Healthcare Monitoring Applications Research Articles

Graphene oxide microstrip antenna-based sensor for oxygen gas sensing in medical applications

Abstract In this work, we report the development of a new graphene oxide (GO) sensor based on a microstrip antenna for detecting and measuring O2 concentration. GO was prepared from natural graphite powder using a modified Hummers procedure and then deposited upon a phenolic substrate to act as the sensing element of the designed device. Detection tests employing the sensor to evaluate oxygen gas (O2) in higher concentrations were performed, whereas it was observed that the two operating frequencies of the device was displaced to higher values as the concentration oxygen gas increased. The effect of relative humidity (RH) in the response sensor too was observed, whereas the 9.704 GHz mode demonstrating to be the most sensitive to O2 variation after sensitivity values have been corrected, presenting limit of detection (LOD) equal to 0.38%O2. Evaluating the results, it is possible to note that the device studied could be used as sensor in medical equipment operating at elevated oxygen concentrations, such as ventilators, O2 concentrators, and other medical equipment. Moreover, evaluated sensor would be a promisor candidate for healthcare monitoring applications for the reason that this device could act as both an O2 sensor and antenna, and thus transmitting their information to other devices. 

Hot‐spot aware multicost‐based energy‐efficient routing protocol for WBANs

SummaryWireless body area networks (WBANs) are becoming widely considered in remote healthcare monitoring applications. However, WBAN nodes have limited resources; therefore, effective and reliable routing protocols are pivotal research challenges. Furthermore, balancing the traffic load among sensor nodes is also highly required to increase network stability. In recent years, many interesting routing solutions have been proposed for WBANs; however, the significant feature in terms of stability and energy in these solutions has not been sufficiently addressed. Therefore, in this context, the Hot‐Sspot Aaware Multicost‐based Energy‐efficient Routing (H‐SAMER) protocol is proposed in this paper. The suggested protocol used multieffective cost function for next‐hop node selection based on the data type, where the patient's data are categorized into three classes: normal data, on‐demand data, and emergency data. Furthermore, the H‐SAMER protocol adds awareness to the transmission of control packets by adding the cost value to the RREQ packets. Thus, the simulation scenario shows that the H‐SAMER saves energy 8.57%, 88%, 98%, 97%, and 100% greater than E‐HARP, EH‐RCP, CO‐LAEEBA, EECBSR, and ELR‐W, respectively. Moreover, the first node death of the proposed H‐SAMER is delayed to round number 7500, which proves H‐SAMER to be a stable and reliable effective solution for WBANs.

Customizable and scalable manufacture of aesthetic ionic conductive silk yarns for e-textile devices

Electronic textiles (e-textiles), which combine the comfort of textiles with the functionality of soft electronics, have attracted much attention in wearable applications. However, scale-up fabrication of stretchable textiles with concurrent high stability and aesthetic appeal features poses significant challenges. Here, we report a scalable and customizable dip-coating strategy for the preparation of multiple-colored and functionally stable ionic conductive silk yarns (i-SY) and demonstrate their effectiveness in exercise posture correction. The i-SY preserves the inherent properties of silk fibers and ionic liquids, exhibiting improved mechanical properties, weaving capabilities, flame retardancy, and electrical conductivity. The method leverages the exceptional transparency of ionic liquids, facilitating the large-scale production of colored i-SYs to meet aesthetic demands. Additionally, the i-SY sensor exhibits exemplary sensing sensitivity and stability, enabling the real-time monitoring of human joint movements and facilitating precise posture correction during fitness exercises. We envision that the proposed sensing textile holds promise for applications in wearable devices, healthcare monitoring, and human–machine interfaces.

Comparison of Machine Learning Algorithms for Heartbeat Detection Based on Accelerometric Signals Produced by a Smart Bed.

This work aims to compare the performance of Machine Learning (ML) and Deep Learning (DL) algorithms in detecting users' heartbeats on a smart bed. Targeting non-intrusive, continuous heart monitoring during sleep time, the smart bed is equipped with a 3D solid-state accelerometer. Acceleration signals are processed through an STM 32-bit microcontroller board and transmitted to a PC for recording. A photoplethysmographic sensor is simultaneously checked for ground truth reference. A dataset has been built, by acquiring measures in a real-world set-up: 10 participants were involved, resulting in 120 min of acceleration traces which were utilized to train and evaluate various Artificial Intelligence (AI) algorithms. The experimental analysis utilizes K-fold cross-validation to ensure robust model testing across different subsets of the dataset. Various ML and DL algorithms are compared, each being trained and tested using the collected data. The Random Forest algorithm exhibited the highest accuracy among all compared models. While it requires longer training time compared to some ML models such as Naïve Bayes, Linear Discrimination Analysis, and K-Nearest Neighbour Classification, it keeps substantially faster than Support Vector Machine and Deep Learning models. The Random Forest model demonstrated robust performance metrics, including recall, precision, F1-scores, macro average, weighted average, and overall accuracy well above 90%. The study highlights the better performance of the Random Forest algorithm for the specific use case, achieving superior accuracy and performance metrics in detecting user heartbeats in comparison to other ML and DL models tested. The drawback of longer training times is not too relevant in the long-term monitoring target scenario, so the Random Forest model stands out as a viable solution for real-time ballistocardiographic heartbeat detection, showcasing potential for healthcare and wellness monitoring applications.

MoS2 based flexible photodetector for broadband visible light photodetection

In recent years, flexible photodetectors (PD) have emerged as a significant innovation with potential applications in healthcare, security, and environmental monitoring. Two-dimensional (2D) layers of metal dichalcogenides MoS2 have gathered significant attention due to their ultrathin thickness and promising applications in the fields of flexible PD. 2H phase of MoS2 micro-flowers were synthesized by facile hydrothermal route. Raman spectra was employed to analyze the quality of grown MoS2 and confirmed with E12g and A1g Raman phonon modes. The micro-flower morphological was verified through FESEM. Subsequently, PD device was fabricated through bar coating method over a flexible polyethylene terephthalate (PET) substrate and Indium Tin oxide (ITO) was employed as an electrode. Photodetection property of the device was tested under dark and illumination. MoS2-microflower PD exhibit good photoresponsivity and detectivity of 1.5 µA/W and 105 Jones at 5 V respectively. Moreover, detector demonstrated remarkable flexibility and exceptional air stability.

Ultrasensitive Flexible Pressure Sensors with Broad Linear Detection Range Enabled by Magnetically Induced Self‐Assembled Parallel Circuit

AbstractFlexible pressure sensors have attracted intensive interest for promising applications in healthcare monitoring and flexible electronic devices. Nonetheless, designing flexible pressure sensors to achieve both ultrahigh sensitivity (>1000 kPa−1) and an extensive linear range (>50 kPa) poses a significant challenge. In this study, a facile magnetic‐facilitated self‐assembly parallel circuit strategy to prepare high‐performance flexible pressure sensors in Nickel particles/polydimethylsiloxane (Ni/PDMS) matrices is proposed. The optimized magnetic‐induced Ni/PDMS piezoresistive sensor (MANPS) exhibits an ultrahigh sensitivity of 3707 kPa−1 over a wide broad linear range (0–80 kPa), and excellent durability with the capability of withstanding 2000 pressure cycles. The MANPS is able to detect a broad range of pressures from pulse to plantar pressures (≈60 kPa), demonstrating great potential for whole‐body healthcare monitoring. Additionally, the sensor is further assembled into an array configuration (2 × 5 pixels) for the assessment of plantar pressure distribution. Importantly, the sensitivity and linear range of the MANPS can be readily adjusted by modifying the mixing ratio of the curing agent, thereby significantly broadening its potential applications.

Selective fluoride detection based on modulation of red emissive carbon dots fluorescence by zirconium-alizarin complex: Application to Nile River water and human saliva samples

Fluoride is an essential ion for dental health that is optimally supplemented through drinking water, toothpastes, and other oral hygiene products. This work reports a selective, simple, and inexpensive fluorescent sesnor for fluoride quantification. The sensor exploits the red fluorescence of carbon dots coupled with the colorimetric response of a zirconium-alizarin complex. The zirconium-alizarin exhibits an absorption band at 530 nm that overlaps the carbon dot excitation peak, resulting in inner filter effect-based quenching of the 612 nm red emission. However, in the presence of fluoride, binding disrupts the zirconium complex, releasing free alizarin with an absorption blue shifted to 420 nm. This reduces spectral overlap and restores carbon dot fluorescence. The carbon dots were synthesized by a hydrothermal method and exhibited excellent fluorescence quantum yield (16.3 %). Structural and optical characterizations were performed using TEM, XRD, XPS, FTIR, UV–vis, and fluorescence techniques. Under optimized conditions, the probe provided selective turn-on fluorescence detection of fluoride with a linear response from 1.0 to 130.0 μM and limit of detection (S/N = 3) of 0.32 μM. Practical utility was demonstrated by accurate quantification of fluoride in Nile River water and human saliva samples. This dual nanoprobe strategy offers a rapid and cost-effective platform for fluoride analysis in support of healthcare and environmental monitoring applications.

Performance Improvement for Reconfigurable Processor System Design in IoT Health Care Monitoring Applications

Performance Improvement for Reconfigurable Processor System Design in IoT Health Care Monitoring Applications

Radiation Detector Front-End Readout Chip with Nonbinary Successive Approximation Register Analog-to-Digital Converter for Wearable Healthcare Monitoring Applications.

A 16-channel front-end readout chip for a radiation detector is designed for portable or wearable healthcare monitoring applications. The proposed chip reads the signal of the radiation detector and converts it into digital serial-out data by using a nonbinary successive approximation register (SAR) analog-to-digital converter (ADC) that has a 1-MS/s sampling rate and 10-b resolution. The minimum-to-maximum differential and integral nonlinearity are measured as -0.32 to 0.33 and -0.43 to 0.37 least significant bits, respectively. The signal-to-noise-and-distortion ratio and effective number of bits are 57.41 dB and 9.24 bits, respectively, for an input frequency of 500 kHz and a sampling rate of 1 MS/s. The SAR ADC has a 38.9-fJ/conversion step figure of merit at the sampling rate of 1 MS/s. The proposed chip can read input signals with peak currents ranging from 20 to 750 μA and convert the analog signal into a 10-bit serial-output digital signal. The input dynamic range is 2-75 pC. The resolution of the peak current is 208.3 nA. The chip, which has an area of 1.444 mm × 10.568 mm, is implemented using CMOS 0.18-μm 1P6M technology, and the power consumption of each channel is 19 mW. This design is suitable for wearable devices, especially biomedical devices.

Bionic-leaf vein inspired breathable anti-impact wearable electronics with health monitoring, electromagnetic interference shielding and thermal management

Breathable and stretchable conductive materials are ideal for healthcare wearable electronic devices. However, the tradeoff between the sensitivity and detection range of electronic sensors and the challenge posed by simple-functional electronics limits their development. Here, inspired by the bionic-leaf vein conductive path, silver nanowires (AgNWs)-Ti3C2Tx (MXene) hybrid structure assembled on the nonwoven fabrics (NWF) is well sandwiched between porous polyborosiloxane elastomer (PBSE) to construct the multifunctional breathable wearable electronics with both high anti-impact performance and good sensing behavior. Benefiting from the high conductive AgNWs-MXene hybrid structure, the NWF/AgNWs-MXene/PBSE nanocomposite exhibits high sensitivity (GF = 1158.1), wide monitoring range (57 %), controllable thermal management properties, and excellent electromagnetic interference shielding effect (SET = 41.46 dB). Moreover, owing to the wonderful shear stiffening effect of PBSE, the NWF/AgNWs-MXene/PBSE possesses a high energy absorption performance. Combining with deep learning, this breathable electronic device can be further applied to wireless sensing gloves and multifunctional medical belts, which will drive the development of electronic skin, human-machine interaction, and personalized healthcare monitoring applications.

Discriminative detection of glucose and urea with a composite polymer nanofiber based matrix

AbstractDetection and quantification of glucose and urea are fundamental in medical analysis, real‐time monitoring, and point of care analysis. However, such analyses generally require sophisticated instrumentation and specialized personnel. Furthermore, discriminative detection of multiple analytes is often necessary for treatment and diagnosis. To address this challenge, this study describes a proof‐of‐concept for discriminative sensitive amperometric detection of both analytes. This was achieved by the fabrication of a polymer‐MWCNTs composite nanofiber matrix upon which glucose oxidase (GOD) and urease were co‐immobilized to allow detection of the corresponding substrates (glucose and urea). The (PAN(−MWCNTs)/Urease‐GOD) biosensor showed good performance in: (i) glucose biosensing with sensitivity of 31±5 μAmM−2cm−2 within an extended linear range (0.1–5.0 mM) and a limit of detection of 3.7 μM, and (ii) urea detection at very low concentration (4–30 and 30–90 μM) with sensitivity up to 350±19 μAmM−2cm−2 and very low LOD (0.1 μM). The analogous mono‐enzyme platform for urea detection (PAN(−MWCNTs)/Urease) showed very similar performance as the bi‐enzyme sensor, suggesting little to no influence of co‐immobilization on Urease activity, thus confirming that the two catalytic processes are independent of each other. The biosensors exhibited high accuracy in the detection of both analytes (at normal and pathological levels) in human serum, thus proving that the biosensor described herein can have practical applications in healthcare and remote patient monitoring.

Resilient Energy Efficient IoT Infrastructure With Server and Network Protection for Healthcare Monitoring Applications

Resilient Energy Efficient IoT Infrastructure With Server and Network Protection for Healthcare Monitoring Applications

Nanostructured Electrochemical Devices and Self-Powered Systems for Biosensing

Flexible and integrated systems for smart biosensing have attracted tremendous research interest in recent years, mainly due to the rapidly expanding market of wearable and portable devices for applications in clinical diagnosis and physiological monitoring. In our work, novel and unique hierarchical nanostructures were designed and synthesized to realize electrochemical devices with high performance, especially the sensor stability and energy storage capability. Meanwhile, scalable and printable approach was developed to integrate these electrochemical devices into monolithically integrated self-powered systems. The as-developed nanostructured electrochemical devices in conjunction with printable approach show great potency in fabrication of various wearable integrated self-powered devices for personalized healthcare monitoring applications.

Harnessing UV light for enhanced room temperature ultra-low NO sensing via WSe2/GaN heterostructure

Transition metal chalcogenides (TMDs) are significant for room-temperature (RT) gas sensing. However, the gas sensing proficiency of WSe2-based sensors is still to be enhanced in terms of selectivity and responsivity. Here, we report UV light-activated WSe2/GaN heterostructure based highly sensitive and selective RT operable NO sensor. The WSe2/GaN device is proficient for NO sensing in a broad concentration range from 100 ppb to 10 ppm. The relative NO sensor response was elevated to 3-fold and 1.75-fold under 266 nm (UVC) and 355 nm (UVA) illumination, respectively. Astonishing relative sensor response of 92.4 % (16.8 %) for 10 ppm (100 ppb) NO gas at RT under UVC is reported with a rapid response/recovery time of 13.64/21.24 sec followed by a significant reduction in the limit of detection (10 ppb). Additionally, impressive sensor responses of 10 % and 58 % were also observed for UVA. Further, the device demonstrates long-term stability and consistent performance with insignificant changes in responsivity, particularly under UVC. Integrating WSe2 with GaN and a large specific surface area boost the charge transfer under UV, leading to superior NO sensing. The device offers significant applications in environmental & healthcare monitoring and provide opportunities for wearable device integration for continuous tracking and monitoring of NO gas.

Melanin-inspired conductive thin films for multimodal-sensing wearable on-skin electronics

Electronic skins (e-skins), composed of various flexible sensors, mimic the sensing functions of human skin aiming for both healthcare monitoring and prosthetics development applications. So far different multi-component e-skin devices aimed to fulfill different requirements (biocompatibility, skin adhesion, flexibility, conductivity, sensitivity towards biological stimuli and stretchability) have been reported. However, the obtaining of such devices combining all the above requirements within a single material that simplifies not only cost but specially functioning still remains a challenge. For this, catechol-based materials have attracted special attention due to their adhesive properties, compatibility and melanin-like electrical conduction. In this work, 2,3,6,7,10,11 – hexahydroxy triphenylene (HHTP) was used as catechol moiety in a typical melanin-like polymerization, resulting in a free-standing melanin-inspired film (MN-film). The obtained MN-film showcased good conductivities with dual charge carriers (electrons and ions) under different environments, i.e. pure water and buffers simulating sweat. Large biocompatibility, adhesion and conformability to skin were obtained as well, allowing to implement the film in wearable electronic on-skin devices on porcine skin. Measurements in wearable devices indicated large sensitivity towards different stimuli (strain, motion and temperature) under sweat-like conditions.

Highly Conductive Peroxidase-like Ce-MoS2 Nanoflowers for the Simultaneous Electrochemical Detection of Dopamine and Epinephrine.

The accurate and simultaneous detection of neurotransmitters, such as dopamine (DA) and epinephrine (EP), is of paramount importance in clinical diagnostic fields. Herein, we developed cerium-molybdenum disulfide nanoflowers (Ce-MoS2 NFs) using a simple one-pot hydrothermal method and demonstrated that they are highly conductive and exhibit significant peroxidase-mimicking activity, which was applied for the simultaneous electrochemical detection of DA and EP. Ce-MoS2 NFs showed a unique structure, comprising MoS2 NFs with divalent Ce ions. This structural design imparted a significantly enlarged surface area of 220.5 m2 g-1 with abundant active sites as well as enhanced redox properties, facilitating electron transfer and peroxidase-like catalytic action compared with bare MoS2 NFs without Ce incorporation. Based on these beneficial features, Ce-MoS2 NFs were incorporated onto a screen-printed electrode (Ce-MoS2 NFs/SPE), enabling the electrochemical detection of H2O2 based on their peroxidase-like activity. Ce-MoS2 NFs/SPE biosensors also showed distinct electrocatalytic oxidation characteristics for DA and EP, consequently yielding the highly selective, sensitive, and simultaneous detection of target DA and EP. Dynamic linear ranges for both DA and EP were determined to be 0.05~100 μM, with detection limits (S/N = 3) of 28 nM and 44 nM, respectively. This study shows the potential of hierarchically structured Ce-incorporated MoS2 NFs to enhance the detection performances of electrochemical biosensors, thus enabling extensive applications in healthcare, diagnostics, and environmental monitoring.

Flexible reduced graphene oxide/polypyrrole films for supercapacitors

The films with stable flexibility and excellent electrochemical properties are essential for fabricating portable and wearable supercapacitors. In this work, the free-standing, flexible reduced graphene oxide/polypyrrole nanotubes (rGO/PPy) films were prepared by the vacuum-filtration of PPy nanotubes and graphene oxide (GO) followed by the reduction treatment of KI and HCl solution. The prepared films exhibited remarkable flexibility, as they can withstand bending to 90° more than 1000 times without experiencing any cracks. Furthermore, the symmetric supercapacitor of rGO/PPy exhibited an areal capacitance of 631 mF cm−2 and a volumetric capacitance of 117,000 mF cm−3, as well as the areal energy density of 56.1 μWh cm−2. Meanwhile, the electrochemical performance under various bending states was stable, and capacitance retention (86 %) after 800 bending cycles was achieved. These characteristics are essential for manufacturing wearable devices, portable electronics, and healthcare monitoring applications.

Highly stretchable, self-healing, self-adhesive and conductive nanocomposite hydrogels based on multi-reversible interactions as multifunctional strain sensors

Construction of highly stretchable and sensitive flexible strain sensors is of great significance for wide applications in human–computer interaction, wearable devices, and electronic skins. However, it turned out to be not effortless to integrate the two seemingly contrary features of high stretchability and sensitivity into a system. Herein, we designed a nanocomposite conductive hydrogel (NCCH) composed of zwitterionic poly(HEAA-co-SBMA) polymers and lithium magnesium silicate (XLG) by means of multi-reversible molecular interactions (MRMIs) including borate ester bonds between polyHEAA and borax, hydrogen bonds, and polySBMA-XLG-based electrostatic interaction, endowing the NCCH with enhanced mechanical, self-healing, adhesive, biocompatible, and sensing performances. The MRMI method enabled NCCHs to obtain an excellent stretchability (∼1080 %)/compressibility (∼98.5 %), a tensile strength of ∼ 0.06 MPa, a good self-healing with a fracture strain recovery of 90.5 %, and a strong adhesion on various hard and soft substrates (e.g. a adhesive shear force of 60 kPa to pigskin tissues). Besides, the integration of zwitterionic polySBMA and conductive XLG promoted charge transfer.by optimal ioinic channels. Based on these outstanding strengths, the NCCHs were farther rationally fabricated as multifunctional strain sensors with remarkable sensing stability for fast and accurately detecting strain/pressure-induced deformation, joint motions, and animal heartbeats. Notably, the excellent self-healing property of NCCH sensors can facilitate their long-period usage and complete recyclability for avoiding wastes. The new MRMI-based NCCH sensor without any conductive additives is deemed to provide a new strategy for broadening their multifunctional strain sensor and healthcare monitoring applications.

Templated Laser-Induced-Graphene-Based Tactile Sensors Enable Wearable Health Monitoring and Texture Recognition via Deep Neural Network.

Flexible tactile sensors show great potential for portable healthcare and environmental monitoring applications. However, challenges persist in scaling up the manufacturing of stable tactile sensors with real-time feedback. This work demonstrates a robust approach to fabricating templated laser-induced graphene (TLIG)-based tactile sensors via laser scribing, elastomer hot-pressing transfer, and 3D printing of the Ag electrode. With different mesh sandpapers as templates, TLIG sensors with adjustable sensing properties were achieved. The tactile sensor obtains excellent sensitivity (52260.2 kPa-1 at a range of 0-7 kPa), a broad detection range (up to 1000 kPa), a low limit of detection (65 Pa), a rapid response (response/recovery time of 12/46 ms), and excellent working stability (10000 cycles). Benefiting from TLIG's high performance and waterproofness, TLIG sensors can be used as health monitors and even in underwater scenarios. TLIG sensors can also be integrated into arrays acting as receptors of the soft robotic gripper. Furthermore, a deep neural network based on the convolutional neural network was employed for texture recognition via a soft TLIG tactile sensing array, achieving an overall classification rate of 94.51% on objects with varying surface roughness, thus offering high accuracy in real-time practical scenarios.

A fiber-shaped temperature sensor composed of chitosan/rGO with high sensitivity and ultra-fast response and recovery for real-time temperature monitoring

Wearable sensors are the development trend in the future iteration of medical devices, in which, flexible temperature sensors with high resolution, fast response speed, and good reliability under deformations, are one of the much important devices. In this study, a nano multilayer sensing structured fiber temperature sensor is fabricated via in situ coating reduced graphene oxide (rGO) and chitosan (CS) on the surface of stretchable polyurethane fiber (PF) by a layer-by-layer self-assembly method. The introduction of CS not only enhances the temperature sensitivity (with a temperature coefficient of −1.379 %‧°C−1 in the range of 30–60 °C) of the rGO-based fiber sensors but also greatly increases the mechanical stability of the nanofibrous membrane. Most importantly, the fiber-shaped temperature sensor shows a fast response time (2.4 s) and recovery time (3.9 s) to temperature. Moreover, the sensor achieves a high temperature resolution of 0.1 °C. Made from a simple and low-cost process, the fiber-like devices can be easily integrated into items such as gloves or face masks to monitor the real-time temperature changes. The results demonstrate the great potential of rGO-based fiber sensors for applications in human healthcare monitoring.