Search Results (267)

The reliable integration of high-performance noble metal interfaces with flexible substrates is a key requirement for wearable electronics. However, achieving uniform, mechanically robust and functionally active coatings on fabric surfaces remains highly challenging. This study reports the atomic-layered-deposition (ALD) growth of platinum (Pt) on textile at low temperatures. Through ozone plasma-assisted activation technology, Pt nucleation can be achieved at 100 °C, forming a dense and defect-suppressed Pt layer that substantially increases the surface oxygen functional groups and enhances binding affinity. The resulting Pt layer also significantly enhances the adsorption behavior and sensing performance of Ti₃C₂T_x MXene gel inks on textile. At the atomic scale, the engineered Pt–MXene interface promotes stronger adsorption of MXene sheets and establishes efficient electron/ion transport pathways within the gel network. Ultimately, the conductive textile treated with Pt functionalized layers (MXene/Pt@textile) exhibits significantly enhanced sensing sensitivity and signal stability, enabling precise detection of human motions, pressure, and subtle physiological vibrations. The synergistic effect of ALD Pt layers and MXene gel inks creates a textile platform combining robustness, breathability, and high responsiveness. Full article

Flexible strain sensors capable of conformal integration with living organisms are essential for advanced wearable electronics, human–machine interaction, and plant health. However, many existing sensors require complex fabrication or rely on non-breathable elastomer substrates that interfere with the physiological microenvironment of skin or plant tissues. Here, we present a low-cost, breathable, and highly stretchable strain sensor constructed from biomedical materials, in which a double-layer medical elastic bandage serves as the porous substrate and an intermediate conductive medical elastic tape impregnated with carbon nanotubes (CNTs) ink acts as the sensing layer. Owing to the hierarchical textile porosity and the deformable CNTs percolation network, the sensor achieves a wide strain range of 100%, a gauge factor of up to 2.72, and excellent nonlinear second-order fitting (R² = 0.997). The bandage substrate provides superior air permeability, allowing long-term attachment without obstructing moisture and gas exchange, which is particularly important for maintaining skin comfort and preventing disturbances to plant epidermal physiology. Demonstrations in human joint-motion monitoring and real-time plant growth detection highlight the device’s versatility and biological compatibility. This work offers a simple, low-cost yet effective alternative to sophisticated strain sensors designed for human monitoring and plant growth monitoring, providing a scalable route toward multifunctional wearable sensing platforms. Full article

Electrocardiography (ECG) is widely recognized as the gold standard for measuring heart rate (HR) and heart rate variability (HRV). However, photoplethysmography (PPG) presents notable advantages in terms of wearability, affordability, and ease of integration into consumer devices, despite its susceptibility to motion artifacts and the absence of standardized processing protocols. In this study, we review current ECG and PPG signal processing methods and propose a signal quality assessment and reconstruction pipeline tailored for dynamic, in-vehicle environments. This pipeline was evaluated using data gathered from participants riding in an automated vehicle. Our findings demonstrate that while blood volume pulse (BVP) derived from PPG can provide reliable heart rate estimates and support extraction of certain HRV features, its utility in accurately capturing high-frequency HRV components remains constrained due to motion-induced noise and signal distortion. These results underscore the need for caution in interpreting PPG-derived HRV, particularly in mobile or ecologically valid contexts, and highlight the importance of establishing best practices and robust preprocessing methods to enhance the reliability of PPG sensing for field-based physiological monitoring. Full article

Rapid global urbanization has intensified the demand for sensing solutions that can capture the complex interactions between urban environments and their impact on human physical and mental health. Conventional laboratory-based approaches, while offering high experimental control, often lack ecological validity and fail to represent real-world exposures. To address this gap, we present the eMOTIONAL Cities Walker—a portable multimodal sensing platform designed as a wearable backpack unit developed for the synchronous collecting of multimodal data in either indoor or outdoor settings. The system integrates a suite of environmental sensors (covering microclimate, air pollution and acoustic monitoring) with physiological sensing technologies, including electroencephalography (EEG), mobile eye-tracking and wrist-based physiological monitoring. This configuration enables real-time acquisition of environmental and physiological signals in dynamic, naturalistic settings. Here, we describe the system’s technical architecture, sensor specifications, and field deployment across selected Lisbon locations, demonstrating its feasibility and robustness in urban environments. By bridging controlled laboratory paradigms with ecologically valid real-world sensing, this platform provides a novel tool to advance translational research at the intersection of sensor technology, human experience, and urban health. Full article

As demanded by the rapid development of wearable electronics, flexible pressure sensors have attracted more and more attention worldwide. However, the performance of pressure sensors based on the piezoelectric effect has not been qualified for practical application. In this work, we designed and prepared PVDF/BTO fibers by an electrospinning approach and constructed pressure sensors for various human motion detection purposes. The performance is dramatically enhanced due to the high piezoelectric coefficient of BTO nanoparticles and the utilization of PVDF matrix with a high β content. The optimized pressure sensor presents a high power density of 27.5 nW cm⁻² at 10 N load stress and remains stable even after 3000 cycles. For human action application, the maximum output voltage is up to 20 V. The optimum β content of the PVDF matrix is up to 72.9%, which in turn contributes to the high energy-harvesting capability of the designed composites. The prepared PVDF/BTO composites show benign capability for sensing various human actions. This work shapes a new strategy for high-performance pressure sensors based on piezoelectric composites. Full article

Monitoring physiological activity and sleep states in real time is challenging, particularly for continuous assessment in daily life settings using wearable IoMT devices. We developed a 24 h wearable system that integrates electrocardiogram (ECG) electrodes for heart rate measurement and a glove-mounted flex sensor for motor responses, connected through an Internet of Medical Things (IoMT) platform. Flex signals were combined using principal component analysis (PCA) to generate a single kinematic channel, then standardized with heart rate. Time-series windows were embedded using TS2Vec and clustered with DBSCAN, while t-SNE was applied only for visualization. The framework identified four physiologically coherent states: (i) nocturnal sleep with the lowest heart rate and minimal motion, (ii) evening pre-sleep with low movement and moderately higher heart rate, (iii) daytime activity with variable motion and mid-range heart rate, and (iv) late-day high-intensity activity with the highest heart rate and increased motor responses. A few outliers were observed during transient body movements or sensor readjustments, which were identified and excluded during preprocessing to ensure stable clustering results. Across 24 h, heart rate ranged from 52 to 96 bpm (mean 77.4), while flexion spanned 0 to 165° (mean 52.5°), showing alignment between movement intensity and cardiac response. This integrated sensing and analytics pipeline provides an interpretable, subject-specific state map that enables continuous remote monitoring of physiological activity and sleep patterns. Full article

Stress, workload, and uncertainty characterize occupational tasks across sports, healthcare, military, and transportation domains. Emerging theory and empirical research suggest that coordinated whole-body movements may reflect these transient mental states. Wearable sensors and optical motion capture offer opportunities to quantify such movement dynamics and classify mental states that influence occupational performance and human–machine interaction. We tested this possibility in a small pilot study (N = 10) designed to test feasibility and identify preliminary movement features linked to mental states. Participants performed a perceptual decision-making task involving facial emotion recognition (i.e., deciding whether depicted faces were happy versus angry) with variable levels of stress (via a risk of electric shock), workload (via time pressure), and uncertainty (via visual degradation of task stimuli). The time series of movement trajectories was analyzed both holistically (full trajectory) and by phase: lowered (early), raising (middle), aiming (late), and face-to-face (sequential). For each epoch, up to 3844 linear and non-linear features were extracted across temporal, spectral, probability, divergence, and fractal domains. Features were entered into a repeated 10-fold cross-validation procedure using 80/20 train/test splits. Feature selection was conducted with the T-Rex Selector, and selected features were used to train a scikit-learn pipeline with a Robust Scaler and a Logistic Regression classifier. Models achieved mean ROC AUC scores as high as 0.76 for stress classification, with the highest sensitivity during the full movement trajectory and middle (raise) phases. Classification of workload and uncertainty states was less successful. These findings demonstrate the potential of movement-based sensing to infer stress states in applied settings and inform future human–machine interface development. Full article

There is a critical demand for flexible resistive sensors that combine high sensitivity with a wide linear range, fast response speed, and excellent long-term stability. This study presents the development of a high-performance resistive flexible sensor utilizing graphene-coated iron nanowires (Fe NWs@Graphene) as conductive fillers within a polyurethane sponge (PUS) substrate. The sensor was constructed with a sandwich-like structure, consisting of Fe NWs@Graphene-impregnated PUS as the sensing layer, encapsulated by polydimethylsiloxane (PDMS) for protection. The Fe NWs were synthesized via a chemical reduction process employing an external magnetic field. Subsequent chemical vapor deposition enabled uniform graphene coating on the surface of Fe NWs. Systematic performance assessments demonstrated that the Fe NWs@Graphene flexible sensor exhibits a gauge factor (GF) of 14.5 within a 0–100% strain range, representing a 71% improvement over previously reported Fe NW-based strain sensors, along with excellent linearity (R² = 0.994). The sensor also showed rapid response times (113 ms for loading and 97 ms for unloading) and outstanding cyclic stability over 3000 stretching cycles at 50% strain. These enhancements are attributed to the synergistic effects between Fe NWs and graphene: the graphene shell effectively protects the Fe NW core against oxidation, thereby improving stability, and facilitates efficient charge transport, while the Fe NWs serve as bridging agents that improve both mechanical integrity and electrical percolation. In addition, application tests simulating human motion detection confirmed the sensor’s ability to accurately capture muscle-induced strain signals with high repeatability. The results underscore the feasibility of Fe NWs@Graphene as conductive fillers for high-sensitivity, wide-range, and stable flexible sensors, highlighting the potential in wearable electronics and human–machine interaction systems. Full article

The adoption of wearable sensors for precision training has accelerated in recent years, yet most studies and reviews remain device- or feasibility-centric and lack a field-ready decision framework. This review organizes wearable sensing across four monitoring dimensions—physiological, kinematic, biochemical, and dynamic—and maps them onto three training pillars: physical, technical, and tactical. From the perspectives of athletes and coaches, we operationalize quality control, threshold, and feedback loop to translate measurement into action. We critically appraise key limitations, including signal robustness under high-intensity motion, inter-individual variability and limited model generalizability, cross-device data fusion and latency, battery life and wearability, privacy and data ownership, and limited accessibility beyond elite settings. Looking ahead, we advocate a shift from mere multidimensional measurement to a verifiable, reusable, and deployable precision-training ecosystem that delivers actionable metrics and clear decision support for practitioners. Full article

The present contribution aims to analyze and highlight the potential of piezoelectric materials in actuation and sensing duties, obtaining reliable high-precision outcomes in cutting-edge applications including medical interventions. This involves high-precision actuations of robotized procedures, as well as monitoring and controlling various physical phenomena via structural sensing. The characteristics of these applications offer enhanced precision machinery and robotic tools, medical robotic precise interventions, and high-accuracy structural sensing. The paper exposed, analyzed, reviewed and discussed different subjects related to piezoelectric actuators, involving their displacement and positioning strategies, piezoelectric sensors, medical applications of piezoelectric actuators and sensors, including robotic actuation for medical interventions, and structural sensing in the monitoring of wearable healthcare tools. Discussions among others on the advantages and limitations of piezoelectric sensors and actuators in general, as well as future research perspectives in medical involvements, are also presented at the end of the article. The specific features in the illustrated applications reflect crucial behaviors in robotic actuation for medical interventions, structural sensing in the monitoring of healthcare wearable tools, and the control of various structural physical occurrences. Full article

Triboelectric materials can convert irregular mechanical stimuli from human motion or environmental sources into high surface charge densities and instantaneous electrical outputs. Their intrinsic properties, such as flexibility, stretchability, chemical tunability, and compatibility with diverse substrates, play a critical role in determining the efficiency and reliability of triboelectric devices. In the context of active health, triboelectric materials not only serve as the core functional layers for self-powered sensing but also enable real-time physiological monitoring, motion tracking, and human–machine interaction by directly transducing biomechanical signals into electrical information. Soft triboelectric sensors exhibit high sensitivity, wide operational ranges, excellent biocompatibility, and wearability, making them highly promising for active health monitoring applications. Despite these advantages, challenges remain in enhancing surface charge density, achieving effective signal multiplexing, and ensuring long-term stability. This review provides a comprehensive overview of triboelectric mechanisms, working modes, influencing factors, performance enhancement strategies, and wearable health applications. Finally, it systematically summarizes the key improvement approaches and future development directions of triboelectric materials for active health, offering valuable guidance for advancing wearable self-powered biosensors. Full article

Nanogenerators (NGs), especially triboelectric nanogenerators (TENGs), represent an emerging technology with great potential for self-powered lumbar motion monitoring. Conventional wearable systems for assessing spinal kinematics are often limited by their reliance on external power supplies, hindering long-term and real-time clinical applications. NGs can convert biomechanical energy from lumbar motion into electrical energy, providing both sensing and power-generation capabilities in a single platform. This review summarizes the fundamental working mechanisms, device architectures, and current progress of NG-based motion monitoring technologies, with a particular focus on their applications in lumbar spine research and clinical rehabilitation. By enabling high-sensitivity, continuous, and battery-free monitoring, NG-based systems may enhance the diagnosis and management of low back pain (LBP) and postoperative recovery assessment. Furthermore, the integration of NGs with wearable electronics, the Internet of Things (IoT), and artificial intelligence (AI) holds promise for developing intelligent, self-sustaining monitoring platforms that bridge biomedical engineering and spine medicine. Full article

Triboelectric nanogenerators (TENG) are mechanical energy harvesters characterized by high sensitivity and simple structure and are currently being widely developed for use in human body motion sensing. Among them, fiber-based TENGs (FTENG) are particularly suitable for wearable human motion sensors due to their unique structure, which offers flexibility, high durability, and comfort. However, studies involving doping to further modify the electrical output characteristics of FTENGs are very limited. Here, we propose an innovative approach that combines graphite (GP) doping with fiber-based TENG fabrication, successfully developing a graphite-doped polyester fiber-based TENG (GP@PET-TENG). Proper graphite doping can increase the amount of transferred charge and thus improve the output electrical performance of TENG, but this method has rarely been explored in FTENG. With the incorporation of 3%wt graphite, the open-circuit voltage of the GP@PET-TENG increased from 103.3 V to 202.1 V, and the short-circuit current increased from 60.7 μA to 105.1 μA, compared to the pure polyester fiber based TENG (PET-TENG). The device achieved a maximum output power of 4.15 mW (2.59 W/m²), demonstrates the capability to charge various capacitors, and successfully lit up 200 LEDs. By attaching the GP@PET tribo-layer to human skin, a single-electrode mode TENG can be formed, which captures the subject’s motion signals through skin contact and separation, converting them into voltage outputs. In fist-clenching and wrist-bending tests, motion-induced voltage signals up to 0.6 V were recorded, demonstrating the potential applications in rehabilitation assistance and mechanical control. Full article

Wearable devices are increasingly used for health and stress monitoring, yet their accuracy under dynamic, real-world conditions remains uncertain. This study validated the heart rate measurement accuracy of one chest-worn device (Zephyr BioHarness 3.0), a research-grade wrist-worn device (EmbracePlus), and five commercial wrist-worn wearable devices (Fitbit Charge 5, Fitbit Sense 2, Garmin Vivosmart 4, WHOOP 4.0, and Withings Scanwatch) against a 12-lead ECG using a 20 min protocol simulating real-life dynamics, including rest and varied-intensity walking. Device performance was evaluated across the full protocol and during transient states, defined as periods of rapid heart rate change. Accuracy and agreement were evaluated across per-second, 10 s, and 60 s resolutions. The Zephyr device showed a strong performance during all dynamic conditions. Among the wrist-worn devices, the Fitbit Charge 5 and Sense 2 showed the highest accuracy overall, while the Garmin Vivosmart 4 demonstrated greater stability during transitions. The WHOOP 4.0, Withings Scanwatch, and EmbracePlus devices performed acceptably during steady-state conditions, but were less accurate during transitions. Performance notably declined across all wrist-worn devices during transient states, with motion onset and large step changes in heart rate exacerbating measurement errors. Larger averaging windows improved accuracy by smoothing variability. The findings underscore that wrist-worn wearable devices may be better suited for average and trend heart rate monitoring rather than capturing acute dynamics. However, the Garmin and Fitbit devices showed suitable when requiring moderate accuracy during dynamic conditions. These results highlight the importance of context-specific validation and informed device selection to ensure effective use in health and stress-related applications. Full article

This paper presents the third-generation design of Bimu, a compact wearable inertial measurement unit (IMU) tailored for advanced human motion tracking. Building on prior iterations, Bimu R2 focuses on enhancing thermal stability, data integrity, and energy efficiency by integrating onboard memory, redesigning the power management system, and optimizing the communication interfaces. A detailed performance evaluation—including noise, bias, scale factor, power consumption, and drift—demonstrates the device’s reliability and readiness for deployment in real-world applications ranging from clinical gait analysis to high-speed motion capture. The improvements introduced offer valuable insights for researchers and engineers developing robust wearable sensing solutions. Full article