b. Similarly, in [35], the authors introduced RCS magnitude level coding through which the tag design attained a bit capacity of 13 b.
In FSC, by modifying the resonating structures, we can shift the resonant peaks in the RCS by which coding capacity can be improved. For example, if the resonant peaks in Figure 2 are coded as 101010, by modifying the resonating structures we can shift the resonant peaks and the resultant code is 010101, as represented in Figure 2. In phase coding, we can make use of phase information to add another attribute to code the tag. By modifying the resonators there will be a change in the phase of the RCS. So, by capturing the phase information we can do phase coding of the tag. Hybrid coding makes use of both FSC and phase coding by which the coding capacity of the tag is improved. In the case of the windowing technique, a particular window is designed for a resonating peak in the corresponding frequency range. To code the peak as “1” we have to pass it through the window for the corresponding frequency range. In [36], the author discussed various sensors and classified them according to the intrinsic parameter, like effective permittivity, effective length, and effective coupling. With the help of effective permittivity, variation in the physical parameter is tracked with the help of an RFID sensor. In [37], the authors presented an RFID sensor for crack detection based on the attribute of the effective length of the RFID sensor. As the effective length of the resonator present on the sensor varies, the frequency information produced by the backscattered signal also varies, which is given by: \[{f}_{r} = \frac{c}{{2}\left({L} + {2}\Delta{L}\right)\sqrt{{\varepsilon}_{r}}} \tag{2} \]
Figure 2 . Frequency shift coding representation.
where L is the effective length of the resonator placed on the tag or sensor.
Different from the intrinsic parameters, if the sensor makes use of multiple substrate layers or different elements, then there will be the effect of coupling by which the sensing of the physical parameter is carried out. A wide variety of printing technologies are available in the market. It is more important to know about printing technologies, so in the next section, various printing techniques are explained [1].
RFID technology has not yet replaced optical barcode technology on a commercial scale in real-time applications. The main reason behind this is the cost of RFID printing and the ability to print directly on objects. It is challenging to print cost-efficient and directly printable RFID tags. In recent years, some RFID printing technologies have overcome the shortcomings given above. New cutting-edge technologies in RFID printing can produce flexible RFID tags, which can offer an additional attribute of wireless sensing of the physical parameters that optical barcodes are not capable of. We have to consider the different effects of the printing technology that we are employing in printing RFID tags.
Choosing the correct printing technology provides low-cost, accurate responses, as desired. Identifying the substrate for a particular application also proved to be significant in defining the radiative properties of the tag designed. The substrate materials that we choose can detect variations in vital signs, like temperature, heart rate, and respiration rate, based on the EM properties. When multiple substrates are used, we have to take into account the dielectric properties of the substrates used in calculating the resonant frequency. The parameters that affect the radiative properties of the RFID tag are the conductivity of the ink used in fabrication, dielectric constant, loss tangent, thickness of substrate, substrate type, and the number of layers used. In printing technologies, ink is used, which is composed of three components: silver, a polymer, and a solvent. Increasing the amount of conductive ink increases the conductivity of the tag [4], at the cost of reduction in bandwidth and also increases the cost of fabrication. The impact of conductivity on the bandwidth is presented in Figure 3. Some other alternatives to silver—like screen, flexo, and gravure—with good conductivity can be used to reduce the cost of printing. There are similar effects of the parameter dielectric constant, loss tangent, substrate thickness, and multiple layers of the substrate on the bandwidth of the tag. As the thickness of the substrate decreases gradually, bandwidth at resonance also decreases [4], which is presented in Figure 4. The impact of the dielectric constant on bandwidth is explained in [4], and is presented in Figure 5.
Figure 3 . Impact of conductivity on bandwidth [4]. PEC: perfect electric conductor.
Figure 4 . Impact of substrate thickness on bandwidth [4].
Figure 5 . Impact of relative permittivity on bandwidth [4].
The classification of printing technologies is presented in Figure 6. Different types of printing techniques available are inkjet printing, doctor-blading, thermal (heat) printing, screen-based printing, gravure printing, aerosol jet, and thin film. Inkjet printing, unlike conventional manufacturing processes, makes use of additive manufacturing, which provides material extrusion, power bind fusion, direct energy deposition, and sheet lamination. The fabrication process of inkjet-based printing used for designing a microfluidics chipless RFID sensor is presented in [26]. The attributes explained above help in 3D printing and brush painting. In conventional processes, the footprint that is of no interest in design is etched out by chemicals or by the photolithography process. The main advantage of inkjet-based printing is the ability to print complex patterns that are very tough to fabricate and etch manually. The ink for printing is deposited with the help of a solution-based substrate [1]. In the drop-on-demand–based inkjet printing technology, a layer of conductive ink is deposited in the well-defined patterns that are needed for printing. Since inkjet printing is highly compatible with various organic materials, in [5], researchers used paper and wood substrates, respectively, and found their applications in the real-time tracking of objects using RFID. In addition to paper and wood, inkjet printing can also be done on carbon nanotubes (CNT), polymers, etc. Wood absorbs moisture, which can alter the performance of the tag in UHF and microwave frequency bands. To avoid this, artificial plywood that doesn’t absorb moisture can be used as a substrate.
Figure 6 . Classification of printing technologies.
Brush painting involves two important steps, such as painting and sintering. This method is used prominently for the printing of RFID tags on textile material for wearable applications using silver (Ag) and copper (Cu) nanoparticle inks. Silver- and copper-conductive inks are comparatively costly for tag fabrication. As an alternative, graphene-based carbon nanomaterials can be used. The unique features of this graphene are high charge mobility, biocompatibility and providing flexibility in design, lower processing temperature, light weight, and cost-effectiveness. Doctor-blading makes use of this material in the fabrication of the tag. Thermal printing is based on a thermal print concept. It consists of a ribbon that carries a thin metal attached to heat sensitive adhesive or glue. The process of printing is done by applying pressure on the material with the help of a thermal print head to the appropriate print area, which is deposited on the substrate. In the screen printing process, the print is produced with the application of pressure by a roller.
A wise selection of materials has to be done in the design process of the sensor. Hence the type of material used plays a crucial role in the sensing of physical parameters. Various materials used for sensing in chipless RFID technology are explained below. Classification of chipless RFID sensors is presented in Figure 7. RFID sensors are classified into mainly three types based on their encoding scheme. They are: time-domain reflectometry (TDR)-based, frequency domain-based, and phase domain-based. TDR-based is further classified into printable and nonprintable. Delay line-based sensors are used in printable ones, whereas surface acoustic wave (SAW)-based sensors are used in nonprintable-type sensors. SAW-based sensors are quite costly due to the presence of piezoelectric materials. In TDR-based, the sensing information is transferred in the form of a train of pulses interrogated by a UWB signal. Frequency domain-based is classified into planar and nonplanar types. In the frequency domain-based method, the data encoding is done in the frequency domain. The phase domain-based method is immune to environmental noise and uses left hand (LH) delay line-based sensors.
Figure 7 . Classification of chipless RFID sensors. MEMS: micro-electromechanical systems.
Smart materials, also called intelligent or responsive materials, are the kinds of materials that are sensitive to physical parameters, such as temperature, humidity, pH, light, stress, and other factors. They are extensively used in sensing operations because of their capacity to modify the EM signal properties according to the variations that happen in the surrounding environment. These smart materials are critical in sensing applications and are to be wisely chosen for a particular application. Hence, EM characterization of the material is a very important task that is to be performed before employing particular smart material for a sensing application. Atomic structure and mass are unique to each material from which electron discharge information can be deduced. Structural properties, like thickness, surface roughness, and chemical composition are other features that are to be taken care of while selecting materials, with the help of techniques like optical, scanning, and transmission electron microscopy. The crystal structure can be studied with the help of diffraction techniques like X-ray diffraction. The conductivity of the material used is another feature useful in identifying the correct material. Aluminum (Al), silver (Ag), and copper (Cu) materials have high conductivity and are used in microwave passive circuit design, whereas materials having lower conductivity, like silver flakes, silver-based nanoparticles, and indium tin oxide are used for sensing applications. Different sensing materials along with their properties are presented in Table 3.
Table 3. Smart materials used for designing chipless RFID sensors.
Materials like ionic plastic crystal, nanostructured metal oxide, and graphene are used for temperature sensing, whereas materials like Kapton and polyvinyl alcohol are used for humidity sensing. Poly (3,4-Ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) material is a very popular material for pH sensing. It has attractive features, like high stability, high conductivity, and excellent transparency [47]. In [48], smart-sensing materials for low-cost chipless RFID sensors are presented. Smart-sensing materials classification and their applications are discussed. In [60], the authors presented an identification integrated pH sensor tag for wireless pH sensing applications. The passive pH sensor tag is implemented by using a transceiver antenna, low-power digital modulation circuit, and an energy-harvesting circuit. The low-power digital modulation circuit is used to generate an identification code. pH sensing has found its application in health care due to the ease of diagnosis of different medical conditions, like gingivitis, periodontitis, or gastroesophageal reflux disease by wirelessly monitoring the pH of salivary or gastroesophageal fluid [61], [62], [63], [64].
In addition to health-care applications, pH sensing is useful in tracking the quality of meat- and fish-based perishable products in the cold-food supply chain. In the literature, different types of pH electrodes, like iridium oxide, antimony oxide, mixed metal oxide, glass electrode, and carbon nanotubes are reported [65], [66], [67]. In [60], the authors had chosen a cost-effective antimony/antimony oxide (Sb/Sb2O3)-based electrode for pH sensor design. The sensor design and fabrication of pH electrodes are discussed. In [68], the authors designed an iridium oxide-based pH sensor for wearable applications. The medical condition of an individual can be detected by monitoring the pH of body fluids, such as sweat, tears, and wound fluid, and by observing the pH condition of patient medical conditions, like diabetes and skin diseases. Iridium oxide-based pH sensors are prominent because of their wider pH operating range. In [49], the authors discussed the application of chitosan hydrogel as a pH sensor for smart packaging applications. The microwave characterization of chitosan-based hydrogel in the UWB frequencies (3–7 GHz) is presented. For the characterization of pH properties, chitosan hydrogel, which consists of materials like chitosan, polyethylene glycol (PEG), and acetic acid is used as the superstate smart material. At different pH levels, the RF characterization of chitosan hydrogel and its frequency response variations are recorded. The designed sensor can be operated in the range of pH on a 4 to 10 scale. The hydrogel can be prepared at a low cost and fabricated onto the chipless tag. In [69], the authors presented a polydimethyl-siloxane material-based pH sensor that operates in the UHF range for food-packaging applications. By correlating the EM properties of sensors and the characteristics of vital signs, the process of vital signs monitoring will be an easy task. In the next section, we will look into various vital signs and their importance in our day-to-day life.
Vital signs, such as heart rate, respiration rate, blood pressure, and posturography are useful in assessing the health status of an individual. Assessing the vital parameters, like deep breathing, indicates reduced stress and blood pressure, whereas shallow breathing indicates chronic stress. A respiratory pattern can also be used in assessing one’s sleeping and recovery status [6]. Hence, irregular breathing patterns indicate bad functionality of the respiratory process of an individual. Thus, vital signs monitoring plays a critical role in identifying the patient’s health status.
Breathing is a natural autonomic human activity that occurs naturally and continuously without the intervention of human intelligence. Breathing guarantees the necessary supply of oxygen to the body for survival. But in extreme stress, anxiety disorders, panic attacks, and chronic disease, the rhythm of respiratory activity is affected and needs to be monitored and addressed by physicians.
Therefore, respiratory analysis is useful in the health-care management of diseases that are caused due to variations in respiratory activity. Hence, monitoring respiratory activity will be useful in diagnosing the respiratory syndromes beforehand and will be helpful in the clinical management of these respiratory syndromes [6]. Some of the respiratory syndromes that can be monitored are obstructive sleep apnea syndrome and Rett syndrome, and other disorders, such as chronic obstructive pulmonary disease, asthma, and cardiac arrest. In this section, the method of respiration rate monitoring with the help of a graphene-oxide (GO)-based RFID sensor is discussed. In [42], the authors proposed a novel contactless wireless breath monitoring technique. A wearable textile-based sensor tag is proposed based on a spiral resonator tag printed on the flexible textile substrate. The sensing of the breathing is done by exploiting the contraction and expansion movements of the body that estimates the breathing activity of the subject under test. Similarly, in [43], the authors discussed the principle of wireless breath monitoring for apnea detection using a frequency-selective surface. The sensor, which is a negative temperature coefficient resistor attached under the subject’s nose, tracks the variations in the temperature due to the breathing activity (inhalation and exhalation).
Mortality rates are higher in low birthweight infants due to irregular heart rate conditions, like apnea and bradycardia. Continuous heart rate monitoring is helpful in detecting these conditions, thereby reducing the mortality rates and fatality risks in infants. This type of monitoring is also helpful in monitoring the developmental growth of infants. Bradycardia is a condition that occurs in infants when their heart rate is below 80 beats per minute (BPM) while awake and 60 BPM while in sleep. An irregular reduction in respiratory rate by 95% over a duration of 10 s can be defined as apnea for infants. So, for an infant monitor, real-time bradycardia and apnea detection is a major priority, as it indicates the health status of an infant. Heart rate detection is carried out by passive RFID tags [8], which is also discussed in this section.
Musculoskeletal health status can be tracked by observing one’s sitting posture. Hence, a good sitting posture is to be maintained by everyone to avoid musculoskeletal disorders. Poor sitting posture can affect one’s breath rhythm and increases fatigue of people. Poor sitting postures are closely related to back and joint pain, spondylosis, and other physical problems. To diagnose this kind of disorder, continuous monitoring of sitting posture is carried out, which will provide vital information about an individual’s sitting posture to the physician. One can reduce these risks by maintaining good sitting postures, like reducing the time of nonvertical sitting time. In the following subsection, we look into the sitting posture monitoring technique with the help of passive RFID technology. Various smart materials used in monitoring vital signs, like respiration rate, and temperature, are presented in Table 4. GO, polyethylene terephthalate (PET), Kapton, Rogers, and polypropylene (PP) materials are used as smart materials used for vital signs monitoring. Using GO respiration rate is monitored as the change in the EM property due to variation in RH. Similarly, each material has its characteristic way of varying the EM property of the signal according to variations of the physical parameters, like humidity.
Table 4. Smart materials used in monitoring vital signs.
With the advent of RFID technology, the process of continuous and noninvasive monitoring techniques gained prominence and gradually are replacing conventional respiration monitoring techniques, which are generally invasive and expensive in nature. These conventional methods require dedicated nasal thoracic belts, probes, and wires that are to be integrated with the sensors for monitoring, which are uncomfortable. Prolonged and continuous monitoring with this kind of equipment is too difficult. In recent times, RFID has become a promising dominant technology in which data retrieval and data transfer occurs wirelessly, and sensing happens noninvasively. Also, wearable devices have gained attention in the field of noninvasive and continuous monitoring. RFID, along with the advancement in smart materials and epidermal electronics, has improved the development of new kinds of sensors that are biointegrated, ultrathin, and easily adhered to the skin as a plaster or tattoo. This makes it easy to integrate a UHF-RFID antenna with a flexible GO-based sensor for respiration monitoring. GO is a derivative of graphene, which has good biocompatibility and is sensitive to metabolic activities. Hence, this feature can be utilized to capture respiratory cycles and other anomalous events, such as apnea and tachypnea. We require a humidity-sensitive GO-based sensor for respiration monitoring; the RH-based GO sensor is fabricated and characterized to evaluate the variations in resistance of the material modulated by RH.
The required GO sensor is fabricated with silicon or silicon-oxide wafer and graphene solution. Graphene solution is deposited over golden electrodes and dried with a peak-to-peak voltage of 10 applied to the electrodes. Annealing will be done after drying at 195 °C for 15 min, which will produce the GO-based sensor used in this application for respiration monitoring. The fabricated sensor [6], along with other components, are presented in Figure 8.
Figure 8 . Epidermal RFID sensor [6].
The measurement setup comprises a UHF-RFID reader, which works around 915 MHz connected to a linearly polarized antenna with 5-dB gain, and a GO sensor that is attached to a 20-${\mu}{\text{m}}$-thin polyurethane film. The sensor is connected to the antenna with wires. The whole setup is placed on the subject’s cheek and nose as shown in Figure 9. During breathing out, the human breath is largely humidified (RH > 60%), which increases the water deposition on the GO layer, which in turn increases resistance, while breathing in the water absorbed by GO is reduced, hence resistance decreases.
Figure 9 . Representation of the setup [6].
This emphasizes the capability of detecting anomalous events like apnea and tachypnea. Several breathing patterns are observed with alternating short intervals of anomalous events, which are detected by the sensor based on the variation in the resistance due to the change in the RH of the material.
The GO sensor used in monitoring respiratory rate has detected anomalous events in breath rate by calibrating changes in the resistance of the sensor, which changes according to the RH. The events detected during various cycles are presented in Figure 10.
Figure 10 . Anomalous events detected during respiration [6].
From Figure 11 we can observe the variation of resistance for different respiratory cycles like apnea, tachypnea, and others. We can observe that the resistance is found to vary when the subject is breathing normally. When the subject is facing a problem like apnea, the change in resistance is not clearly visible, which indicates there is a problem with breathing. Also, in the case of a deep breath, a high variation in resistance is observed.
Figure 11 . Heart rate detection using SimBaby monitor [8].
Noncontacting temperature monitoring has gained more prominence in recent times. Previously, there have been various kinds of temperature monitoring by using contacting devices, like thermometers, thermocouples assisted with wired sensors, and noncontacting types, like infrared or radiometric devices. These manual procedures have proven to be costly in recent times due to the contact procedure of staff with patients. Hence, contactless devices like infrared thermometers are used but with limited accuracy. Also, different parameters that affect this technique are mandatory line of sight to the subject of interest, strong sensitivity to the environmental parameters, and outer skin conditions, like sweating, cosmetics, and others. These parameters vary the radiation characteristics of the body. Recent innovative epidermal electronic technologies that are integrated with passive RFID technology are acting as a driving force for the development of a new class of epidermal ultrathin biointegrated RFID sensors that are compatible with human epidermis and fall under wearable devices.
A flexible adhesive-backed copper foil of 35-${\mu}{\text{m}}$ thickness is carved to prototype a sensor used for temperature monitoring [7]. To avoid the breaking of copper traces while carving meanderings, plastic adhesive tape is applied to the surface. All of the components that are meandered are kept on a 600-${\mu}{\text{m}}$-thick biosilicone membrane having a conductivity of 0.005 S/m and relative permittivity of 2.2 by using paper tape, thus forming copper–silicone bonding as the top surface, which is easy to peel off where integrated circuits (IC) are installed, if necessary, by forming a hole. Finally, a medical-grade adhesive is attached to the sensor setup, which is attached to the subject’s epidermis for temperature monitoring. The representation of the epidermal temperature monitoring system is represented in Figure 12.
Figure 12 . Epidermal temperature monitoring system [7].
Heart rate detection for infants is a critical vital sign to be monitored. The heart rate of the infant is monitored with the help of a passive RFID tag and electrocardiogram (ECG). Whenever a spike is detected by the ECG, which indicates a heartbeat, RFID is made when this spike occurs, thereby creating a waveform that constitutes these spikes separated by the time intervals. From these waveforms, heart rate can be calculated easily. In the absence of spikes, the RFID tag continues transmitting its unique ID number. Between the occurrence of spikes, the RFID tag is turned off, which we can call an outage. The whole system of heart rate detection requires less power and harvests energy from the RFID reader, which eliminates the usage of the battery, an IC, analog-to-digital converters, and memories. Since this RFID heart rate detection system is time-stamped, the calculation of heart rate is easy and simple.
In this heart rate detection system, SimBaby [8] is used, which is a programmable mannequin RFID system for cardiorespiratory monitoring in infants. The mannequin is connected to a computer with which vital signs are recorded. The breath rate is recorded by the rise and fall of the abdomen, which is tracked by an RFID bellyband. ECG activity of the infant is carried out by connecting two electrodes to the left and right arms. The representation of the heart rate detection system is given in Figure 13. In a multiple-tag environment, the reader should correlate the interrogating signals as per the read rate of the tag. A consistent read rate is essential for this detection system to avoid collisions between the tag responses. The heart rate tag is turned off for a considerable period when a heartbeat is detected. So, at the reader, a heartbeat is detected by the absence of a heart rate tag response for more than the time defined above. Depending on the time interval between successive outages, the heart rate is calculated.
Figure 13 . A setup for heart rate detection. (a) Complete setup of heart rate detection system. (b) A representation of integrating bellyband to a baby. (c) ECG signal contact. (d) Heart rate detection circuit [8].
With the help of the passive RFID tag included with the SimBaby monitor system, calibration is performed for the SimBaby system, and a comparison with the actual ECG signal is provided in Figure 11. The SimBaby is calibrated from 115 BPM to 50 BPM to detect anomalous events occurring in infants.
The heart rate detection circuit employed in SimBaby detects bradycardia and apnea by observing the changes in the heart rate calculation during outages. The representation of the events discussed above is presented in Figure 14. The SimBaby is tested for different anomalous event detections, as we find in Figure 14. For a period of 50 s, the heart rate varies around 115 BPM, which indicates bradycardia. In a normal heart cycle around 60 BPM is observed. Also in the bradycardia condition, the heart rate is varied very fast.
Figure 14 . Bradycardia and apnea detection in SimBaby [8].
Sitting posture can be recognized in two ways, by video-based approach and the sensor approach. In a video-based approach, there should be continuous streaming of the video by which the sitting posture is recognized. The video stream is applied to a machine learning algorithm that identifies the sitting posture depending on the training set it has based on computer vision graphics processing. This video-based approach is more accurate and has security concerns, since video streaming is required. On the other hand, in the wearable sensor-based approach, there are no such privacy issues and there is no compromise in privacy. However, most of the approaches used in wearable sensor-based kind use many on-body sensors, which cause severe discomfort to the users for long-term use. As an alternative, Feng et al. [9], proposed a new system of “sit right” (SitR), the sitting posture recognition system that uses only three lightweight and low-cost RFID tags, which are placed on the subject under test. The basic idea behind sitR is that three RFID tags are attached to the user’s body and an antenna is placed on the chair facing the tags on the user’s back; the distance varies between the tag and antenna according to the type of sitting posture. When there is a variation in the distance of the tag from the antenna, the received signal’s phase at the reader varies. The phase variation of each sitting posture is unique to itself. Since accuracy is of more concern, we have to place the tags on the user’s back where the system can attain maximum accuracy. Also, it is very important to avoid the multipath effect, which causes unnecessary phase variations. A representation of the sitR system is presented in Figure 15.
Figure 15 . Representation of sitR System [9].
The working of sitR consists of four stages by employing three RFID tags attached to the user’s back facing the antenna on a chair. Sitting posture recognition includes four stages. They are: tag placement and data collection, data preprocessing, extraction of features, and recognition of sitting posture. In the first stage, the three RFID tags are placed at key positions on the user’s back such that the phase information is extracted to the most accurate extent. Also, spinal imbalances can be easily detected. The tags are placed at the thoracic, thoracolumbar, and lumbar, which are our primary positions of interest. It is of greater importance to place the tags at a minimum distance to avoid mutual coupling from the nearby tags. This mutual coupling varies the radiation from the tags, which in turn varies the phase information associated with the tags. In the second stage, data preprocessing is done to remove the noise from hardware and multipath effects. To remove the hardware noise, a comparison of two adjacent phase measurements is done, after the threshold is applied to remove noise, and phase calibration is done. The multipath effects can be removed by wavelets. In the third stage, feature extraction of phase sequences is done. Each sitting posture is characterized by a phase sequence. In the fourth stage, this phase sequence is applied as data set to the random forest classifier to recognize sitting postures. K-nearest neighbor, Bayes, and decision tree also can be used as classifiers. A random forest classifier is used because of its better performance. These classifiers will help in the detection of sitting posture.
By employing three RFID tags on the subject’s back, the sitR system extracted the required phase information for different sitting postures. The phase information recorded by the sitR system for different sitting postures is presented in Figure 16. The sitR system includes some of the sitting postures as represented in Figure 17. They are identified as: sitting straight, lean forward, lean backward, left hand holding face, right hand holding face, fold right leg, and fold left leg.
Figure 16 . (a)-(g) Phase information of different sitting postures according to sitR system [9].
Figure 17 . Different sitting postures [9]: (a) sitting straight, (b) lean forward, (c) lean backward, (d) left hand holding face, (e) right hand holding face, (f) fold right leg, and (g) fold left leg.
A comparison table of different vital signs monitoring techniques is provided in Table 5. Several vital signs monitoring techniques are compared with respect to chipless RFID technology. Applications, frequency bands, and the materials used for vital signs monitoring are presented.
Table 5. A comparison of vital signs monitoring techniques with chipless RFID.
The challenges that are faced by chipless RFID sensors regarding wearability, feature extraction, tracking distance, reproducibility, compactness, fabrication, and simultaneous data capture of multiple tags are discussed in this section.
The devices that are manufactured should be wearable without much effort and should be comfortable for the user. They are to be of less weight and should not obstruct the regular activities of the user. One of the biggest challenges of chipless RFID design is in maintaining a cost-effective wearable device with less complexity. A textile-based chipless RFID tag is designed in [14], which is suitable for wearable applications. The work done in [15] used the concept of smart fabric and reduced the uncomfortable problems due to the placement of a huge number of sensors on the body in health-care management. Also, the wearable devices are designed in such a way that they are suitable for vital signs monitoring, like respiration rate, heart rate detection, and sitting posture in a noninvasive way.
In a multitag environment like vital signs monitoring for multiple individuals, it is very tough to handle multiple responses from multiple RFID tags. There may arise a collision situation among them like tag–tag collision, reader–tag collision, and reader–reader collision, of which tag–tag collision is a prominent one. It is highly essential in some situations where vital signs like temperature, heart rate, and respiration rate are to be monitored simultaneously. Also, collecting information from more sensors is a difficult task. Although there are several anticollision algorithms available for chip-based systems, they are not applicable to chipless systems. In [16], [17], and [18], the authors tried to collect information from multiple tags but still, some issues are present.
Although chipless RFID sensors reduced the cost since IC is not used, manufacturing techniques, like a deposition or photolithographic etching, have increased the cost. Screen printing, flexography, gravure printing, and inkjet printing techniques are the fabrication techniques that allowed the usage of low-cost substrate materials. Necessary care is to be taken in identifying the materials that are sensitive to vital signs. The materials that we choose should be sensitive to variations in temperature, heart rate, and respiration rate in one or another form.
Although huge research is going on in the chipless RFID domain, only a few are found suitable for practical applications. Reproducibility, robustness, and scalability are the important attributes that are to be kept in mind while designing and manufacturing chipless RFID sensors. The measured response of the sensor should not deviate from the simulated response in the vital signs monitoring scenario. Measuring vital signs like temperature, heart rate, and respiration rate in an accurate way is necessary to diagnose the diseases.
The electrical characterization of the RFID system varies with a change in the surrounding environment, which will affect the parameters, like conductivity, the amplitude of the signal, resonant frequency, and Q-factor. Also, tag orientation, interference from other sources, noise from objects around, and polarization mismatches are the other factors that are responsible for variation in the features of the backscattered signal. Hence, feature extraction methods are helpful in getting sensing information without noise [9]. Principal component analysis and independent component analysis are the processes used for feature extraction. So, feature extraction is a vital thing that has to be done to attain robust detection in RFID sensors.
The read distance is a key factor in the working of a chipless RFID sensor since based on the reading distance, parameters like amplitude (RCS level) are going to be affected. Also, reading distance is dependent on transmitted power, the gain of the antenna, and other factors. Noise from the surrounding tags and objects also affect the reading distance of a tag. Therefore, several other sophisticated solutions are required to improve the reading distance of the chipless RFID sensor.
The flexibility of the chipless RFID sensor for vital signs monitoring, like temperature, heart rate, and respiration rate, is a major challenge because the designed sensors have to be conformable on the surface of the body at different locations.
Since chipless RFID doesn’t carry any chip, it’s difficult to get higher data capacity in chipless RFID within smaller physical footprints, as compared to chip-based. In [3], the authors proposed a hybrid coding technique to improve the coding capacity, but its practical application is yet to be investigated. For multiple vital signs monitoring, tags with higher data capacity are preferred. In [24], the authors presented a passive hybrid resonator-based RFID transponder that enhanced the data capacity.
The sensors that are used for sensing purposes in vital signs monitoring should be biocompatible. Since in most cases of vital signs monitoring the sensors will be in direct contact with the body, the materials with which sensors are fabricated should not be toxic or hazardous.
The article discussed the basic features of the chipless RFID system that includes transponder design and reader architecture. Comparison of chipless and chip-based RFID, chipless RFID sensor classification, and printing technologies are presented. Discussion of compact and high bit capacity tag design is elaborated. Data-encoding techniques in both time and frequency domains are discussed. A section is dedicated to explain the importance of smart materials in the field of sensing for the benefit of the readers. Most of the existing technologies are invasive in nature, so this review focused on a few vital signs monitoring techniques with chipless RFID sensor technology that is entirely noninvasive in nature. Most of the vital signs are monitored in the UHF range with passive RFID technology. Several examples of monitoring vital signs with the help of chipless RFID are provided. There are still other vital signs that are to be taken care of. The challenges faced by chipless RFID in the area of vital signs monitoring with respect to area of coverage, the orientation of the tag, and materials suitable for the purpose are addressed. It is a big task to identify the specific material for sensing vital signs and recording their EM response in the RF range. The future focus should be in the direction of enhancing the parameters discussed above.
The authors thank Subhasish Pandav, Priyabrata Sethy, Kushbu Patel, Gaddam Sai Priya and Kottakota Uha Priya for their constant support in writing this article.
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Digital Object Identifier 10.1109/MMM.2023.3303668