Search Results (937)

The rapid rise of bio-hybrid robots and hybrid human–AI systems has triggered an explosion of terminology that inhibits clarity and progress. To investigate how terms are defined, we conduct a narrative scoping review and concept analysis. We extract 60 verbatim definitions spanning engineering, human–computer interaction, human factors, biomimetics, philosophy, and policy. Entries are coded on three axes: agency locus (human, shared, machine), integration depth (loose, moderate, high), and normative valence (negative, neutral, positive), and then clustered. Four categories emerged from the analysis: (i) machine-led, low-integration architectures such as neuro-symbolic or “Hybrid-AI” models; (ii) shared, moderately integrated systems like mixed-initiative cobots; (iii) human-led, medium-coupling decision aids; and (iv) human-centric, low-integration frameworks that focus on user agency. Most definitions adopt a generally positive valence, suggesting a gap with risk-heavy popular narratives. We show that, for researchers investigating where living meets machine, terminological precision is more than semantics and it can shape design, accountability, and public trust. This narrative review contributes a comparative taxonomy and a shared lexicon for reporting hybrid systems. Researchers are encouraged to clarify which sense of Hybrid-AI is intended (algorithmic fusion vs. human–AI ensemble), to specify agency locus and integration depth, and to adopt measures consistent with these conceptualizations. Such practices can reduce construct confusion, enhance cross-study comparability, and align design, safety, and regulatory expectations across domains. Full article

Multidrug resistance has also been accompanied by the prolonged use of antibiotics that makes complications in treatment. Biofilm in pathogenic bacteria is the most serious challenge linked with chronic illnesses and also contributes to virulence and drug resistance. Several bacterial pathogens employ the Quorum-sensing (QS) mechanism to coordinate their collective behaviors like bioluminescence, virulence, and biofilm formation. Therefore, agents that inhibit or interfere with bacterial QS and biofilm formation are emerging as a new class of next-generation antibacterial. Recently, nanoparticles have been employed to improve the efficacy of existing antibacterial agents. In the present study, gold nanocrystals were synthesized by using Koelreuteria paniculata (KP) leaf extract. Synthesized nanocrystals were characterized by a face-centered cubic structure of ~20 nm by XRD, FTIR, Zeta sizer, and TEM. Biogenic Gold nanocrystals (BGNCs) exhibited extended QS inhibition in bio-indicator strains Chromobacterium violaceum and Pseudomonas aeruginosa biosensor strains. BGNCs strongly suppressed QS-controlled violacein production in C. violaceum CV026, and elastase, protease, pyocyanin, alginate, and biofilm formation in P. aeruginosa (PA01). In addition, BGNCs notably suppressed the relative expression of PA01 quorum sensing, biofilm-forming, and virulence-regulating genes, as quantified by qRT-PCR. As a result of the broad-spectrum suppression of QS and biofilm by BGNCs, it is anticipated that these nontoxic bioactive nanocrystals can be employed as surface sterilization agents in nosocomial infections. Full article

Autonomous navigation in GPS-denied, unstructured environments such as murky waters or complex seabeds remains a formidable challenge for robotic systems, primarily due to sensory degradation and the computational inefficiency of conventional algorithms. Drawing inspiration from the robust navigation strategies of marine species such as the sea turtle’s quantum-assisted magnetoreception, the octopus’s tactile-chemotactic integration, and the jellyfish’s energy-efficient flow sensing this study introduces a novel neuromorphic framework for resilient robotic navigation, fundamentally based on the co-design of marine-inspired sensors and event-based neuromorphic processors. Current systems lack the dynamic, context-aware multisensory fusion observed in these animals, leading to heightened susceptibility to sensor failures and environmental perturbations, as well as high power consumption. This work directly bridges this gap. Our primary contribution is a hybrid sensor fusion model that co-designs advanced sensing replicating the distributed neural processing of cephalopods and the quantum coherence mechanisms of migratory marine fauna with a neuromorphic processing backbone. Enabling real-time, energy-efficient path integration and cognitive mapping without reliance on traditional methods. This proposed framework has the potential to significantly enhance navigational robustness by overcoming the limitations of state-of-the-art solutions. The findings suggest the potential of marine bio-inspired design for advancing autonomous systems in critical applications such as deep-sea exploration, environmental monitoring, and underwater infrastructure inspection. Full article

New strawberry cultivars with unusual peel colors, such as white and peach, require thorough characterization to understand their quality traits. In this study, we examined three Japanese cultivars, ‘Kotoka’ (red), ‘Awayuki’ (peach), and ‘Pearl White’ (white), to investigate their differences in chemistry and optical properties. We measured the sugar content, acidity, and maturity index, and combined these with fluorescence spectroscopy and imaging under three LED lights (365 nm, 420 nm, and white). The fluorescence data showed clear differences between cultivars, in which the ‘Pearl White’ gave a strong near-UV peak around 290/325 nm, ‘Awayuki’ had a high far-red signal in 490/745 nm, and ‘Kotoka’ showed lower fluorescence overall. Imaging backed up these findings, with ‘Pearl White’ and ‘Awayuki’ looking brighter under UV while Kotoka appeared darker and more uniform. Texture analysis showed ‘Pearl White’ had a more uneven surface, while ‘Kotoka’ was smoother. The basic chemistry also matched these trends, as ‘Kotoka’ had the most sugar and acid, giving it a sharper taste, while ‘Pearl White’ had the highest maturity index and a milder flavor. These results demonstrate how fluorescence fingerprints and imaging features, when combined, can rapidly characterize strawberry types and assess their quality without damaging the fruit. Full article

Wearable devices (WDs) are increasingly integrated into clinical workflows to enable continuous, non-invasive vital signs monitoring. Combined with Artificial Intelligence (AI), these systems can shift clinical monitoring from being reactive to predictive, allowing for earlier detection of deterioration and more personalized interventions. The value of these technologies lies not in absolute measurements, but in detecting physiological parameters trends relative to each patient’s baseline. Such a trend-based approach enables real-time prediction of deterioration, enhancing patient safety and continuity of care. However, despite their shared multiparametric capabilities, WDs are not interchangeable. This narrative review analyzes nine clinically validated devices, Radius VSM^® (Masimo Corporation, Irvine, CA, USA), BioButton^® (BioIntelliSense Inc., Redwood City, CA, USA. Distributed by Medtronic), Portrait Mobile^® (GE HealthCare, Chicago, IL, USA), VitalPatch^® (VitalConnect Inc., San Jose, CA, USA), CardioWatch 287-2^® (Corsano Health B.V., The Hague, The Netherlands. Distributed by Medtronic), Cosinuss C-Med Alpha^® (Cosinuss Gmb, Munich, Germany), SensiumVitals^® (Sensium Healthcare Limited, Abingdon, Oxfordshire, UK), Isansys Lifetouch^® (Isansys Lifecare Ltd., Abingdon, Oxfordshire, UK), and CheckPoint Cardio^® (CheckPoint R&D LTD., Kazanlak, Bulgaria), highlighting how differences in sensor configurations, battery life, connectivity, and validation contexts influence their suitability across various clinical environments. Rather than establishing a hierarchy of technical superiority, this review emphasizes the importance of context-driven selection, considering care setting, patient profile, infrastructure requirements, and interoperability. Each device demonstrates strengths and limitations depending on patient population and operational demands, ranging from perioperative, post-operative, emergency, or post-Intensive Care Unit (ICU) settings. The findings support a tailored approach to WD implementation, where matching device capabilities to clinical needs is key to maximizing utility, safety, and efficiency. Full article

The rapid evolution of healthcare technology is being driven by advancements in Micro-Electro-Mechanical Systems (MEMS), BioMEMS (Biological MEMS), and the expanding concept of the Internet of Bodies (IoB). This review explores the convergence of these three domains and their transformative impact on personalized medicine (PM), with a focus on smart, connected biomedical devices. Starting from the historical development of MEMS for medical sensing and diagnostics, the review traces the emergence of BioMEMS as biocompatible, minimally invasive solutions for continuous monitoring and real-time intervention. The integration of such devices within the IoB ecosystem enables data-driven, remote, and predictive healthcare, offering tailored diagnostics and treatment for chronic and acute conditions alike. The paper classifies IoB-associated technologies into non-invasive, invasive, and incorporated devices, reviewing wearable systems such as smart bracelets, e-tattoos, and smart footwear, as well as internal devices including implantable and ingestible. Alongside these opportunities, significant challenges persist, particularly in device biocompatibility, data interoperability, cybersecurity, and ethical regulation. By synthesizing recent advances and critical perspectives, this review aims to provide a comprehensive understanding of the current landscape, clinical potential, and future directions of MEMS, BioMEMS, and IoB-enabled personalized healthcare. 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

Electrochemical impedance spectroscopy (EIS) is a highly versatile electrochemical technique capable of discretizing each electrochemical parameter in complex systems by employing a broad frequency spectrum. When EIS is employed in (bio)sensing applications, the electrochemical parameters are usually fitted into a relatively limited equivalent circuit model regardless of the system at hand. This work thoroughly discusses the meaning of each physical parameter in the Randles circuit, the most common equivalent circuit to model (bio)sensing systems based on EIS transduction. Additionally, it pinpoints the most suitable modifications to the Randles circuit for modern-day electrodes, where coatings of non-biological and/or biological materials can radically impact the measured impedance compared to that of unmodified electrodes. The discussion is supported by simulations that clearly exhibit the effect of each examined parameter, providing guidance for experimentalists to improve the accuracy of their work. Full article

The actomyosin complex—nature’s dynamic engine composed of actin filaments and myosin motors—is emerging as a versatile tool for bio-integrated nanotechnology. This review explores the growing potential of actomyosin-powered systems in biosensing and actuation applications, highlighting their compatibility with physiological conditions, responsiveness to biochemical and physical cues and modular adaptability. We begin with a comparative overview of natural and synthetic nanomachines, positioning actomyosin as a uniquely scalable and biocompatible platform. We then discuss experimental advances in controlling actomyosin activity through ATP, calcium, heat, light and electric fields, as well as their integration into in vitro motility assays, soft robotics and neural interface systems. Emphasis is placed on longstanding efforts to harness actomyosin as a biosensing element—capable of converting chemical or environmental signals into measurable mechanical or electrical outputs that can be used to provide valuable clinical and basic science information such as functional consequences of disease-associated genetic variants in cardiovascular genes. We also highlight engineering challenges such as stability, spatial control and upscaling, and examine speculative future directions, including emotion-responsive nanodevices. By bridging cell biology and bioengineering, actomyosin-based systems offer promising avenues for real-time sensing, diagnostics and therapeutic feedback in next-generation biosensors. Full article

Understanding how electromagnetic (EM) waves travel through different tissues is important for EM medical imaging, sensing, and in-body communication. It is known that EM waves in lossy bio-tissues are nonuniform and do not strictly follow the least time or least loss paths. Instead, they exhibit two distinct wavefronts: the phase wavefront and the amplitude wavefront, which are generally oriented at different angles. The impact of that on imaging and in-body communications is investigated and validated through comprehensive analysis and full-wave EM simulations. Additionally, the impact of a matching medium, commonly used to reduce antenna–skin interface reflections in medical EM applications, on the direction of EM wavefronts, travel time, phase changes, and attenuation is analyzed and quantified. The results show that the Fermat principle of least travel time, often used to estimate EM wave travel time for localization in medical imaging and wireless endoscopy, is only accurate when the loss tangent or dissipation factor of both the matching medium and tissues is very low. Otherwise, the results will be inaccurate, and the dual wavefronts should be considered. The presented analysis and results provide guidance on EM wave travel time and the direction of phase and amplitude wavefronts. This information is valuable for developing reliable processing algorithms for sensing, imaging, and in-body communication. Full article

Synthetic aperture radar (SAR) exhibits all-day and all-weather capabilities, granting it significant application in remote sensing. However, interpreting SAR images requires extensive expertise, making SAR-to-optical remote sensing image translation a crucial research direction. While conditional generative adversarial networks (CGANs) have demonstrated exceptional performance in image translation tasks, their massive number of parameters pose substantial challenges. Therefore, this paper proposes ILF-BDSNet, a compressed network for SAR-to-optical image translation. Specifically, first, standard convolutions in the feature-transformation module of the teacher network are replaced with depthwise separable convolutions to construct the student network, and a dual-resolution collaborative discriminator based on PatchGAN is proposed. Next, knowledge distillation based on intermediate-layer features and channel pruning via weight sharing are designed to train the student network. Then, the bio-inspired dynamic search of channel configuration (BDSCC) algorithm is proposed to efficiently select the optimal subnet. Meanwhile, the pixel-semantic dual-domain alignment loss function is designed. The feature-matching loss within this function establishes an alignment mechanism based on intermediate-layer features from the discriminator. Extensive experiments demonstrate the superiority of ILF-BDSNet, which significantly reduces number of parameters and computational complexity while still generating high-quality optical images, providing an efficient solution for SAR image translation in resource-constrained environments. Full article

Oceans, which cover more than 70% of Earth’s surface, are home to vast biological and mineral resources. Deep-sea exploration encounters significant challenges due to harsh environmental factors, including low temperatures, high pressure, and complex hydrodynamic forces. These constraints have led to the widespread use of underwater robots as essential tools for deep-sea resource exploration and exploitation. Conventional underwater robots, whether rigid with fixed stiffness or fully flexible, fail to achieve the propulsion efficiency observed in biological fish. To overcome this limitation, researchers have developed adjustable stiffness mechanisms for robotic fish designs. This innovation strikes a balance between structural rigidity for stability and flexible adaptability to dynamic environments. By dynamically adjusting localized stiffness, these bio-inspired robots can alter their mechanical properties in real time. This capability improves propulsion efficiency, energy utilization, and resilience to external disturbances during operation. This paper begins by reviewing the evolution of underwater robots, from fixed-stiffness systems to adjustable-stiffness designs. Next, existing methods for stiffness adjustment are categorized into two approaches: offline component replacement and online real-time adaptation. The principles, implementation strategies, and comparative advantages of each approach are then analyzed. Finally, we identify the current challenges in adjustable-stiffness underwater robotics and propose future directions, such as advancements in intelligent sensing, autonomous stiffness adaptation, and enhanced performance in extreme environments. Full article

Autonomic dysfunction is a key non-motor feature of Parkinson’s disease (PD) and may influence motor performance, particularly gait. While heart rate variability (HRV) has been associated with freezing of gait, its relationship with broader gait parameters remains unclear. The objective was to investigate correlations between resting-state HRV time-domain measures and spatiotemporal gait parameters during comfortable and fast walking in patients with idiopathic PD. Twenty-eight PD patients (mean age 68 ± 9 years) were evaluated at Campus Bio-Medico University Hospital. HRV was recorded at rest using the e-Sense pule™ portable sensor, including the Baevsky’s Stress Index a measure increasing with sympathetic burden. Gait parameters were assessed via the 10 m Timed Up and Go (TUG) test using the Mon4t™ smartphone app at comfortable and fast pace. Clinical data included UPDRS III, MoCA, and disease characteristics. Gait metrics significantly changed between walking conditions. HRV parameters clustered separately from gait metrics but intersected with significant correlations. Higher Stress Index values, reflecting sympathetic dominance, were associated with poorer gait performance, including prolonged transition times, shorter steps, and increased variability (p < 0.001, r = 0.57–0.61). MoCA scores inversely correlated with the Stress Index (r = −0.52, p = 0.004), linking cognitive and autonomic status. UPDRS III and MoCA were related to TUG metrics but not HRV. Time-domain HRV measures, particularly the Stress Index, are significantly associated with spatiotemporal gait features in PD, independent of gait speed. These findings suggest that impaired autonomic regulation contributes to functional mobility deficits in PD and supports the role of HRV as a biomarker in motor assessment. Full article

The peregrine falcon, known as the fastest bird in the world, has been studied for its ability to stabilize during high-speed dives, a capability attributed to the configuration of its dorsal feathers. These feathers have inspired the design of vortex generators devices that promote controlled turbulence to delay boundary layer separation on aircraft wings and turbine blades. This study presents an experimental wind tunnel investigation of a bio-inspired peregrine falcon prototype, equipped with movable artificial feathers, a hot-wire anemometer, and a 3D accelerometer. Wake velocity profiles measured behind the prototype revealed fluctuations associated with feather motion. Spectral analysis of the velocity signals, recorded with oscillating feathers at a wind tunnel speed of 10 m/s, showed attenuation of specific frequency components, suggesting that feather dynamics may help mitigate wake fluctuations induced by structural vibrations. Three-dimensional acceleration measurements indicated that prototype vibrations remained below 1 g, with peak differences along the X and Z axes ranging from −0.06 g to 0.06 g, demonstrating the sensitivity of the vibration sensing system. Root Mean Square (RMS) values of velocity signals increased with wind tunnel speed but decreased as the feather inclination angle rose. When the mean value was subtracted from the signal, higher RMS variability was observed, reflecting increased flow disturbance from feather movement. Fast Fourier Transform (FFT) analysis revealed that, for fixed feather angles, spectral magnitudes increased uniformly with wind speed. In contrast, dynamic feather oscillation produced distinctive frequency peaks, highlighting the feather’s influence on the wake structure in the frequency domain. To complement the experimental findings, 3D CFD simulations were conducted on two HAWT-type wind turbines—one with bio-inspired vortex generators and one without. The simulations showed a significant reduction in turbulent kinetic energy contours in the wake of the modified turbine, particularly in the Y-Z plane, compared to the baseline configuration. Full article

The transportation and automotive industries are slowly integrating biocomposite materials into products where the economics make sense; this typically means a short manufacturing cycle time, not using expensive prepreg, and with little waste generated from the process. In a previous investigation into the use of biocomposites for electric bus seats and backs, three different material systems (hemp, flax, and pure cellulosic fibers, each paired with a high-bio-content epoxy) and two manufacturing processes (wet layup followed by compression molding, vacuum-assisted resin transfer molding) were investigated, but neither process proved to be viable. In this paper, a relatively obscure process called Wet Compression Molding (WCM) is considered for economical production of the biocomposite bus seats using the same three material systems. Darcy’s law predictions of full impregnation time for a nominally 3.5 mm thick part using experimentally determined permeability values are all less than 2 s. Furthermore, prepreg is not used, and net-shape parts without excess resin show potential. Important design details of the WCM mold set, used in the manufacturing of flat test panels from each material system, that are generally not discussed in the literature include a high-pressure O-ring seal, and semi-permeable membranes covering injection pins and vacuum vents (evacuates trapped air) to prevent resin ingress. Biocomposite laminate specimens are fabricated using the mold set in a thermal press and a vacuum pump. Part characterization includes fiber volume fraction estimates and measurements of thickness, density, flexural modulus, and outer fiber maximum stress at failure. Due to its rapid impregnation with just enough resin, WCM should be considered for the economical manufacture of parts similar in shape and size to electric bus seats and backs. Full article