Human Health Monitoring Research Articles

Facile Microwave-Assisted Growth of 3D ZnVO Nanomarbles on Graphene Oxide Nanosheets for Simultaneous Detection of Ascorbic Acid, Dopamine, and Uric Acid

Simultaneous detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA) is challenging due to close oxidation potential. These biomolecules lie in the human body and have significant roles in many psychological reactions. A slight change in the concentration of these molecules can cause serious health issues; in this context, accurate and timely detection holds significant value in clinical diagnostics. This work demonstrates the synthesis of 3D zinc nanomarbles on 2D graphene oxide sheets using a rapid and environmentally friendly microwave-assisted technique. The porous morphology with thin nanomarbles where (2 2 0) reactive sites were exposed to the environment with enhanced surface area measured 38.29 m2 g-1. The composite ZnVO/rGO has been employed on glassy carbon electrodes, resulting in superior electrocatalytic properties that enable the simultaneous detection of these analytes with wide potential gaps. Notably, the ZnVO/rGO/GCE exhibits simultaneous detection with a working range of AA (100 µM-1000 µM), DA (10 µM-100 µM), and UA (10 µM-100 µM). The detection limits were estimated to be 4.3µM, 0.7µM, and 0.32µM, respectively. The ZnVO/rGO/GCE sensor demonstrates remarkable stability, selectivity, reproducibility, and satisfactory recovery during real sample analysis. The high surface area, porous nature, and thin size of 3D nanomarbles enhance charge transportation, making it promising for electrochemical performance. This study lays the foundation for future advancements in human health monitoring by introducing a novel approach.

Pasteables: A Flexible and Smart “Stick-and-Peel” Wearable Platform for Fitness and Athletics

Wearable technologies are becoming increasingly popular and transforming our fitness and sports industry. Monitoring health parameters and body activity can help achieve fitness goals, improve sports performance, and aid in physiotherapy. However, state-of-the-art wearable devices are often not flexible, expensive, hard to set up, or have privacy concerns. They are designed and optimized for a specific application with tight hardware-software integration and it is hard or impossible to re-purpose them for diverse use cases. In this paper, we propose a flexible, re-configurable human body movement and health monitoring platform, called "Pasteables". It is a stick-and-peel device (which acts like a band-aid) that attaches to the skin or clothing and can create an on-body network of smart wearables. Given an application, Pasteables can be easily adapted to its requirements while ensuring good performance and privacy. We present the overall architecture, system design steps, and the configuration process. We have designed a set of functional prototypes and configured them for performing a variety of camera-less pose and posture detection tasks, which are important for athletes, professional dancing, physiotherapy, and fitness workouts. We note that the Pasteables can perform pose/posture detection without external stationary reference at low cost and high accuracy.

Highly sensitive and stretchable CB/GNPs-TPU strain sensor with porous microstructure for multifunctional strain sensing

Multifunctional flexible strain sensors have garnered significant attention in recent years, particularly in the fields of smart wearable devices and human health monitoring. However, the trade-off between high sensitivity and a wide strain range limits their practical applications. This study presents a porous TPU/CB framework prepared using a water vapor-induced phase separation method, which can deform like a spring when stretched, thereby providing the sensor with a greater strain range. The graphene nanoplatelets (GNPs) were subsequently incorporated into the pores of the porous framework through ultrasonic treatment, which enhanced the sensor's sensitivity while preventing increased brittleness caused by the aggregation of conductive fillers. This structure establishes a stable conductive network, enabling the sensor to achieve high sensitivity (GF = 5902.4) across a wide strain range (327 %) while also demonstrating excellent stability and durability (over 7000 stretching/releasing cycles). The sensor can detect not only simple limb movements, such as bending of the arms and knees but also subtle muscle activities, including facial expressions and throat vocalization, thus bringing excellent human-computer interaction experience. These remarkable features position the sensor for promising applications in smart wearables and human health monitoring.

Highly Stretchable Strain Sensor with Both an Ultrawide Workable Range and an Ultralow Detection Limit for Human Health Monitoring

Highly Stretchable Strain Sensor with Both an Ultrawide Workable Range and an Ultralow Detection Limit for Human Health Monitoring

Design and Development of a Wearable Device for Multi-Parametric Human Health Monitoring

INTRODUCTION: Wearable technology has emerged as a promising tool for continuous health monitoring, offering potential disease prevention and management benefits. However, existing devices often provide limited physiological data, hindering comprehensive health assessments.OBJECTIVES: This study aims to design and develop a wearable device capable of multi-parametric human health monitoring, focusing on vital indicators such as heart rate, body temperature, and physical activity.METHODS: A modular design approach was employed to integrate multiple biosensors into a compact wearable device. The collected data was processed by a microcontroller and transmitted wirelessly to a server.RESULTS: The developed wearable device demonstrated accurate and reliable measurement of target health parameters, with results comparable to existing prototypes in terms of functional capabilities.CONCLUSION: The proposed wearable device holds significant potential for enhancing personal health management by providing comprehensive and real-time health data. Future research will focus on expanding the device's capabilities, improving battery life, and conducting long-term user trials.

PVDF/NiFe2O4 multiferroic composite membranes for dual mechanical and magnetic energy harvesting devices

A multiferroic composite membrane, combining PVDF piezoelectric polymer and nickel ferrite (NFO) nanofibers, was successfully fabricated and studied as an active material layer in multifunctional devices designed to harvest both mechanical and magnetic energy. Optimization of the manufacturing process ensured an even distribution of NFO fibers within the PVDF matrix, enhancing the crystallization of PVDF in the electroactive β phase. The resulting PVDF/NFO multiferroic films exhibited both piezoelectric and magnetic properties, along with a pronounced magnetoelectric (ME) effect. In a structure comprising Al/PVDF-NFO/PDMS/Al, the device operated as a piezoelectric generator (PEG) under a pressing force of 0.5 MPa, achieving a maximum output power density of 14.7 μW cm−12 with a peak-to-peak voltage of 12.2 V. When subjected to an AC magnetic field of 20 Oe at 50 Hz, the device functioned as a magneto-mechano-electrical (MME) generator, producing a sinusoidal waveform voltage of 486 mV. The cost-effective and easily integrable PVDF/NFO composite membrane presents promising opportunities for developing flexible, self-powered smart sensors for human health monitoring systems and implantable biomedical devices.

Tear-Based Ocular Wearable Biosensors for Human Health Monitoring.

Wearable tear-based biosensors have garnered substantial interest for real time monitoring with an emphasis on personalized health care. These biosensors utilize major tear biomarkers such as proteins, lipids, metabolites, and electrolytes for the detection and recording of stable biological signals in a non-invasive manner. The present comprehensive review delves deep into the tear composition along with potential biomarkers that can identify, monitor, and predict certain ocular diseases such as dry eye disease, conjunctivitis, eye-related infections, as well as diabetes mellitus. Recent technologies in tear-based wearable point-of-care medical devices, specifically the state-of-the-art and prospects of glucose, pH, lactate, protein, lipid, and electrolyte sensing from tear are discussed. Finally, the review addresses the existing challenges associated with the widespread application of tear-based sensors, which will pave the way for advanced scientific research and development of such non-invasive health monitoring devices.

Magnetron sputtering preparation of flexible ZnO/AlN thin-films sensors with hybrid piezoelectric effect for broad-range human motions detection

Wearable sensors with excellent comfort, flexibility and fast response are widely applied in human-machine interactions, artificial skin, motion detection and healthcare monitoring. However, preparation processes of the most of current piezoelectric sensors are relatively expensive and complicate, limiting their mass productions in the applications. This work demonstrates the superior piezoelectric performance and stability of ZnO/AlN flexible thin films prepared by magnetron sputtering for broad-range human motions detection, and first-principles calculation are applied to reveal the complicate piezoelectric effect of the hybrid system. The ZnO/AlN hybrid thin films sensor exhibits superior piezoelectric performance and excellent reliability, with presenting high outputs voltage (3.63 V), high degree of response speed (42.33 ms), water stability and robust performance upon 10000 cycles. First-principles calculations reveal that formation of the ZnO/AlN interface facilitates charge transport and improves efficiency of carrier transport, and results in reduced in band gap and enhanced electrical conductivity. By applying the sensors in human health monitoring, the underlying behaviors can be determined by output voltage of the sensor in real-time. This work offers a sensitive, simple structured and robust solution for human motion detection.

Deep‐Learning‐Based Prediction of Long‐Term Piezoresistive Sensing Performance of MXene/Aramid Nanofiber Sensors

Flexible compressible sensors are widely used in the human health monitoring field for their numerous advantages. However, the dynamic loads and possible injuries associated with long‐term living and exercise pose a challenge to the long‐term piezoresistive performance stability of these sensors. In this study, the application of deep learning for predicting the long‐term performance of these sensors is explored, aiming to enhance the assessment of sensor stability and ensure accurate and reliable long‐term monitoring. Samples with different Ti3C2Tx MXene/aramid nanofiber mass ratios (1:1, 1:2, 1:3) are prepared and piezoresistive characterization is conducted under long‐term loading cycles to obtain training data. Three distinct deep‐learning prediction models, convolutional neural network (CNN), long short‐term memory, and recurrent neural network (RNN), are utilized to assess their influence on prediction accuracy. To assess the effectiveness of the proposed method, its prediction of long‐term piezoresistive sensing performance with experimental data not used for training purposes is compared. The CNN model demonstrates optimal results with a mean absolute error of 0.0251 for the 1:3 mass ratio sample. Based on the experimental results, the model is expected to be integrated into human health monitoring systems, thus improving the assessment of sensor stability throughout its lifetime.

Wet stability soft skin electronic sensor based on biochar-polypyrrole conductive hydrogel

Hydrogels have the softness and stretchability of similar tissues and are considered as materials for smart flexible electronic devices. However, the durability and reliability of most polypyrrole hydrogels in wet environments are still insufficient, especially its wet stability in the wet environment of seawater, limiting its development as flexible conductive electrodes. In this study, the porous solid carbon material after pyrolysis of natural materials is introduced into hydrogel, which is conducive to the migration and propagation of electrolyte ions, and can improve the moisture resistance stability of hydrogel. At the same time, polypyrrole material is introduced to further improve its electrical conductivity. With this method, the conductivity of conventional hydrogel materials can be increased by 12.2 times. The triboelectric nanogenerator device prepared with polypyrrole/biochar composite hydrogel can not only accurately monitor human joint motion, but also easily light up at least 300 light-emitting diodes when rubbed with aluminum materials, which proves the practical performance of the device. This study provides an alternative material for sensing hydrogels that can be used for human health monitoring of marine operators.

Air plasma fast-induced defect-enriched carbon cloth for simultaneous electrochemical detection of dopamine and uric acid

Herein, we report a fast (10 min) and simple surface treatment of pure carbon cloth (CC) only by an air plasma. The structural characterizations indicate that the air plasma process brings out higher rugosity, more defects, and increased oxygen-related groups on CC surfaces than Ar- or N2-plasma, which can offer abundant capture sites, large electroactive area, and superhydrophilic interface for analytes. As a result, the air-treated CC (CC−PAir) electrode achieves a pronounced improvement of electrocatalytic activity for the [Fe(CN)6]3-/[Fe(CN)6]4- probe evidenced by increased peak currents, decreased peak-to-peak separation, and the lowered resistance of charge transfer. It is also demonstrated that the self-supported CC−PAir electrode possesses excellent sensing performance toward dopamine (DA) and uric acid (UA). The feasibility of the simultaneous electrochemical detection of DA and UA can be verified by their large peak potential gap (∼112 mV) for differential pulse voltammetry. The chronoamperometric sensor yields wide linear ranges of 0.05–100 μM for DA and 0.5–300 μM for UA. The corresponding detection limits are estimated to be 2.6 and 20.4 nM for DA and UA, respectively. The sensor also displays satisfactory selectivity, stability, and reproducibility. Due to good flexibility, the CC−PAir electrode presents great potential for manufacturing wearable and soft electronics for human health monitoring.

High mechanical, self-adhesive oxidized guar gum/chitosan hydrogel prepared at room temperature based on a nickel-urushiol catalytic system for wireless wearable sensors

Recently, sensors constructed on the basis of hydrogel are playing a major role in health detection such as motion detection and breathing monitoring. However, the common hydrogels have poor mechanical properties, insufficient adhesion and complex preparation processes, which hinder the further use of such sensors. In this paper, the conductive hydrogel (P(AA-UH)-OGG-CS/NiCl2) composed of acrylic acid (AA), oxidized guar gum (OGG) and chitosan (CS) was prepared at room temperature through the dynamic redox reaction of nickel chloride (NiCl2) and urushiol (UH). In detail, the reduction group (phenolic hydroxyl) of UH and Ni2+/Ni3+ pair form a semi-quinone/quinone redox dynamic cycle system, allowing the hydrogel to quickly gel at room temperature for 3 min. The catechol group in UH also promotes the hydrogel to have a superior adhesion strength of 25.23 kPa to pig skin and a strong repeated adhesion performance. In addition, the dynamic Schiff base bond created by the interaction of OGG and CS elevated the tensile stress of the hydrogel to 67.54 kPa. After the hydrogel is assembled into the sensor, it has high sensitivity and high stability to different strains, and has great application prospects in the field of actual human health monitoring.

Ultra-stretchable, robust, self-healable conductive hydrogels enabled by the synergistic effects of hydrogen bonds and ionic coordination bonds toward high-performance e-skins

Ionic conductive hydrogels as electronic skins (e-skins) have showcased pivotal potentials in the realm of human health monitoring and human–machine interfaces. However, developing intelligent hydrogel with remarkable stretchability and mechanical elasticity is yet challenging. Herein, high-performance ion-conducting hydrogels with unprecedented mechanical properties and good transparent, conductive, self-healing properties are constructed via free-radical polymerization of acrylic acid (AA) within the polyvinyl alcohol (PVA) network, and the subsequent freeze–thaw (F-T) treatment and Zr4+ ion immersion crosslinking technique. Profiting from the synergy of multiple intermolecular/intramolecular hydrogen bonds between different polymers and coordination bonds of carboxyl-Zr4+, the resultant PVA/PAA/Zr4+ hydrogel exhibits high transparency (∼97 %), superior conductivity (0.6089 S/m), a long elongation at break (2053 %), robust self-healing efficiency (96.3 %), high deformation-tolerate property, and notable mechanical repeatability. These multifaceted attributes render the hydrogel to serve as an ionic conductor for capacitive/resistive −type strain sensor. The hydrogel-based resistive-type strain sensor features a wide detection range (0.5 %-800 %), rapid response time (150 ms), long-term stability, and consistent output stability, making it promising in monitoring diverse human motions and seamless human–machine interactions. Additionally, the hydrogel sensor demonstrates excellent linear response in ultra-wide range (0–900 % strain), high sensitivity, and excellent cycling stability in a capacitive mode, enabling to be used for accurately detecting the weights of objects. As such, this work advances the development of ionic conductive hydrogel as flexible and wearable electronic devices.

Multifunctional and flexible sensor based on PU-supported Au/VTe2/Ti3C2Tx yarns for human motion and NO2 detection

Given the considerable harm that NO2 poses to the environment and human health, developing reliable NO2 detection sensors is crucial. Herein, a flexible, multifunctional sensor was successfully synthesized through hydrothermal and the wet impregnation methods using an elastic PU yarn as the substrate. This sensor, named Au/VTe2/Ti3C2Tx–PU, was characterized via X-ray diffraction, X-ray photoelectron spectroscopy, and scanning electron microscopy to analyze its structure, chemical valence states, and micromorphology. At room temperature (23 °C), the sensor demonstrated an exceptionally high response to NO2 gas, with a response value of 1.72 at 50 ppm as well as low response and recovery time of 33 and 38 s. Additionally, testing of the strain performance of Au/VTe2/Ti3C2Tx–PU showed that this flexible sensor exhibits high strain sensitivity, excellent repeatability, and durability, making it suitable for detecting subtle human movements. Overall, the synthesized sensor is in considerable advantages in terms of both gas-sensing performance and tensile performance, exhibiting broad application prospects in human motion and health monitoring.

Microstructured CNTs/Cellulose Aerogel for a Highly Sensitive Pressure Sensor.

Flexible sensors have been applied in human health monitoring and biomedical research, but producing high-performance piezoresistive sensors at low cost is still challenging. To address these shortcomings, we proposed a microstructured carbon nanotube (CNT)/cellulose aerogel-based pressure sensor. The sensor consists of three parts, i.e., cellulose/poly(vinyl alcohol)/CNT aerogel-based sensing layer and top and bottom thermoplastic polyurethane elastomer (TPU)/silver nanowire (Ag NW) nanofiber electrode. The aerogel is fabricated using a simple freeze-drying method and an easy electrospinning method to obtain the nanofiber-based electrode. Two TPU/Ag NW nanofiber electrodes sandwiched the aerogel with a microstructure in the middle. Benefiting from the microcone and micropore structures on the nanofiber electrode, the assembled sensors show a high sensitivity of 66.4 kPa-1, a significant detection boundary of 50 kPa, and an excellent response speed of 10 ms. The high sensing performance enables the sensor to monitor physiological signals, Morse code interactions, and gesture recognition. With the help of machine learning, the success rate of gesture recognition is as high as 98.8%. The preparation of this pressure sensor based on an aerogel shows excellent health and environmental monitoring potential as an artificial skin.

Fiber Bragg Grating Pulse and Systolic Blood Pressure Measurement System Based on Mach-Zehnder Interferometer.

A fiber Bragg grating (FBG) pulse and systolic blood pressure (SBP) measurement system based on the edge-filtering method is proposed. The edge filter is the Mach-Zehnder interferometer (MZI) fabricated by two fiber couplers with a linear slope of 52.45 dBm/nm. The developed system consists of a broadband light source, an edge filter, fiber Bragg gratings (FBGs), a coarse wavelength-division multiplexer (CWDM), and signal-processing circuits based on a field-programmable gate array (FPGA). It can simultaneously measure pulse pulsations of the radial artery in the wrist at three positions: Cun, Guan and Chi. The SBP can be calculated based on the pulse transit time (PTT) principle. The measurement results compared to a standard blood pressure monitor showed the mean absolute error (MAE) and standard deviation (STD) of the SBP were 0.93 ± 3.13 mmHg. The system meets the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) equipment standards. The proposed system can achieve continuous real-time measurement of pulse and SBP and has the advantages of fast detection speed, stable performance, and no compression sensation for subjects. The system has important application value in the fields of human health monitoring and medical device development.

Three-dimensional interconnected nanofiber network derived from bacterial cellulose for strain sensing and energy harvesting

Flexible strain sensors have garnered widespread attention due to their potential applications, including human health monitoring, human-machine interfaces and intelligent robotics. However, the tradeoff between sensitivity and detection range needs to be considered. Herein, a dual-functional film based on bacterial cellulose is fabricated with a cost-effective freeze-drying and carbonization process, which is used for strain sensing and energy harvesting. The effect of the carbonization temperature on the structure is explored. Taking advantage of three-dimensional interconnected nanofiber of carbonized bacterial cellulose (CBC) network and the stretchability of the Ecoflex substrate, the optimized sensor demonstrates impressive strain sensing capabilities, featuring exceptional sensitivity (gauge factor = 100), large tolerable strain (100 %), swift response time (70 ms), and robust durability (3000 cycles). These features endow the CBC strain sensor with the capability to effectively discern and monitor multiple complex human activities, such as pulse rate and various human movements. Moreover, the CBC structure can serve as triboelectric nanogenerator (TENG) for energy harvesting. This work provides a green, efficient and cost-effective manufacturing method for the development of multifaceted wearable devices for human health monitoring and portable energy sources.

Flexible intelligent fabric composed of pinecone-like microstructure Co-cMOFs/CoZnAl-LDH composite nanomaterial for various types of sensor signals to guide personalized health activities

Multifunctional interfacing is a key aspect of flexible sensor development that facilitates enhanced interaction with the natural environment. However, challenges faced by contemporary multifunctional flexible sensors are structural complexity and high cost. Herein, inspired by the specific structure of pinecone in nature and the microstructured neural networks randomly distributed within human skin, we fabricated Co-cMOFs/CoZnAl-LDH composite nanomaterials with pinecone-like microstructure. Through the mutual verification of finite element simulation and experimental data, the mechanism of high sensitivity of the sensor is dynamically revealed from the structural point of view. The prepared pressure sensors exhibit a detection range (0–120 kPa), high sensitivity (2.35 × 109 kPa−1) and fast response. The photoelectric sensor shows enhanced photoelectric energy conversion, which shows great potential in the detection of sunlight intensity (20–100 mW cm−2). Simultaneously, building a hybrid pressure, acoustic and optical sensing platform and validating its superior performance in human movement and health monitoring applications. Furthermore, a strategy of light intensity feedback system to guide personalized health activities is put forward, so that doctors can guide patients/elderly health activities remotely.

Self‐Powered and 3D Printable Soft Sensor for Human Health Monitoring, Object Recognition, and Contactless Hand Gesture Recognition

AbstractA new galvanic cell design of a self‐powered and 3D‐printable soft sensor showing health monitoring, object recognition, and contactless hand gesture recognition, is reported. The soft sensor consists of a 3D‐printed poly(acrylic acid) (PAA) hydrogel electrolyte layer, a soft anode layer, and a soft cathode layer. The anode layer is a 3D‐printed and Cu2+ cross‐linked poly(N,N‐dimethylacrylamide‐co‐3‐alanine‐2‐hydroxypropylmethacrylate) (PDA) hydrogel dispersed with Cu metal particles (PDA/Cu2+/Cu hydrogel), while the cathode layer is a bottom thin layer of the PAA hydrogel containing MnO2 (PAA/MnO2). Using graphite films as the soft electrodes, the soft sensor is finally assembled. The soft sensor has high force and temperature sensitivities. It gives different electric current responses under stretching, bending, pressing, and impact loading. The soft sensor is demonstrated to be useful in detecting human motion and physiological activities, e.g., breath. Based on the force and contactless temperature sensitivities, the soft sensor is used to recognize human hand gestures and plastic balls with different diameters. This 3D printable soft sensor with self‐powering, contactless motion capturing, and multi‐pimulus sensing capabilities illustrates a new pathway to make soft sensory devices for healthcare and human‐machine interaction applications.

A non-enzymatic flexible and wearable sensor based on thermal transfer printing technology for continuous glucose detection in sweat

Non-invasive, flexible wearable sensors are an important method to continuously measure glucose in sweat for diabetes and human health monitoring and management. However, how to create an alkaline environment at any time so that CuO based sensors can be applied to wearable devices to detect sweat glucose while finding a way to efficiently and quickly produce the sensors in small batches have been a challenge. Herein, we report a non-enzymatic thermal transferred flexible and wearable sensor based on CuO/CaTiO3 for continuous glucose detection in sweat. The sensor is manufactured using thermal transfer printing technology, which offers advantages like low cost, ease of operation, and rapid small batch production. CuO is known for its excellent electrocatalytic activity, making it a suitable candidate for glucose oxidation. Meanwhile, CaTiO3 particles provide a large specific surface area, good biocompatibility, and electrical conductivity, which enhance the electron transfer rate during detection and broaden the linear range of glucose detection. Specially designed NaOH/Nafion/PEO blend film make the measurements always in a strong alkali environment without any pretreatment and preparation. The synthesized material with this as-prepared flexible and wearable sensor exhibits superior performance towards glucose monitoring, such as high sensitivity of 487.3 μA mM−1 cm−2 with limit of detection(LOD) 0.75 μM, wide dynamic linear range from 0.01 mM to 2 mM and fast response time of less than 0.1 s. Additionally, the proposed sensor also exhibited excellent biocompatibility, selectivity, reproducibility and flexibility, as well as good stability with about 88 % of its initial activity after 5 weeks’ storage and it has been successfully applied for the detection of glucose concentration in human sweat real samples. This research contributes to the development of flexible and wearable sensors for non-invasive sweat diagnostics, enabling continuous glucose monitoring for various applications in healthcare and wellness.