Wearable Sensors Research Articles

Silver oxide integrated ionic polymer composite for wearable sensing and water purification

Integrating metal nanoparticles (NPs) with ionic polymer blends/composites showed immense interest for their potential in wearable sensors, soft robotic arms, flexible man-machine interfaces of biomedical devices, and water purification applications. However, conventional NPs attached ionic polymer composites exhibit limitations such as low sensitivity (ΔR/R), low total dissolved solids (TDS) reduction, and low phosphate (PO4-P) removal rate. Herein, ionic polymer composites (IPCs) using flower-shaped silver oxide (Ag2O) attached Poly (vinylidene fluoride) (PVDF)/ polyvinylpyrrolidone (PVP)/ionic liquid (IL) were designed and developed for wearable sensing and water purification. The IPCs demonstrated remarkably high ΔR/R values of 50, 10, and 3.5 corresponding to the wrist movement of 50°, finger movement of 180°, and chin movements respectively. The Ag2O-based IPC recorded a significant reduction of TDS from sewage water from 3405 ppm to 1035 ppm, elevated the dissolved oxygen (DO) levels in the sewage water from 1.2 mg/l to 6.8 mg/l, and removed approximately 87.38 % phosphate from sewage water. Due to the uniform distribution of Ag2O within pores of IPC, it demonstrated enhanced performance for wearable and wastewater treatment applications.

Hydrogel Sensors in an IoT System for Self-Monitoring and Remote Monitoring of Massage Pressure.

The effectiveness of massage can be enhanced if the pressure applied can be monitored continuously. In this study, we described an Internet-of-Things (IoT) system based on hydrogel sensors, which allows for self-monitoring and remote monitoring of massage pressure. The piezoresistive hydrogel with the compressive energy loss coefficient of 15.7% was developed, which was attributed to the strong polarization of ammonium phosphate on water molecules, which was evidenced by nuclear magnetic resonance (NMR) transverse relaxation analyses and atomic force microscopy. Using this hydrogel as a pressure-sensing component, we assembled a wearable sensor capable of quantifying and transmitting massage pressure with insignificant energy dissipation. By integrating RGB LED arrays, the message pressure was indicated by the color states of the LEDs. Furthermore, the wearable sensors and LEDs were connected to a microcontroller (MCU) chip, an IoT chip, and a cloud server to form a sensing-controlled IoT system, enabling visible and remote monitoring of massage pressure.

Fe(OH)3/Ti3C2Tx nanocomposites for enhanced ammonia gas sensor at room temperature

Two-dimensional material (2D material) MXene has great application potential in gas sensors because of its excellent controllable performance and vast specific surface area. In this study, we used a straightforward in-situ electrostatic self-assembly technique to create Fe(OH)3/Ti3C2Tx nanocomposites, which were then used to fabricate gas sensors for ammonia detection at room temperature (25 ℃). Several characterization methods were performed aimed at determining the surface appearance and construction of the nanocomposites, and the sensing characteristics and mechanism were also systematically examined. The findings demonstrate the effective incorporation of amorphous Fe(OH)3 nanoparticles on the surface of Ti3C2Tx. Additionally the nanocomposites of Fe(OH)3/Ti3C2Tx have considerably higher specific surface area than pure Ti3C2Tx, hence offering more active NH3 adsorption sites. The response of the sensor to 100 ppm NH3 was 48.6% at room temperature, which was 9.3 times more higher than that of pure Ti3C2Tx. The sensors also have the advantages of long-term stability (33 days), low NH3 detection limit (500 ppb), and rapid recovery time (85 s) and response times (78 s). It is anticipated that this work will be helpful for developing the new generation of wearable ammonia sensors at room temperature.

In-situ cured gel polymer/ecoflex hierarchical structure-based stretchable and robust TENG for intelligent touch perception and biometric recognition

Gel-based sensors for next generation touch panels have been acknowledged for their exceptional sensitivity and flexibility. However, these sensors typically depend on a metal grid connection, which is susceptible to structural deformation under heavy stress applications and necessitates external power. Here, we report a novel in-situ cured gel polymer electrode-based triboelectric nanogenerator (GPE-TENG) that is stretchable, semi-transparent, and durable, designed to enable a self-powered touch panel for intelligent touch perception. The in-situ curing of the hierarchical structure of the ionic polymer gel encapsulated within the ecoflex ensures robust adhesion of the ionic conductive polymer gel (PEO/LiTFSI) to the ecoflex layers, addressing the issue of delamination in TENG components under mechanical stress. As a result, the GPE-TENG demonstrates high durability, enduring under stretching of approximately 375 % and sustaining heavy mechanical deformations (under folding, twisting, and rolling) over a long period (approximately 2 months) without loss of functionality. Remarkably, the GPE-TENG exhibits outstanding energy harvesting capabilities with a peak power density of 0.36 W m-2. Notably, the GPE-TENG generates electrical signals through simple device stretching, thus serving as a self-powered wearable sensor for human activity monitoring. Moreover, a 9-digital arrayed (3 × 3) flexible, semi-transparent, and self-powered touch panel based on the GPE-TENG shows multifunctionality, including touch track/pattern recognition (i.e. touch and sliding mode) and a highly accurate (∼98 %) deep learning assisted smart biometric system for user identification.

Room temperature self-healing and reprocessing elastomer with dynamic bonds for flexible wearable sensor

The production of room-temperature (RT) self-healing elastomers with good mechanical properties is significant for application in soft electronics, yet remains a challenge in material design. Herein, we present an effective and feasible approach to create RT self-healing cross-linked elastomers (CEs) through photo-initiated copolymerization. A key feature is the incorporation of 2,7-dihydroxynaphthalene and alicyclic diisocyanate into the polymer backbone as hard domains, along with the rational optimization of the soft segments. In addition, urethane-based H-bonding interactions, acting as sacrificial bond, contribute to the high toughness of the CEs. The resulting CEs exhibit desirable mechanical performances, including a tensile strength of 12.9 MPa, an elongation at break of approximately 1243 %, and a high toughness of 68.64 MJ m–3. Furthermore, by integrating a flexible PTMEG-based polymeric chain and hindered urea bonds into the backbone, the chain mobility and dynamic nature of the CEs are improved. The CEs are capable of reprocessing and self-healing at RT within 30 min upon scratching, with a self-healing efficiency in toughness reaching 99.64 %. The dynamic networks are evidenced by rheological test, stress relaxation analysis, as well as creep and recovery experiments. These CEs, characterized by their superior properties, hold promise for applications in flexible wearable electronics.

Metal Organic Frameworks Based Wearable and Point-of-Care Electrochemical Sensors for Healthcare Monitoring.

The modern healthcare system strives to provide patients with more comfortable and less invasive experiences, focusing on noninvasive and painless diagnostic and treatment methods. A key priority is the early diagnosis of life-threatening diseases, which can significantly improve patient outcomes by enabling treatment at earlier stages. While most patients must undergo diagnostic procedures before beginning treatment, many existing methods are invasive, time-consuming, and inconvenient. To address these challenges, electrochemical-based wearable and point-of-care (PoC) sensing devices have emerged, playing a crucial role in the noninvasive, continuous, periodic, and remote monitoring of key biomarkers. Due to their numerous advantages, several wearable and PoC devices have been developed. In this focused review, we explore the advancements in metal-organic frameworks (MOFs)-based wearable and PoC devices. MOFs are porous crystalline materials that are cost-effective, biocompatible, and can be synthesized sustainably on a large scale, making them promising candidates for sensor development. However, research on MOF-based wearable and PoC sensors remains limited, and no comprehensive review has yet to synthesize the existing knowledge in this area. This review aims to fill that gap by emphasizing the design of materials, fabrication methodologies, sensing mechanisms, device construction, and real-world applicability of these sensors. Additionally, we underscore the importance and potential of MOF-based wearable and PoC sensors for advancing healthcare technologies. In conclusion, this review sheds light on the current state of the art, the challenges faced, and the opportunities ahead in MOF-based wearable and PoC sensing technologies.

Challenges and opportunities in sensor-based fall prevention for older adults: a bibliometric review

PurposeThis bibliometric review examines the recent literature on sensor-based fall prevention for older adults. It analyzes publication trends, key researchers and institutions, major research themes, as well as gaps and opportunities in this field.Design/methodology/approachA comprehensive search was conducted in Scopus and Web of Science (WoS) databases for publications from 1990 to 2024. Bibliometric indicators including publication output, citation analysis and co-occurrence of keywords were used to map the research landscape. Network visualizations were employed to identify key thematic clusters.FindingsThe research on sensor-based fall prevention has grown rapidly, peaking in 2019. The USA, Australia and Canada lead this work, with universities and hospitals collaborating globally. Key themes include fall epidemiology, wearable sensors and AI for fall detection. Opportunities exist to better implement these sensor systems through large trials, user-centered design, hybrid sensors and advanced analytics.Research limitations/implicationsWhile comprehensive, the analysis focused primarily on publications indexed in Scopus and WoS, which may not capture all relevant literature. Future studies could expand the search to include other databases and conduct deeper analyses of highly influential studies.Practical implicationsThe review provides an evidence-informed roadmap to accelerate the translation of sensor innovations into scalable and sustainable fall prevention practices for vulnerable older adult populations.Originality/valueThis is the first comprehensive bibliometric analysis to map the research landscape of sensor-based fall prevention, identifying key trends, themes and opportunities to advance this critical domain addressing a major global public health challenge.

Preparation of aerogels with SBS@rGO structure by Pickering emulsion method for innovative applications in pressure sensors

Pressure sensors based on graphene conductive fillers show great promise for application in the field of smart wearable devices. The SBS@rGO structured aerogel sensors covered herein were prepared by the Pickering emulsion method based on a solution of styrene-butadiene-styrene (SBS) and reduced graphene oxide (rGO) dispersion. The mechanical properties of SBS@rGO aerogel were tested with 100 independent loading-unloading cycles in a graded compressive strain range of 10–40 %. The results indicate that the SBS@rGO aerogel have fast and slightly destructive resilience after unloading at low compressive strains (ε ≤ 30 %). Moreover, the presence of rGO endowed SBS@rGO with pressure sensing properties such as high electrical conductivity (2.294 S/m), high sensitivity (0.016 kPa−1 at 6.36–100 kPa), short signal response time (60 ms) and recovery time (30 ms). The SBS@rGO pressure sensors were integrated into shoe soles to simulate walking scenes, whose response signals had excellent reproducibility and could be differentiated according to three different walking states. The potential and feasibility of SBS@rGO aerogel as wearable flexible pressure sensors has been demonstrated.

Unique framework effect induced by uniform silk fibroin dynamic nanospheres enables multiscale hydrogel with outstanding elastic resilience and strain sensing performance

It is a significant challenge to obtain hydrogels simultaneously with low tensile energy dissipation, high compressive resilience and long durability. Herein, the uniform dynamic nanospheres (Sil-4H0.75) derived from 4-Hydroxybutyl acrylate glycidyl ether grafted silk fibroin is designed to overcome this issue. Due to its uniform and dynamic characteristic, Sil-4H0.75 could endow hydrogel with homogeneous multiscale structure and produce unique framework effect. Thus, transparent Sil-4H0.75 crosslinked acrylamide hydrogel doped with Ag nanowires APS3.75%/AgNW0.1 exhibits a high stretchability (1260 %) and outstanding elastic resilience. The tensile energy dissipation ratio maintains a low value of 9 % across a wide 800 % strain range. A high compression resilience ratio of 92.2 % is kept after ten compression cycles under 90 % compressive strain. The orderly AgNWs motion guided by framework effect also make it be used as both tensile and compressive sensors and exhibits high gauge factor of 7.35, outstanding compression sensitivity of 30.379 kPa−1 and excellent durability (up to 2000 cycles). The detection or other applications based on both two sensing modes are also demonstrated. In a word, this work affords a general strategy to achieve high-performance hydrogel based on uniform dynamic nanospheres which exhibits great potential in the applications of flexible wearable strain sensors.

A skin-inspired anisotropic multidimensional sensor based on low hysteresis organohydrogel with linear sensitivity and excellent robustness for directional perception

Human skin has complex sensors to perceive three-dimensional stimuli from the environment. Skin-inspired flexible sensors with multidimensional and directional perception are desirable for applications in intelligent robots and human–machine interaction. Herein, wearable multidimensional sensors have been fabricated by macroscopically assembling 3D-printed microstructured anisotropic organohydrogel sensory units through robust interfacial adhesion. The organohydrogel is crosslinked using microgels and starch microparticles through non-covalent interactions, and composited with short carbon fibers as conductive fillers. The physical network exhibits low hysteresis against 5000 cyclic loadings, which demonstrates excellent robustness in both mechanical properties and sensory performance. The organohydrogel precursor is printed into a cone-shaped sensor with a pressure sensitivity 50 times higher than that of its bulk counterpart. A sea cucumber epidermis-like microstructured sensor with abundant highly sensitive cone array is assembled with 3D-printed anisotropic gels with highly aligned carbon fibers inside, generating a multidimensional sensor capable of perceiving stimuli along X-, Y-, and Z-axis. The assembled sensor can directionally distinguish external forces and identify human motions. This study demonstrates a promising strategy to fabricate well-structured organohydrogel sensors for applications in electronic skin, biomimetic flexible electronics, and artificial intelligence.

Wearable Pressure Sensor Based on the Melamine Formaldehyde Resin Sponge with Graphene/MWCNTs/PDMS for Medical Assisting of Patients with Amyotrophic Lateral Sclerosis

Wearable Pressure Sensor Based on the Melamine Formaldehyde Resin Sponge with Graphene/MWCNTs/PDMS for Medical Assisting of Patients with Amyotrophic Lateral Sclerosis

A Novel Wearable Sensor for Measuring Respiration Continuously and in Real Time.

In this work, a flexible textile-based capacitive respiratory sensor, based on a capacitive sensor structure, that does not require direct skin contact is designed, optimised, and evaluated using both computational modelling and empirical measurements. In the computational study, the geometry of the sensor was examined. This analysis involved observing the capacitance and frequency variations using a cylindrical model that mimicked the human body. Four designs were selected which were then manufactured by screen printing multiple functional layers on top of a polyester/cotton fabric. The printed sensors were characterised to detect the performance against phantoms and impacts from artefacts, normally present whilst wearing the device. A sensor that has an electrode ratio of 1:3:1 (sensor, reflector, and ground) was shown to be the most sensitive design, as it exhibits the highest sensitivity of 6.2% frequency change when exposed to phantoms. To ensure the replicability of the sensors, several batches of identical sensors were developed and tested using the same physical parameters, which resulted in the same percentage frequency change. The sensor was further tested on volunteers, showing that the sensor measures respiration with 98.68% accuracy compared to manual breath counting.

Transformative personalized oxalate biomarker analysis through a wrist-worn microneedle device integrated with duplex nanozyme toolbox

The interstitial fluid (ISF) is valuable for disease diagnosis due to its unique biomarkers. Microneedles (MNs) offer a painless method for ISF sampling, facilitating primary diagnostics. This study introduces a minimally invasive, biocompatible MN patch made from a swellable hydrogel of polyvinyl alcohol (PVA) and polyvinyl pyrrolidone (PVP), which effectively extracts ISF. The hydrogel selectively permits small molecules like oxalate, a kidney disease biomarker, while blocking large biomolecules. The MN patch is integrated with a multilayer sensor via microfluidic channels, featuring cotton fiber, agarose, and Mn3[Fe(CN)6]2, alongside Fe3[Fe(CN)6]3 (AGH-CP/MnFeCN/FeFeCN). These nanozymes exhibit oxidase-like activity, reacting with 3,3′,5,5′-tetramethylbenzidine (TMB) to indicate oxalate levels through a color change from green (no oxalate) to light or dark blue, based on concentration. The designed sensor demonstrates high performance with a detection limit of 0.897 μM and an RSD of 1.22 %, enabling accurate quantification via smartphone image analysis as readout platforms for more accessibility and user-friendliness which helps to reach personalized healthcare goals. This integration facilitates real-time, remote, precise disease detection, biochemical analysis and forsooth miniaturization, leading to the development of portable, flexible, and wearable sensors. The MN patch and integrated sensor show excellent stability, selectivity, sensitivity, reliability, and long-term durability. This minimally invasive sensing system, designed for wristband integration, opens new avenues for precision point-of-care monitoring, enhancing personal healthcare.

Highly Stretchable Supercapacitor‐Type Multifunctional Self‐Powered Porous Electronic Skins

AbstractThe development of highly stretchable self‐powered electronic skins with a broad detection range is urgently needed but remains a great challenge. Herein, unprecedented highly stretchable, broad‐range‐response, supercapacitor‐type, one‐body, and self‐powered electronic skins are developed by assembling porous polyurethane/polypyrrole electrode, polyacrylic acid/polyacrylamide ionic gel electrolyte, and porous polyurethane/MXene electrode. The folded porous structure of the electrodes significantly enhances the stretchability, while the modulus‐gradient multilayer structure of the device effectively broadens the pressure detection range. The electronic skins combine self‐powered dynamic/static pressure sensing, ultrabroad detection range (20 Pa–3.5 MPa), ultrahigh stretchability up to 387%, excellent compression stability (5000 cycles under 195 kPa), and good stretching stability (500 cycles under 200% tensile strain). They have the capability of monitoring human body motions, physiological signals, and high pressures from motorcycle tires, as well as tactile sensing of robotic grippers. In addition, they can be applied for highly stretchable thermal management and electromagnetic shielding devices. This work provides a new strategy for the development of highly stretchable, broad‐range‐response, and multifunctional self‐powered wearable electronics and sensors.

Exploring the use of wearable sensors for assessing risk factors during orthopedic surgeries: A protocol for data collection

During orthopedic surgeries, surgeons are generally exposed to prolonged periods of standing, awkward and sustained body postures, and forceful movements, which can increase the likelihood of developing work-related musculoskeletal disorders (WRMSD). Therefore, this study proposes a protocol to measure parameters related to physical risk factors contributing to lower limb WRMSD, during orthopedic surgery procedures. The protocol development was preceded by an initial phase of understanding and specifying the context of use, followed by pre-tests in laboratory environment. It integrates a motion capture system, using inertial measurement units (IMU) to collect posture data from hip, knee, and ankle, and electromyography system (EMG) to measure and record data from muscle activity of biceps femoris, rectus femoris, and gastrocnemius lateralis. Pre-tests provided insights for protocol optimization, estimating a 3-hour data collection session per surgery due to sensor battery limitations, streamlining the process by placing EMG sensors before IMU and refining thigh sensor placement strategies. The protocol presents an opportunity for a real-time and quantitative approach to monitor surgeon's exposure to risk factors contributing to lower limb WRMSD while performing surgical procedures. Two months after pre-tests, the protocol implementation began in a real work context. The study's final outcomes fall outside the paper's scope.

Enhanced Photodetection Performance of WSe2/V2O5 Nanocomposite on Flexible Substrate: Synergistic Advantages and Improved Efficiency.

The two-dimensional (2D) chalcogenide WSe2/V2O5 composite nanostructures were synthesized using the hydrothermal method and extensively characterized with various spectroscopic techniques. X-ray diffraction analysis confirmed the hexagonal crystal structure exhibiting space symmetry of P63/mmc. Scanning electron microscopy images provided insights into the irregular and nonuniform morphology. Optical spectrum analysis indicated a band gap value of 2.01 eV for 15% WSe2/V2O5 nanostructures, as determined by the Wood and Tauc equation. Photoluminescence (PL) excitation spectra at emission wavelengths of 550 and 750 nm exhibited broad emission attributed to self-trapped excitons for V2O5 and WSe2 nanostructures. Under excitation at λexc = 365 nm, PL emission spectra displayed distinct peaks at 550 and 750 nm, demonstrating the ability to emit vivid red light. A device optimized for photoresponsivity (R) of approximately 7.80 × 10-1 A W-1 and detectivity (D) of around 8.65 × 1011 Jones, and quantum efficiency of approximately 3.42 × 10-2 A W-1 were achieved at a wavelength of 390 nm while using a lamination sheet as a substrate. These findings underscore the capability of devices for efficient photoconversion at specified wavelengths, indicating potential applications in sensing, imaging, and optical communication. The photoresponsivity of the device remained stable at 3.38 × 10-3 A W-1 at 0° and 3.09 × 10-3 A W-1 at 55° bending angle. This indicates the resilience of device to mechanical strain, making it ideal for flexible and wearable sensor applications. The structural, morphological, and optical characterizations confirm the suitability of luminescent WSe2/V2O5 chalcogenide for practical optoelectronic applications, especially in display technologies.

Optical Fiber‐Based Wearable Sensors for Remote Health Monitoring [Invited

AbstractThe wearable optical fiber sensors have demonstrated significant promise in the realm of health monitoring in recent times. These sensors utilize the flexibility and exceptional sensitivity of optical fibers to precisely measure many physiological aspects of the human body, including heart rate, breathing rate, mobility status, and body temperature. Optical fiber sensors usually have good biocompatibility and anti‐interference capabilities, can be integrated into flexible materials, and are suitable for long‐term wear. It can be integrated into clothing, patches, or accessories to provide continuous, real‐time health data monitoring, providing important support for personalized medicine and remote health management. This paper primarily presents the fundamental operating concept of wearable optical fiber sensors and their use in monitoring physiological signals across multiple domains. In conclusion, this paper provides a summary of the limitations and future prospects of wearable fiber sensors using optical fiber technology.

Relationship between objectively measured conversation time and social behavior in community-dwelling older adults.

Social isolation is a significant public health concern in aging societies. The association between conversation time and social behavior remains unclear. This study examines whether objective conversation time is associated with social activity frequency in older adults. This prospective cohort study enrolled 855 older adults (538 women; mean age, 73.8 years) aged 65 and older, who were followed from 2015 to 2019. All participants wore a wristband sensor to measure conversation time for at least 9 days and an average of 31.3 days per year. Social behaviors were assessed through interviews, and the frequency of engagement in community activities, outings, lessons, or classes and contact frequency were assessed using a self-report questionnaire. The association between conversation time and social behavior was evaluated using multi-linear regression analysis. Conversation time was significantly associated with the frequency of engagement in community activities and lessons or classes after adjusting for several covariates (β = 0.181, 95% confidence interval: 0.107-0.254, p < 0.001; β = 0.11, 95% confidence interval: 0.04-0.179, p = 0.002). Objectively measured conversation time using a wearable sensor is associated with social behavior and may be a valuable parameter for social isolation in older adults.

Sensor-Aware Data Imputation for Time-Series Machine Learning on Low-Power Wearable Devices

Wearable devices that have low-power sensors, processors, and communication capabilities are gaining wide adoption in several health applications. The machine learning algorithms on these devices assume that data from all sensors are available during runtime. However, data from one or more sensors may be unavailable due to energy or communication challenges. This loss of sensor data can result in accuracy degradation of the application. Prior approaches to handle missing data, such as generative models or training multiple classifiers for each combination of missing sensors are not suitable for low-energy wearable devices due to their high overhead at runtime. In contrast to prior approaches, we present an energy-efficient approach, referred to as Sensor-Aware iMputation (SAM), to accurately impute missing data at runtime and recover application accuracy. SAM first uses unsupervised clustering to obtain clusters of similar sensor data patterns. Next, it learns inter-relationship between clusters to obtain imputation patterns for each combination of clusters using a principled sensor-aware search algorithm. Using sensor data for clustering before choosing imputation patterns ensures that the imputation is aware of sensor data observations. Experiments on seven diverse wearable sensor based time-series datasets demonstrate that SAM is able to maintain accuracy within 5% of the baseline with no missing data when one sensor is missing. We also compare SAM against generative adversarial imputation networks (GAIN), transformers, and k-nearest neighbor methods. Results show that SAM outperforms all three approaches on average by more than 25% when two sensors are missing with negligible overhead compared to the baseline.

Wood Cell Wall Nanoengineering toward Anisotropic, Strong, and Flexible Cellulosic Hydrogel Sensors.

Achieving highly ionic conductive hydrogels from natural wood remains challenging owing to their insufficient surface area and low number of active sites on the cell wall. This study proposes a viable strategy to design a strong and anisotropic wood-based hydrogel through cell wall nanoengineering. By manipulating the microstructure of the wood cell wall, a flexible cellulosic hydrogel is achieved through Schiff base bonding via the polyacrylamide and cellulose molecular chains. This results in excellent flexibility and mechanical properties of the wood hydrogel with tensile strengths of 22.3 and 6.1 MPa in the longitudinal and transverse directions, respectively. Moreover, confining aqueous salt electrolytes within the porous structure gives anisotropic ionic conductivities (19.5 and 6.02 S/m in the longitudinal and transverse directions, respectively). The wood-based hydrogel sensor has a favorable sensitivity and a stable working performance at a low temperature of -25 °C in monitoring human motions, thereby demonstrating great potential applications in wearable sensor devices.