Search Results (87)

Background and Objectives: Early ambulation and timely detection of postoperative complications are cornerstones of colorectal Enhanced Recovery After Surgery (ERAS) programmes, yet the traditional bedside checks performed every 4–8 h may miss clinically relevant deterioration. The consumer wearables boom has spawned a new generation of wrist- or waistband-mounted sensors that stream step count, heart-rate and temperature data continuously, creating an opportunity for data-driven early-warning strategies. No previous systematic review has focused exclusively on colorectal surgery. Methods: Three databases (PubMed, Embase, and Scopus) were searched (inception—1 May 2025) for prospective or retrospective studies that used a consumer-grade or medical-grade wearable to collect objective physical-activity or vital-sign data during the peri-operative period of elective colorectal resection. Primary outcomes were postoperative complication rates, length-of-stay (LOS) and 30-day readmission. Two reviewers screened records, extracted data and performed risk-of-bias appraisals with ROBINS-I or RoB 2. Narrative synthesis was adopted because of the heterogeneity in devices, recording windows and outcome definitions. Results: Nine studies (n = 778 patients) met eligibility: one randomised controlled trial (RCT), seven prospective cohort studies and one retrospective analysis. Five studies relied on step-count metrics alone; four combined step-count with heart-rate or skin-temperature streams. Median wear time was 6 d (range 2–30). Higher day-1 step count (≥1000 steps) was associated with shorter LOS (odds ratio 0.63; 95% CI 0.45–0.84). Smart-band–augmented ERAS pathways shortened protocol-defined LOS by 1.1 d. Pre-operative inactivity (<5000 steps·day⁻¹) and low “return-to-baseline” activity on the day before discharge independently predicted any complication (OR 0.39) and 30-day readmission (OR 0.60 per 10% increment). A prospective 101-patient study that paired pedometer-recorded ambulation with daily lung-ultrasound scores found fewer pulmonary complications when patients walked further (Spearman r = –0.36, p < 0.05). Conclusions: Continuous, patient-worn sensors are feasible and yield clinically meaningful data after colorectal surgery. Early postoperative step-count trajectories and activity-derived recovery indices correlate with LOS, complications and readmission, supporting their incorporation into digital ERAS dashboards. Standardised outcome definitions, open algorithms for signal processing and multicentre validation are now required. Full article

Saxitoxin (STX) is a toxin with paralyzing and lethal properties, necessitating the development of a simple analytical method. This study developed a nucleic acid aptamer biosensor using graphene oxide (GO) as a fluorescence quencher for STX detection. GO was combined with M30-f, an STX nucleic acid aptamer modification with 5-carboxyfluorescein, which can produce fluorescence absorption under the conditions of an excitation wavelength of 408 nm and emission wavelength of 515 nm. Based on the principle of fluorescence resonance energy transfer, the fluorescence of M30-f was quenched. In the presence of STX, M30-f specifically binds to STX and dissociates from the GO surface, thereby restoring fluorescence. The STX content can be quantitatively detected through differences in fluorescence absorption. The influence of ultrasonic time on the fluorescence quenching ability of GO was investigated. The aqueous solution of graphene oxide, 30GO, optimized by ultrasound treatment for a duration of 30 min, demonstrated excellent fluorescence quenching capability. 30GO was analyzed utilizing various characterization techniques, including SEM, FT-IR, UV, XPS, XRD, AFM, and contact angle measurements. The methodological validation showed that the established STX sensor exhibits excellent linearity within a concentration range of 10–100,000 ng/L, with a limit of detection (LOD) as low as 0.098 μg/L. In addition, the results further demonstrated the sensor’s high specificity for detecting neurotoxic shellfish toxin STX. The recovery rate for clam samples ranged from 89.12% to 104.71%, while that for oyster samples ranged from 91.20% to 109.65%, with relative standard deviations (RSDs) all below 3%. This aptamer sensor is characterized by its simplicity, high sensitivity, and broad detection range, providing significant technical support for advancing marine biotoxin research. Full article

For the first time, comprehensive investigations into the tensile load-bearing behavior and crack formation of reinforced concrete based on ultrasound are presented. Uniaxial tensile tests are performed on reinforced concrete tension members equipped with embedded ultrasonic transducers. Key mechanical parameters across all ranges of tensile behavior are continuously quantified by recording ultrasonic signals and evaluated with coda wave interferometry. The investigations include member configurations of different lengths to cover different numbers of cracks. For reference, crack patterns and crack widths are analyzed using digital image correlation, while the strain in the reinforcement is monitored with distributed fiber optic sensors. For the first time, a direct proportional relationship between the relative velocity change in ultrasonic signals and crack widths is established in the ranges of crack formation and stabilized cracking. In the non-cracked state, linear correlations are found between the velocity change and the average strain, as well as the length of the specimens. The experimental results significantly enhance the general understanding of the phenomena related to ultrasonic signals in flexural reinforced concrete members, particularly concerning cracking in the tensile zone. Consequently, this study contributes to the broader objective of employing coda wave interferometry to evaluate the condition of infrastructure. Full article

Railway infrastructures necessitate the inspection of various elements to ensure operational safety. This study concentrates on five key components: rail, sleepers and ballast, track geometry, and catenary. The operational principles of the primary defect measurement sensors are elaborated, emphasizing the use of ultrasound, eddy currents, active and passive optical elements, accelerometers, and ground penetrating radar. Each sensor type is evaluated in terms of its advantages and limitations. Examples of mobile inspection platforms are provided, ranging from laboratory trains to draisines and track trolleys. The authors foresee future trends in railway inspection, including the implementation of IoT sensors, autonomous robots, and geospatial intelligence technologies. It is anticipated that the integration of sensors within both infrastructure and rolling stock will enhance maintenance and safety, with an increased utilization of autonomous robotic systems for hazardous and hard-to-reach areas. Full article

In this literature review, methods for the detection of breast cancer biomarkers and the operation of electrochemical sensors are considered. The work of sensors in the determination of breast cancer biomarkers was systematized, a comparative table with other methods was compiled, as was a classification of sensors depending on their intended use. The various traditional methods for the diagnosis of breast cancer biomarkers are described, including mammography, ultrasound, magnetic resonance imaging, positron emission computed tomography, computed tomography, single-photon emission computed tomography, and biopsy, and their advantages and disadvantages are presented. Key sensor parameters for the detection of breast cancer biomarkers are compared, such as the detection limit, linear detection range, response time, sensitivity, and other characteristics depending on the analyte being analyzed. Based on the reviewed scientific papers, the significance of electrochemical sensors in detecting the biomarkers of breast cancer is demonstrated. The types of tumor biomarkers identified by biosensors were analyzed, with a particular focus on HER2. Studies on HER2 detection using electrochemical methods are compared and systematized, and the features of electrochemical biosensors for determining this biomarker are characterized. Possible interfering agents affecting the accuracy of HER2 determination under experimental conditions are considered, their mechanisms of action are analyzed, and ways to eliminate them are proposed. This report provides a summary of the current aspects of scientific research on electrochemical sensors for the detection of breast cancer biomarkers. The development of electrochemical biosensors opens up new prospects for the early diagnosis and prognosis of breast cancer treatment. Full article

Numerous strategies have been demonstrated to enhance the mechanical stretchability of electromechanical sensors for widespread applications in wearable electronics. However, ranging from composite to microstructural materials, their electromechanical sensing performances are usually vulnerable to large stretching deformations due to the low-ductility of the infilled conductive components and the modulus mismatch between the flexible polymer substrate and conductive fillers. Here, a novel design strategy is proposed to fabricate ultra-stretchable electromechanical composites constructed by a triple-level interaction conductive network (Tri-LICN) in buckled-TPU microfibers for strain sensors. The Tri-LICN is established by bridging one-dimensional cellulose nanocrystals (CNC) with zero-dimensional gold-nanoparticles (AuNPs) and two-dimensional MXene sheets using interface self-assembly and ultrasound-assisted anchoring to eliminate the modulus mismatching between the conductive material and polymer substrate. The buckled-TPU microfibers are introduced to improve the mechanical stretchability of composites by the external-stimuli-induced imbalance of the stretching conformation of TPU macromolecules. The Tri-LICN MXene/CNC/AuNPs@TPU composite sensor displays an enhanced strain sensitivity (GF~2514) with a fast response time (~150 ms) over a wide operational strain up to 200% and excellent durability over 1000 tensile cycles. Our finding offers a promising approach to enhancing the performance of stretchable sensors based on polymer materials, providing new opportunities for the development of next-generation electronics. Full article

Hand gesture recognition (HGR) is a convenient and natural form of human–computer interaction. It is suitable for various applications. Much research has already focused on wearable device-based HGR. By contrast, this paper gives an overview focused on device-free HGR. That means we evaluate HGR systems that do not require the user to wear something like a data glove or hold a device. HGR systems are explored regarding technology, hardware, and algorithms. The interconnectedness of timing and power requirements with hardware, pre-processing algorithm, classification, and technology and how they permit more or less granularity, accuracy, and number of gestures is clearly demonstrated. Sensor modalities evaluated are WIFI, vision, radar, mobile networks, and ultrasound. The pre-processing technologies stereo vision, multiple-input multiple-output (MIMO), spectrogram, phased array, range-doppler-map, range-angle-map, doppler-angle-map, and multilateration are explored. Classification approaches with and without ML are studied. Among those with ML, assessed algorithms range from simple tree structures to transformers. All applications are evaluated taking into account their level of integration. This encompasses determining whether the application presented is suitable for edge integration, their real-time capability, whether continuous learning is implemented, which robustness was achieved, whether ML is applied, and the accuracy level. Our survey aims to provide a thorough understanding of the current state of the art in device-free HGR on edge devices and in general. Finally, on the basis of present-day challenges and opportunities in this field, we outline which further research we suggest for HGR improvement. Our goal is to promote the development of efficient and accurate gesture recognition systems. Full article

Predicting meat quality, especially dark, firm and dry meat, as well as muscle fat prior to slaughter, presents a challenge in practice. Medical as well as high-frequency ultrasound applications can be utilized to predict body composition and meat quality aspects. Ultrasounds are non-invasive, rapid-to-operate in vivo and show high correlations to the animal production traits being estimated. Farm animal ultrasounds are used to predict intramuscular fat content in the beef cattle industry. Challenges are identified in applying ultrasound technology to detect glycogen content in farm animals due to a wide range of fat, muscle and water composition. Other technologies and methods are reported in this literature review to overcome issues in the practicability and accuracy of ultrasound technology when estimating muscle glycogen levels in cattle. The discussion of other tools such as hyperspectral imaging, microwave sensor technology and digital infrared thermal imaging were addressed because of their superior accuracy in estimating moisture and fat components. Full article

In areas where there is high humidity and freezing rain, there is a tendency of blade icing on wind turbines. It results in energy dissipation and mechanical abrasion and also creates a safety concern due to the risk of having falling ice. Real-time online detection of icing is crucial in the enhancement of power generation efficiency and in the safety of wind turbines. The current methods of icing detection that use ultrasound, optics, vibration, and electromagnetics are already studied. But these methods have their drawbacks, including small detection ranges, low accuracy, large size, and challenges in distributed installation, making it hard to capture the real-time dynamics of the icing and de-icing processes on the wind turbine blades. To this end, this paper presents a new blade surface icing detection technique using microstrip lines. This approach uses the impact of icing state and thickness on the effective dielectric constant of the microstrip line surface. This paper presents the analysis of time-domain features of microwave signals, which facilitates the identification of both the icing state and the corresponding thickness. Simulation and experimental measurement of linear and S-shaped microstrip sensors are used in this research in order to compare the response of the sensors to the variation in the thickness of the icing layer. It is seen that for icing thickness ranging from 0 mm to 6 mm, the imaginary part of the S21 parameter of the S-shaped microstrip line has a more significant change than that of the linear microstrip line. The above experiments also confirm that the phase shift value of the S-shaped microstrip line is always higher than that of the linear microstrip line for the same variation of icing thickness, which proves that the S-shaped microstrip line is more sensitive than the linear one. Also, it was possible to establish the relationship between the phase shift values and icing thickness, which makes it possible to predict the icing thickness. The developed microwave microstrip detection technology is intended for usage in the wind turbine blade icing and similar surface detection areas. This method saves the size and thickness of icing sensors, which makes it possible to conduct measurements at various points. This is especially beneficial for usage in wind turbine blades and can be further applied in aerospace, automotive, and construction, especially the bridges. Full article

Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecting image quality and reproducibility. Robot-assisted ultrasound may provide a solution by delivering more consistent, precise, and faster scans, potentially reducing human error and healthcare costs. Effective force control is crucial in robotic ultrasound scanning to ensure consistent image quality and patient safety. However, existing robotic ultrasound systems rely heavily on expensive commercial force sensors or the integrated sensors of commercial robotic arms, limiting their accessibility. To address these challenges, we developed a cost-effective, lightweight, 3D-printed force sensor and a hybrid position–force control strategy tailored for robotic ultrasound scanning. The system integrates patient-to-robot registration, automated scanning path planning, and multi-sensor data fusion, allowing the robot to autonomously locate the patient, target the region of interest, and maintain optimal contact force during scanning. Validation was conducted using an ultrasound-compatible abdominal aortic aneurysm (AAA) phantom created from patient CT data and healthy volunteer testing. For the volunteer testing, during a 1-min scan, 65% of the forces were within the good image range. Both volunteers reported no discomfort or pain during the whole procedure. These results demonstrate the potential of the system to provide safe, precise, and autonomous robotic ultrasound imaging in real-world conditions. Full article

Piezoelectric micromachined ultrasonic transducers (PMUTs) have been widely applied in distance sensing applications. However, the rapid movement of miniature robots in complex environments necessitates higher ranging capabilities from sensors, making the enhancement of PMUT sensing distance critically important. In this paper, a scandium-doped aluminum nitride (ScAlN) PMUT based on a flexurally suspended membrane is proposed. Unlike the traditional fully clamped design, the PMUT incorporates a partially clamped membrane, thereby extending the vibration displacement and enhancing the output sound pressure. Experimental results demonstrate that at a resonant frequency of 78 kHz, a single PMUT generates a sound pressure level (SPL) of 112.2 dB at a distance of 10 mm and achieves a high receiving sensitivity of 12.3 mV/Pa. Distance testing reveals that a single PMUT equipped with a horn can achieve a record-breaking distance sensing range of 11.2 m when used alongside a device capable of simultaneously transmitting and receiving ultrasound signals. This achievement is significant for miniaturized and integrated applications that utilize ultrasound for long-range target detection. Full article

Perception systems for assisted driving and autonomy enable the identification and classification of objects through a concentration of sensors installed in vehicles, including Radio Detection and Ranging (RADAR), camera, Light Detection and Ranging (LIDAR), ultrasound, and HD maps. These sensors ensure a reliable and robust navigation system. Radar, in particular, operates with electromagnetic waves and remains effective under a variety of weather conditions. It uses point cloud technology to map the objects in front of you, making it easy to group these points to associate them with real-world objects. Numerous clustering algorithms have been developed and can be integrated into radar systems to identify, investigate, and track objects. In this study, we evaluate several clustering algorithms to determine their suitability for application in automotive radar systems. Our analysis covered a variety of current methods, the mathematical process of these methods, and presented a comparison table between these algorithms, including Hierarchical Clustering, Affinity Propagation Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Mini-Batch K-Means, K-Means Mean Shift, OPTICS, Spectral Clustering, and Gaussian Mixture. We have found that K-Means, Mean Shift, and DBSCAN are particularly suitable for these applications, based on performance indicators that assess suitability and efficiency. However, DBSCAN shows better performance compared to others. Furthermore, our findings highlight that the choice of radar significantly impacts the effectiveness of these object recognition methods. Full article

Tert-butylhydroquinone (TBHQ) is a phenolic substance that is commonly employed to prevent food oxidation. Excessive or improper utilization of this antioxidant can not only impact food quality but may also pose potential risks to human health. In this study, an ultrasensitive, stable, and easily operable ratiometric electrochemical sensor was successfully fabricated by combining the tubular (3,4-ethylenedioxythiophene) (T-PEDOT) with single-wall carbon nanohorns (SWCNHs) for the detection of TBHQ antioxidants in food. The SWCNHs/T-PEDOT nanocomposite fabricated through ultrasound-assisted and template approaches was employed as the modified substrate for the electrode interface. The synergistic effect of SWCNHs and T-PEDOT, which possess excellent electrical conductivity and catalytic properties, enabled the modified electrode to showcase remarkable electrocatalytic performance towards TBHQ, with the redox signal of methylene blue serving as an internal reference. Under optimized conditions, the SWCNHs/T-PEDOT-modified electrode demonstrated good linearity within the TBHQ concentration range of 0.01–200.0 μg mL⁻¹, featuring a low limit of detection (LOD) of 0.005 μg mL⁻¹. The proposed ratiometric electrochemical sensor displayed favorable reproducibility, stability, and anti-interference capacity, thereby offering a promising strategy for monitoring the levels of TBHQ in oil-rich food products. Full article

Physiotherapy plays a crucial role in the rehabilitation of damaged or defective organs due to injuries or illnesses, often requiring long-term supervision by a physiotherapist in clinical settings or at home. AI-based support systems have been developed to enhance the precision and effectiveness of physiotherapy, particularly during the COVID-19 pandemic. These systems, which include game-based or tele-rehabilitation monitoring using camera-based optical systems like Vicon and Microsoft Kinect, face challenges such as privacy concerns, occlusion, and sensitivity to environmental light. Non-optical sensor alternatives, such as Inertial Movement Units (IMUs), Wi-Fi, ultrasound sensors, and ultrawide band (UWB) radar, have emerged to address these issues. Although IMUs are portable and cost-effective, they suffer from disadvantages like drift over time, limited range, and susceptibility to magnetic interference. In this study, a single UWB radar was utilized to recognize five therapeutic exercises related to the upper limb, performed by 34 male volunteers in a real environment. A novel feature fusion approach was developed to extract distinguishing features for these exercises. Various machine learning methods were applied, with the EnsembleRRGraBoost ensemble method achieving the highest recognition accuracy of 99.45%. The performance of the EnsembleRRGraBoost model was further validated using five-fold cross-validation, maintaining its high accuracy. Full article

The piezoelectric effect refers to a physical phenomenon where piezoelectric materials generate an electric field when subjected to mechanical stress or undergo mechanical deformation when subjected to an external electric field. This principle underlies the operation of piezoelectric sensors. Piezoelectric sensors have garnered significant attention due to their excellent self-powering capability, rapid response speed, and high sensitivity. With the rapid development of sensor techniques achieving high precision, increased mechanical flexibility, and miniaturization, a range of flexible electronic products have emerged. As the core constituents of piezoelectric sensors, flexible piezoelectric composite materials are commonly used due to their unique advantages, including high conformability, sensitivity, and compatibility. They have found applications in diverse domains such as underwater detection, electronic skin sensing, wearable sensors, targeted therapy, and ultrasound diagnostics for deep tissue. The advent of flexible piezoelectric composite materials has revolutionized the design concepts and application scenarios of traditional piezoelectric materials, playing a crucial role in the development of next-generation flexible electronic products. This paper reviews the research progress on flexible piezoelectric composite materials, covering their types and typical fabrication techniques, as well as their applications across various fields. Finally, a summary and outlook on the existing issues and future development of these composite materials are provided. Full article