Healthcare Sensor Research Articles

Radar-based contactless heart beat detection with a modified Pan–Tompkins algorithm

Background.Using radar for non-contact measuring human vital signs has garnered significant attention due to its undeniable benefits. However, achieving reasonably good accuracy in contactless measurement senarios is still a technical challenge.Materials and methods.The proposed method includes two stages. The first stage involves the process of datasegmentation and signal channel selection. In the next phase, the raw radar signal from the chosen channel is subjected to modified Pan-Tompkins.Results.The experimental findings from twelve individuals demonstrated a strong agreement between the contactless radar and contact electrocardiography (ECG) devices for heart rate measurement, with correlation coefficient of 98.74 percentage; and the 95% limits of agreement obtained by radar and those obtained by ECG were 2.4 beats per minute.Conclusion.The results showed high agreement between heart rate calculated by radar signals and heart rate by electrocardiograph. This research paves the way for future applications using non-contact sensors to support and potentially replace contact sensors in healthcare.

Secured Fog-Body-Torrent : A Hybrid Symmetric Cryptography with Multi-layer Feed Forward Networks Tuned Chaotic Maps for Physiological Data Transmission in Fog-BAN Environment

Recently, the Wireless Body Area Networks (WBAN) have become a promising and practical option in the tele-care medicine information system that aids for the better clinical monitoring and diagnosis. The trend of using Internet of Things (IoT) has propelled the WBAN technology to new dimension in terms of its network characteristics and efficient data transmission. However, these networks demand the strong authentication protocol to enhance the confidentiality, integrity, recoverability and dependability against the emerging cyber-physical attacks owing to the exposure of the IoT ecosystem and the confidentiality of biometric data. Hence this study proposes the Fog based WBAN infrastructure which incorporates the hybrid symmetric cryptography schemes with the chaotic maps and feed forward networks to achieve the physiological data info security without consuming the characteristics of power hungry WBAN devices. In the proposed model, scroll chaotic maps are iterated to produce the high dynamic keys streams for the real time applications and feed-forward layers are leveraged to align the complex input-output associations of cipher data for subsequent mathematical tasks. The feed forward layers are constructed which relies on the principle of Adaptive Extreme Learning Machines (AELM) thereby increasing randomness in the cipher keys thereby increasing its defensive nature against the different cyber-physical attacks and ensuring the high secured encrypted-decrypted data communication between the users and fog nodes. The real time analysis is conducted during live scenarios. BAN-IoT test beds interfaced with the heterogeneous healthcare sensors and various security metrics are analysed and compared with the various residing cryptographic algorithms. Results demonstrates that the recommended methodology has exhibited the high randomness characteristics and low computational overhead compared with the other traditional BAN oriented cryptography protocol schemes

Wearable Sensors for Healthcare of Industrial Workers: A Scoping Review

Background and Objectives: This scoping review evaluates the use of wearable sensor technologies for workplace safety and health monitoring in industrial settings. The aim is to synthesize evidence on the impact of these sensors and their application in high-risk environments. Materials and Methods: Following the PRISMA guidelines, a systematic search across four international electronic databases yielded 59 studies, of which 17 were included in the final review. The selection criteria involved studies that specifically utilized wearable sensors to monitor various health and environmental parameters relevant to industrial workers. Results: The analysis categorizes wearable technologies into five distinct groups based on their function: gas monitoring technologies, heart rate and physiological data collection, fatigue and activity monitoring, comprehensive environmental and physiological monitoring, and advanced sensing and data collection systems. These devices demonstrated substantial benefits in terms of early detection of health risks and enhancement of safety protocols. Conclusions: The review concludes that wearable sensor technologies significantly contribute to workplace safety by providing real-time, data-driven insights into environmental hazards and workers’ physiological status, thus supporting proactive health management practices in industrial settings. Further research is recommended to address the challenges of data privacy, sensor reliability, and cost-effective integration to maximize their potential in occupational health safety.

Stretchable, Self-Healing, and Bioactive Hydrogel with High-Functionality N,N'-bis(acryloyl)cystamine Dynamically Bonded Ag@polydopamine Crosslinkers for Wearable Sensors.

Hydrogels present attractive opportunities as flexible sensors due to their soft nature and tunable physicochemical properties. Despite significant advances, practical application of hydrogel-based sensor is limited by the lack of general routes to fabricate materials with combination of mechanical, conductive, and biological properties. Here, a multi-functional hydrogel sensor is reported by in situ polymerizing of acrylamide (AM) with N,N'-bis(acryloyl)cystamine (BA) dynamic crosslinked silver-modified polydopamine (PDA) nanoparticles, namely PAM/BA-Ag@PDA. Compared with traditional polyacrylamide (PAM) hydrogel, the BA-Ag@PDA nanoparticles provide both high-functionality crosslinks and multiple interactions within PAM networks, thereby endowing the optimized PAM/BA-Ag@PDA hydrogel with significantly enhanced tensile/compressive strength (349.80kPa at 383.57% tensile strain, 263.08kPa at 90% compressive strain), lower hysteresis (5.2%), improved conductivity (2.51 S m-1) and excellent near-infrared (NIR) light-triggered self-healing ability. As a strain sensor, the PAM/BA-Ag@PDAhydrogel shows a good sensitivity (gauge factor of 1.86), rapid response time (138ms), and high stability. Owing to abundant reactive groups in PDA, the PAM/BA-Ag@PDA hydrogel exhibits inherent tissue adhesiveness and antioxidant, along with a synergistic antibacterial effect by PDA and Ag. Toward practical applications, the PAM/BA-Ag@PDA hydrogel can conformally adhere to skin and monitor subtle activities and large-scale movements with excellent reliability, demonstrating its promising applications as wearable sensors for healthcare.

Coaxially spinning spiral coils into concentric microtubes to synchronize motion and temperature sensing for stretchable and wearable device

Wearable electronical sensors with the combination of multi-mode sensing, stretchability and stability have long been in pursuit for various applications, such as the strain and temperature sensing for health assessment and disease diagnosis. To design endurable dual-mode sensor without signal interference, in this study, a coaxial wet spinning process were suggested to spin helical fibers into concentric double-layer microtubes to synchronize motion and temperature sensing with negligible signal interference. The inner helical fiber showed a high temperature-dependent ionic conductivity for the sensitivity of 5.76 % °C−1 and detection limit of 0.1 °C. Its helical geometry ensured large stretchability and minimal strain-induced interference. The outer coating shell could serve as the strain sensor with a high gauge factor of 11.36–1512 (up to 300 % strain) and response time of 120 ms. When filling the microtubes with polydimethylsiloxane, the multi-mode sensos could stay stable sensing abilities up to 104 stretching-release cycles. Thus, this study not only offers a coaxial spinning approach for production of stretchable multicomponent fibers, but also shows an unprecedented alternative of dual-mode sensor for healthcare, rehabilitation, and sleep monitoring.

Stable Operation and Enhanced Sensitivity via Composite Structure Design for Efficient Photoplethysmography and Motion Sensors

Healthcare sensors have attracted lots of interests owing to saving a patient's life by continuously monitoring the patient's health via early diagnosis of the symptoms by using healthcare sensors. Many health-care sensors are available in wearable application that can monitor continuously patient health. There are some common parameters such as a heart rate and human motion that are used to monitor human activity.In order to realize stable operation of health-care sensors, material designs are required considering human-body compatibility. In this research, light-sensors fabricated from low-toxicity organic materials by introducing neutral poly(3,4-ethylenedioxythiophene)-(polystyrene sulfonate) (PEDOT-(PSS)) to improve human-body compatibility as well as to strengthen photoplethysmography (PPG) signal. [1] Neutral PEDOT-(PSS) with heterocyclic 1,3-diazole (HDZ) enhances the polymerization degree, carrier mobility, and other physicochemical properties. Consequently, the presented OPD-based PPG sensor has the ability to diagnose blood circulation status and cardiovascular diseases.Second, we fabricate motion sensors by utilizing metallic glass, i.e., amorphous metallic alloy, which is an alloy composition without grain boundaries and long-range ordering. The unique structure of metallic glass results in excellent tensile strength and strain-resistivity as well as chemical stability to those of conventional metals. The Al-Sm MG-based sensors results in enhanced sensitivity and considerable device stability, because of its amorphous phase. [2][1] Adv. Funct. Mater. 2023, 10.1002/adfm.202309271[2] Electrochimica Acta, 2023, 446, 142053

Cobalt ferrite-embedded polyvinylidene fluoride electrospun nanocomposites as flexible triboelectric sensors for healthcare and polysomnographic monitoring applications

Human respiration is a vital physiological function of the body and a key metric for assessing overall health, particularly in conditions related to sleep deprivation. However, developing a real-time system for detecting sleeping position, heartbeat, and respiration is challenging yet crucial. Such a system should be easy to fabricate, comfortable to wear, and highly sensitive. In this study, we fabricated a flexible electrospun cobalt ferrite (CoFe2O4, CF) embedded polyvinylidene fluoride (PVDF) nanocomposite (NC) using an electrospinning technique. Additionally, we investigated the influence of varying CF content (0, 1, 3, and 5 wt%) on the crystalline β-phase in PVDF. The triboelectric nanogenerator (TENG) device was fabricated using PVDF-CF (P-CF) NC as the tribo-negative layer and non-woven fabric of thermoplastic polyurethane (TPU) as the tribo-positive layer. Among the four sample combinations used in this study, P-CF-3 (3 wt% CF in PVDF)/TPU TENG exhibited a significantly higher triboelectric open circuit voltage (Voc) of 5.8 V, nearly three times higher as compared to P-CF-0/TPU TENG (1.7 V). This work demonstrates an efficient method for enhancing the output efficacy of flexible TENG devices by varying the nanofiller concentration. Moreover, the fabricated TENG device was efficiently tested for real-time healthcare monitoring (HCM) and polysomnographic (PSG) related studies. This study aspires to provide a novel and pragmatic way of identifying real-time sleeping disorders and respiratory monitoring.

Conductive recycled PETg additive manufacturing filament for sterilisable electroanalytical healthcare sensors

Current reports of healthcare sensors within literature that use additive manufacturing electrochemistry all utilise conductive PLA, which is unsuitable for widespread use within the industry. Poly(ethylene terephthalate glycol (PETg) is a polymeric material with proven attributes for additive manufacturing due to its thermal and mechanical properties. Likewise, its excellent chemical stability transforms PETg into a desirable alternative for developing healthcare sensing devices. In this work, we report the production, physicochemical and electrochemical characterisations, as well as the electroanalytical performance of an enhanced electrically conductive additive manufacturing filament made with recycled poly(ethylene terephthalate glycol (rPETg) and a combination of carbon black, multi-walled carbon nanotubes and graphene nanoplatelets as conductive fillers. The post-print activation of additive manufactured electrodes from this material is optimised and shown to produce enhanced electrochemical performance compared to non-activated electrodes, with a k0 of 1.03×10−3 cm s−1. The sterilisation for the real application of sensors in the biomedical field is a critical point, the electrodes were submitted to standard UV light treatment showing to be reliable compared to PLA in the determination of uric acid (30–500 µM) and sodium nitrite (0.1–5 mM) within synthetic urine using differential pulse voltammetry and chronoamperometry techniques. A sensitivity and LOD for uric acid of 25.7 µA µM−1 and 0.27 µM, and 52.6 µA mM−1 and 2.69 µM for nitrite were obtained within synthetic urine, respectively. The re-useability of the electrodes was also tested for the detection of uric acid, showing that the electrode could be used up to 10 times before a significant decrease in the results was observed. We demonstrate that a new conductive rPETg with superior electrochemical performance has a prominent place within the development of additive manufactured-printed healthcare sensors due to its ability to be sterilised and re-used, low solution ingress, and its potential to tackle rising costs and plastic waste problems within the healthcare sector.

Highly Biocompatible Antibacterial Hydrogel for Wearable Sensing of Macro and Microscale Human Body Motions.

Flexible electronics, like electronic skin (e-skin), rely on stretchable conductive materials that integrate diverse components to enhance mechanical, electrical, and interfacial properties. However, poor biocompatibility, bacterial infections, and limited compatibility of functional additives within polymer matrices hinder healthcare sensors' performance. This study addresses these challenges by developing an antibacterial hydrogel using polyvinyl alcohol (PVA), konjac glucomannan (KGM), borax (B), and flower-shaped silver nanoparticles (F-AgNPs), referred as PKB/F-AgNPs hydrogel. The developed hydrogel forms a hierarchical network structure, with a tensile strength of 96 kPa, 83% self-healing efficiency within 60 minutes, and 128% cell viability in Cell Counting Kit-8 (CCK-8) assays, indicating excellent biocompatibility. It also shows strong antibacterial efficacy against Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus). Blue light irradiation enhances its antibacterial activity by 1.3-fold for E. coli and 2.2-fold for S. aureus. The hydrogel's antibacterial effectiveness is assessed by monitoring changes in electrical conductivity, providing a cost-effective alternative to traditional microbial culture assays. The PKB/F-AgNPs hydrogel's flexibility and electrical conductivity enable it to function as strain sensors for detecting body movements and facial expressions. This antibacterial hydrogel underscores its potential for future human-machine interfaces and wearable electronics.

2D Hybrid Perovskite Sensors for Environmental and Healthcare Monitoring.

Layered perovskites, a novel class of two-dimensional (2D) layered materials, exhibit versatile photophysical properties of great interest in photovoltaics and optoelectronics. However, their instability to environmental factors, particularly water, has limited their utility. In this study, we introduce an innovative solution to the problem by leveraging the unique properties of natural beeswax as a protective coating of 2D-fluorinated phenylethylammonium lead iodide perovskite. These photodetectors show outstanding figures of merit, such as a responsivity of >2200 A/W and a detectivity of 2.4 × 1018 Jones. The hydrophobic nature of beeswax endows the 2D perovskite sensors with an unprecedented resilience to prolonged immersion in contaminated water, and it increases the lifespan of devices to a period longer than one year. At the same time, the biocompatibility of the beeswax and its self-cleaning properties make it possible to use the very same turbidity sensors for healthcare in photoplethysmography and monitor the human heartbeat with clear systolic and diastolic signatures. Beeswax-enabled multipurpose optoelectronics paves the way to sustainable electronics by ultimately reducing the need for multiple components.

Privacy Preserving Authentication of IoMT in Cloud Computing

INTRODUCTION: The Internet of Medical Things (IoMT) blends the healthcare industry with the IoT ecosystem and enables the creation, collection, transmission, and analysis of medical data through IoT networking. IoT networks consist of various healthcare IT systems, healthcare sensors, and healthcare management software. OBJECTIVES: The IoMT breathes new life into the healthcare system by building a network that is intelligent, accessible, integrated, and effective. Privacy-preserving authentication in IoMT is difficult due to the distributed communication environment of heterogeneous IoMT devices. Although there has been numerous research on potential IoMT device authentication methods, there is still more to be done in terms of user authentication to deliver long-term IoMT solutions. However, password handling is one of the big challenges of IoMT. METHODS: In this paper, we present an IoMT-related online password-less authentication technique that is quick, effective, and safe. In order to offer cross-platform functionality, the article includes a simulation of FIDO2/WebAuthn, one of the most recent standards for a password-less authentication mechanism. RESULTS: This makes it easier to secure user credentials and improve them while preserving anonymity. The IoMT device authentication process and registration process delays are also assessed. CONCLUSION: Results and simulations show that the efficacy of the proposed mechanism with quick authentication on cloud servers may be accomplished with the fewest registration and authentication procedures, regardless of device setup.

Electrochemical detection platform based on graphene-zinc oxide composite nanomaterials for 17β-estradiol determination in milk

This research presents the development of an innovative electrochemical detection platform using a graphene-zinc oxide (G-ZnO) nanocomposite for the quantification of 17β-estradiol in milk. The G-ZnO nanocomposite, synthesized via a facile one-pot method, exhibited a unique wrinkled structure with a high specific surface area of 143 m²/g. Characterization through SEM, TEM, and XRD confirmed the effective integration of ultrafine ZnO nanoparticles onto graphene sheets. The electrochemical performance of the G-ZnO modified glassy carbon electrode was evaluated, revealing a notably low detection limit of 8.3 nM for 17β-estradiol, a significant improvement over traditional sensors. The sensor demonstrated a wide linear range of 0.05–100 μM and exceptional reproducibility with less than 3.5 % RSD over repeated measurements. Recovery studies in spiked milk samples yielded highly accurate results, with recovery percentages ranging from 97.8 % to 104.6 %. These findings underscore the potential of G-ZnO nanocomposites in creating sensitive, efficient, and reliable sensors for healthcare and environmental applications.

IoHT Based Tele-Healthcare Support System for Feasibility and Perfor-mance Analysis

With the rapid development in Internet of Things (IoT) it come up with the subbranch Internet of Healthcare Things or the Internet of Medical Things. With the help of portable healthcare sensors and the wearable devices now, ambulance can be converted into critical diagnostics unit on the wheels. Monitoring the home care patient is not the just part of IoT application where doctor can remotely monitor the patient situation by the means of sensors. It requires a complete system may called as telemedicine where multiple components will play similar priority role to monitor the patient status using sensors, let the doctor connect the patient, data analytics calculate the progression, AI engine will detect the emergency and act upon. The proposed system is to design and developing centralized tele-healthcare support system and systematic analytics sharing with multiple level of user with privacy protection. This will allow different authorities to take advantages from patient generated records.

A Low-Noise Low-Power 0.001Hz-1kHz Neural Recording System-on-Chip With Sample-Level Duty-Cycling.

Advances in brain-machine interfaces and wearable biomedical sensors for healthcare and human-computer interactions call for precision electrophysiology to resolve a variety of biopotential signals across the body that cover a wide range of frequencies, from the mHz-range electrogastrogram (EGG) to the kHz-range electroneurogram (ENG). Existing integrated wearable solutions for minimally invasive biopotential recordings are limited in detection range and accuracy due to trade-offs in bandwidth, noise, input impedance, and power consumption. This article presents a 16-channel wide-band ultra-low-noise neural recording system-on-chip (SoC) fabricated in 65nm CMOS for chronic use in mobile healthcare settings that spans a bandwidth of 0.001 Hz to 1 kHz through a featured sample-level duty-cycling (SLDC) mode. Each recording channel is implemented by a delta-sigma analog-to-digital converter (ADC) achieving 1.0 μ V rms input-referred noise over 1Hz-1kHz bandwidth with a Noise Efficiency Factor (NEF) of 2.93 in continuous operation mode. In SLDC mode, the power supply is duty-cycled while maintaining consistently low input-referred noise levels at ultra-low frequencies (1.1 μV rms over 0.001Hz-1Hz) and 435 M Ω input impedance. The functionalities of the proposed SoC are validated with two human electrophysiology applications: recording low-amplitude electroencephalogram (EEG) through electrodes fixated on the forehead to monitor brain waves, and ultra-slow-wave electrogastrogram (EGG) through electrodes fixated on the abdomen to monitor digestion.

Innovative Applications of Time-of-Flight Sensors in Smart Homes and Healthcare

Innovative Applications of Time-of-Flight Sensors in Smart Homes and Healthcare

Design and Development of Transient Sensing Devices for Healthcare Applications.

With the ever-growing requirements in the healthcare sector aimed at personalized diagnostics and treatment, continuous and real-time monitoring of relevant parameters is gaining significant traction. In many applications, health status monitoring may be carried out by dedicated wearable or implantable sensing devices only within a defined period and followed by sensor removal without additional risks for the patient. At the same time, disposal of the increasing number of conventional portable electronic devices with short life cycles raises serious environmental concerns due to the dangerous accumulation of electronic and chemical waste. An attractive solution to address these complex and contradictory demands is offered by biodegradable sensing devices. Such devices may be able to perform required tests within a programmed period and then disappear by safe resorption in the body or harmless degradation in the environment. This work critically assesses the design and development concepts related to biodegradable and bioresorbable sensors for healthcare applications. Different aspects are comprehensively addressed, from fundamental material properties and sensing principles to application-tailored designs, fabrication techniques, and device implementations. The emerging approaches spanning the last 5 years are emphasized and a broad insight into the most important challenges and future perspectives of biodegradable sensors in healthcare are provided.

Flexible, transparent and conductive wearable electronic skin based on 2D titanium carbide (MXene) ink

Flexible and transparent conductors are essentially required in epidermal wearable devices such as electronic-skins (E-skins) that facilitate human interaction and biofeedback. However, due to the “trade-off” effect between high electrical conductivity and optical transparency, it is difficult to obtain transparent E-skins with high electrical conductivity. Furthermore, traditional transparent conductor is bulky and brittle which is not suitable for flexible and wearable applications. Herein, ultrathin two-dimensional (2D) titanium carbide (MXene) nanosheets with metallic conductivity, hydrophilic surface and excellent mechanical flexibility was proposed as a novel high-performance transparent conductor, which was further developed as wearable E-skins. Solution-processable MXene conductive ink was obtained by facilely etching Al from MAX phase for large-scale spray coating to obtain flexible transparent conductors. The flexible, transparent, and conductive MXene-based electrodes own a sheet resistance as low as 200 Ω/sq, while with high optical transparency of 60% @550 nm, which is sufficient for the applications of E-skins. Moreover, the transparent MXene-based soft E-skins also exhibits outstanding mechanical flexibility which could maintain its high opto-electrical performance even after 1000 cyclic bending tests. In addition, the robust flexible transparent MXene-based E-skins also could accurately identify the movements of human body including approaching, touching and pressing, which is essentially required in various application scenarios such as human-machine interactions, touch panels and healthcare sensors. The solution-processable flexible, transparent and conductive MXene-based E-skins holds tremendous potential in emerging wearable applications.

Security and Privacy of Wearable Wireless Sensors in Healthcare: A Systematic Review

Wearable Wireless Sensor Network (WWSN) devices are widely used in healthcare to monitor health data. However, when WWSN users transmit their data to healthcare professionals or third parties over wireless connections, they face privacy and security vulnerabilities. This paper aims to identify the unsolved privacy and security challenges in wearable sensor devices in healthcare, especially the aspects overlooked by previous research. The main research question is: What are the unsolved privacy and security challenges in wearable sensor devices in healthcare, and what are their implications for users and healthcare professionals? This systematic review employs specific keywords to search for relevant publications on bibliographic databases, including Google Scholar, Scopus, IEEE Xplore, and Web of Science. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) charts helped in screening and summarising the selected papers. The results highlight the critical areas that can make WWSNs vulnerable to security attacks. The findings examine the security and privacy issues of wearable sensor devices in cloud computing, fog computing, the Internet of Things (IoT) and the like. Many studies examine IoT due to its privacy and security challenges, especially regarding handling extensive data, using public channels, deploying advanced technologies, managing sharing policies alongside the growing number of wireless devices, and protecting data from hackers. These challenges seriously threaten the confidentiality, integrity, and availability of health data transmitted by WWSN users to healthcare professionals or third parties in cloud-based environments and IoT and are exacerbated by limited resources. The significant findings thereby focus on unresolved areas in IoT. This paper aims to safeguard against cyber-attacks on healthcare and increase users' adoption rate of WWSN devices.

Flexible sensors with zero Poisson's ratio.

Flexible sensors have been developed for the perception of various stimuli. However, complex deformation, usually resulting from forces or strains from multi-axes, can be challenging to measure due to the lack of independent perception of multiaxial stimuli. Herein, flexible sensors based on the metamaterial membrane with zero Poisson's ratio (ZPR) are proposed to achieve independent detection of biaxial stimuli. By deliberately designing the geometric dimensions and arrangement parameters of elements, the Poisson's ratio of an elastomer membrane can be modulated from negative to positive, and the ZPR membrane can maintain a constant transverse dimension under longitudinal stimuli. Due to the accurate monitoring of grasping force by ZPR sensors that are insensitive to curvatures of contact surfaces, rigid robotic manipulators can be guided to safely grasp deformable objects. Meanwhile, the ZPR sensor can also precisely distinguish different states of manipulators. When ZPR sensors are attached to a thermal-actuation soft robot, they can accurately detect the moving distance and direction. This work presents a new strategy for independent biaxial stimuli perception through the design of mechanical metamaterials, and may inspire the future development of advanced flexible sensors for healthcare, human-machine interfaces and robotic tactile sensing.

An efficient three-factor authentication protocol for wireless healthcare sensor networks

An efficient three-factor authentication protocol for wireless healthcare sensor networks