Journal Description
Sensors
Sensors
is an international, peer-reviewed, open access journal on the science and technology of sensors. Sensors is published semimonthly online by MDPI. The Polish Society of Applied Electromagnetics (PTZE), Japan Society of Photogrammetry and Remote Sensing (JSPRS), Spanish Society of Biomedical Engineering (SEIB) and International Society for the Measurement of Physical Behaviour (ISMPB) are affiliated with Sensors and their members receive a discount on the article processing charges.
- Open Access — free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, MEDLINE, PMC, Ei Compendex, Inspec, Astrophysics Data System, and other databases.
- Journal Rank: JCR - Q2 (Instruments & Instrumentation) / CiteScore - Q1 (Instrumentation)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about Sensors.
- Companion journals for Sensors include: Chips, Automation, JCP and Targets.
Impact Factor:
3.9 (2022);
5-Year Impact Factor:
4.1 (2022)
Latest Articles
Reducing Driving Risk Factors in Adolescents with Attention Deficit Hyperactivity Disorder (ADHD): Insights from EEG and Eye-Tracking Analysis
Sensors 2024, 24(11), 3319; https://doi.org/10.3390/s24113319 (registering DOI) - 23 May 2024
Abstract
Adolescents with attention deficit hyperactivity disorder (ADHD) face significant driving challenges due to deficits in attention and executive functioning, elevating their road risks. Previous interventions targeting driving safety among this cohort have typically addressed isolated aspects (e.g., cognitive or behavioral factors) or relied
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Adolescents with attention deficit hyperactivity disorder (ADHD) face significant driving challenges due to deficits in attention and executive functioning, elevating their road risks. Previous interventions targeting driving safety among this cohort have typically addressed isolated aspects (e.g., cognitive or behavioral factors) or relied on uniform solutions. However, these approaches often overlook this population’s diverse needs. This study introduces the “Drive-Fun” innovative intervention (DFI), aimed at enhancing driving skills among this vulnerable population. The intervention was tested in a pilot study including 30 adolescents aged 15–18, comparing three groups: DFI, an educational intervention, and a control group with no treatment. Assessments included a driving simulator, EEG, and Tobii Pro Glasses 2. Evaluation was conducted pre- and post-intervention and at a 3-month follow-up. Results indicated that the DFI group significantly improved in the simulated driving performance, attentional effort, and focused gaze time. The findings underscore that holistic strategies with personalized, comprehensive approaches for adolescents with ADHD are particularly effective in improving driving performance. These outcomes not only affirm the feasibility of the DFI but also highlight the critical role of sensor technologies in accurately measuring and enhancing simulator driving performance in adolescents with ADHD. Outcomes suggest a promising direction for future research and application.
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(This article belongs to the Special Issue Advances in Principles, Methods and Applications of Brain-Computer Interaction)
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Open AccessArticle
Quantifying Changes in Dexterity as a Result of Piano Training in People with Parkinson’s Disease
by
Hila Tamir-Ostrover, Sharon Hassin-Baer, Tsvia Fay-Karmon and Jason Friedman
Sensors 2024, 24(11), 3318; https://doi.org/10.3390/s24113318 - 22 May 2024
Abstract
People with Parkinson’s disease often show deficits in dexterity, which, in turn, can lead to limitations in performing activities of daily life. Previous studies have suggested that training in playing the piano may improve or prevent a decline in dexterity in this population.
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People with Parkinson’s disease often show deficits in dexterity, which, in turn, can lead to limitations in performing activities of daily life. Previous studies have suggested that training in playing the piano may improve or prevent a decline in dexterity in this population. In this pilot study, we tested three participants on a six-week, custom, piano-based training protocol, and quantified dexterity before and after the intervention using a sensor-enabled version of the nine-hole peg test, the box and block test, a test of finger synergies using unidimensional force sensors, and the Quantitative Digitography test using a digital piano, as well as selected relevant items from the motor parts of the MDS-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) and the Parkinson’s Disease Questionnaire (PDQ-39) quality of life questionnaire. The participants showed improved dexterity following the training program in several of the measures used. This pilot study proposes measures that can track changes in dexterity as a result of practice in people with Parkinson’s disease and describes a potential protocol that needs to be tested in a larger cohort.
Full article
(This article belongs to the Special Issue Advanced Wearable Sensors and Other Sensing Technologies for Diagnosis and Treatment of Parkinson's Disease and Movement Disorders)
Open AccessArticle
A Robust End-to-End IoT System for Supporting Workers in Mining Industries
by
Marios Vlachos, Lampros Pavlopoulos, Anastasios Georgakopoulos, Georgios Tsimiklis and Angelos Amditis
Sensors 2024, 24(11), 3317; https://doi.org/10.3390/s24113317 - 22 May 2024
Abstract
The adoption of the Internet of Things (IoT) in the mining industry can dramatically enhance the safety of workers while simultaneously decreasing monitoring costs. By implementing an IoT solution consisting of a number of interconnected smart devices and sensors, mining industries can improve
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The adoption of the Internet of Things (IoT) in the mining industry can dramatically enhance the safety of workers while simultaneously decreasing monitoring costs. By implementing an IoT solution consisting of a number of interconnected smart devices and sensors, mining industries can improve response times during emergencies and also reduce the number of accidents, resulting in an overall improvement of the social image of mines. Thus, in this paper, a robust end-to-end IoT system for supporting workers in harsh environments such as in mining industries is presented. The full IoT solution includes both edge devices worn by the workers in the field and a remote cloud IoT platform, which is responsible for storing and efficiently sharing the gathered data in accordance with regulations, ethics, and GDPR rules. Extended experiments conducted to validate the IoT components both in the laboratory and in the field proved the effectiveness of the proposed solution in monitoring the real-time status of workers in mines.
Full article
(This article belongs to the Special Issue Industrial Internet of Things in the Industry 4.0: New Researches, Applications and Challenges (Volume II))
Open AccessArticle
Evaluation of EEG Signals by Spectral Peak Methods and Statistical Correlation for Mental State Discrimination Induced by Arithmetic Tasks
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Daniela Andreea Coman, Silviu Ionita and Ioan Lita
Sensors 2024, 24(11), 3316; https://doi.org/10.3390/s24113316 - 22 May 2024
Abstract
Bringing out brain activity through the interpretation of EEG signals is a challenging problem that involves combined methods of signal analysis. The issue of classifying mental states induced by arithmetic tasks can be solved through various classification methods, using diverse characteristic parameters of
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Bringing out brain activity through the interpretation of EEG signals is a challenging problem that involves combined methods of signal analysis. The issue of classifying mental states induced by arithmetic tasks can be solved through various classification methods, using diverse characteristic parameters of EEG signals in the time, frequency, and statistical domains. This paper explores the results of an experiment that aimed to highlight arithmetic mental tasks contained in the PhysioNet database, performed on a group of 36 subjects. The majority of publications on this topic deal with machine learning (ML)-based classification methods with supervised learning support vector machine (SVM) algorithms, K-Nearest Neighbor (KNN), Linear Discriminant Analysis (LDA), and Decision Trees (DTs). Also, there are frequent approaches based on the analysis of EEG data as time series and their classification with Recurrent Neural Networks (RNNs), as well as with improved algorithms such as Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BLSTM), and Gated Recurrent Units (GRUs). In the present work, we evaluate the classification method based on the comparison of domain limits for two specific characteristics of EEG signals: the statistical correlation of pairs of signals and the size of the spectral peak detected in theta, alpha, and beta bands. This study provides some interpretations regarding the electrical activity of the brain, consolidating and complementing the results of similar research. The classification method used is simple and easy to apply and interpret. The analysis of EEG data showed that the theta and beta frequency bands were the only discriminators between the relaxation and arithmetic calculation states. Notably, the F7 signal, which used the spectral peak criterion, achieved the best classification accuracy (100%) in both theta and beta bands for the subjects with the best results in performing calculations. Also, our study found the Fz signal to be a good sensor in the theta band for mental task discrimination for all subjects in the group with 90% accuracy.
Full article
(This article belongs to the Section Biomedical Sensors)
Open AccessArticle
Evaluation of Different Types of Stimuli in an Event-Related Potential-Based Brain–Computer Interface Speller under Rapid Serial Visual Presentation
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Ricardo Ron-Angevin, Álvaro Fernández-Rodríguez, Francisco Velasco-Álvarez, Véronique Lespinet-Najib and Jean-Marc André
Sensors 2024, 24(11), 3315; https://doi.org/10.3390/s24113315 - 22 May 2024
Abstract
Rapid serial visual presentation (RSVP) is currently a suitable gaze-independent paradigm for controlling visual brain–computer interfaces (BCIs) based on event-related potentials (ERPs), especially for users with limited eye movement control. However, unlike gaze-dependent paradigms, gaze-independent ones have received less attention concerning the specific
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Rapid serial visual presentation (RSVP) is currently a suitable gaze-independent paradigm for controlling visual brain–computer interfaces (BCIs) based on event-related potentials (ERPs), especially for users with limited eye movement control. However, unlike gaze-dependent paradigms, gaze-independent ones have received less attention concerning the specific choice of visual stimuli that are used. In gaze-dependent BCIs, images of faces—particularly those tinted red—have been shown to be effective stimuli. This study aims to evaluate whether the colour of faces used as visual stimuli influences ERP-BCI performance under RSVP. Fifteen participants tested four conditions that varied only in the visual stimulus used: grey letters (GL), red famous faces with letters (RFF), green famous faces with letters (GFF), and blue famous faces with letters (BFF). The results indicated significant accuracy differences only between the GL and GFF conditions, unlike prior gaze-dependent studies. Additionally, GL achieved higher comfort ratings compared with other face-related conditions. This study highlights that the choice of stimulus type impacts both performance and user comfort, suggesting implications for future ERP-BCI designs for users requiring gaze-independent systems.
Full article
(This article belongs to the Special Issue Brain Computer Interface for Biomedical Applications)
Open AccessArticle
Adaptive Multi-Sensor Joint Tracking Algorithm with Unknown Noise Characteristics
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Weihao Sun, Yi Wang, Weifeng Diao and Lin Zhou
Sensors 2024, 24(11), 3314; https://doi.org/10.3390/s24113314 - 22 May 2024
Abstract
In this study, to solve the low accuracy of multi-space-based sensor joint tracking in the presence of unknown noise characteristics, an adaptive multi-sensor joint tracking algorithm (AMSJTA) is proposed. First, the coordinate transformation from the target object to the optical sensors is considered,
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In this study, to solve the low accuracy of multi-space-based sensor joint tracking in the presence of unknown noise characteristics, an adaptive multi-sensor joint tracking algorithm (AMSJTA) is proposed. First, the coordinate transformation from the target object to the optical sensors is considered, and the observation vector-based measurement model is established. Then, the measurement noise characteristics are assumed to be white Gaussian noise, and the measurement covariance matrix is set as a constant. On this premise, the traditional iterative extended Kalman filter is applied to solve this problem. However, in most actual engineering applications, the measurement noise characteristics are unknown. Thus, a forgetting factor is introduced to adaptively estimate the unknown measurement noise characteristics, and the AMSJTA is designed to improve the tracking accuracy. Furthermore, the lower bound of the proposed algorithm is theoretically proved. Finally, numerical simulations are executed to verify the effectiveness and superiority of the proposed AMSJTA.
Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle
Research on Miniaturized UHF Sensing Technology for PD Detection in Power Equipment Based on Symmetric Cut Theory
by
Bowen Xu, Chaoqian Duan, Jiangfan Wang, Lei Zhang, Guozhi Zhang, Guoguang Zhang and Guangke Li
Sensors 2024, 24(11), 3313; https://doi.org/10.3390/s24113313 - 22 May 2024
Abstract
In answer to the demand for high sensitivity and miniaturization of ultra-high frequency (UHF) sensors for partial discharge (PD) detection in power equipment, this paper proposes research on miniaturized UHF-sensing technology for PD detection in power equipment based on symmetric cut theory. The
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In answer to the demand for high sensitivity and miniaturization of ultra-high frequency (UHF) sensors for partial discharge (PD) detection in power equipment, this paper proposes research on miniaturized UHF-sensing technology for PD detection in power equipment based on symmetric cut theory. The symmetric cut theory is applied for the first time to the miniaturization of PD UHF sensors for power equipment. A planar monopole UHF sensor with a size of only 70 mm × 70 mm × 1.6 mm is developed using an exponential asymptotic feed line approach, which is a 50% size reduction. The frequency–response characteristics of the sensor are simulated, optimized and tested; the results show that the standing wave ratio of the sensor developed in this paper is less than 2 in the frequency band from 427 MHz to 1.54 GHz, and less than 5 in the frequency band from 300 MHz to 1.95 GHz; in the 300 MHz~1.5 GHz band; the maximum and average gains of the sensor E-plane are 4.76 dB and 1.02 dB, respectively. Finally, the PD simulation experiment platform for power equipment is built to test the sensor’s sensing performance; the results show that the sensor can effectively detect the PD signals; the sensing sensitivity is improved by about 95% relative to an elliptical monopole UHF sensor.
Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
Open AccessReview
Passive Polarized Vision for Autonomous Vehicles: A Review
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Julien R. Serres, Pierre-Jean Lapray, Stéphane Viollet, Thomas Kronland-Martinet, Antoine Moutenet, Olivier Morel and Laurent Bigué
Sensors 2024, 24(11), 3312; https://doi.org/10.3390/s24113312 - 22 May 2024
Abstract
This review article aims to address common research questions in passive polarized vision for robotics. What kind of polarization sensing can we embed into robots? Can we find our geolocation and true north heading by detecting light scattering from the sky as animals
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This review article aims to address common research questions in passive polarized vision for robotics. What kind of polarization sensing can we embed into robots? Can we find our geolocation and true north heading by detecting light scattering from the sky as animals do? How should polarization images be related to the physical properties of reflecting surfaces in the context of scene understanding? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying future directions in passive polarized vision for robotics. After an introduction, three key interconnected areas will be covered in the following sections: embedded polarization imaging; polarized vision for robotics navigation; and polarized vision for scene understanding. We will then discuss how polarized vision, a type of vision commonly used in the animal kingdom, should be implemented in robotics; this type of vision has not yet been exploited in robotics service. Passive polarized vision could be a supplemental perceptive modality of localization techniques to complement and reinforce more conventional ones.
Full article
(This article belongs to the Special Issue Multispectral, Polarized and Unconventional Vision in Robotics)
Open AccessArticle
Implementation of Engagement Detection for Human–Robot Interaction in Complex Environments
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Sin-Ru Lu, Jia-Hsun Lo, Yi-Tian Hong and Han-Pang Huang
Sensors 2024, 24(11), 3311; https://doi.org/10.3390/s24113311 - 22 May 2024
Abstract
This study develops a comprehensive robotic system, termed the robot cognitive system, for complex environments, integrating three models: the engagement model, the intention model, and the human–robot interaction (HRI) model. The system aims to enhance the naturalness and comfort of HRI by enabling
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This study develops a comprehensive robotic system, termed the robot cognitive system, for complex environments, integrating three models: the engagement model, the intention model, and the human–robot interaction (HRI) model. The system aims to enhance the naturalness and comfort of HRI by enabling robots to detect human behaviors, intentions, and emotions accurately. A novel dual-arm-hand mobile robot, Mobi, was designed to demonstrate the system’s efficacy. The engagement model utilizes eye gaze, head pose, and action recognition to determine the suitable moment for interaction initiation, addressing potential eye contact anxiety. The intention model employs sentiment analysis and emotion classification to infer the interactor’s intentions. The HRI model, integrated with Google Dialogflow, facilitates appropriate robot responses based on user feedback. The system’s performance was validated in a retail environment scenario, demonstrating its potential to improve the user experience in HRIs.
Full article
(This article belongs to the Special Issue Emotion Recognition Technologies in Human-Machine Interaction)
Open AccessReview
An Overview of Millimeter-Wave Radar Modeling Methods for Autonomous Driving Simulation Applications
by
Kaibo Huang, Juan Ding and Weiwen Deng
Sensors 2024, 24(11), 3310; https://doi.org/10.3390/s24113310 - 22 May 2024
Abstract
Autonomous driving technology is considered the trend of future transportation. Millimeter-wave radar, with its ability for long-distance detection and all-weather operation, is a key sensor for autonomous driving. The development of various technologies in autonomous driving relies on extensive simulation testing, wherein simulating
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Autonomous driving technology is considered the trend of future transportation. Millimeter-wave radar, with its ability for long-distance detection and all-weather operation, is a key sensor for autonomous driving. The development of various technologies in autonomous driving relies on extensive simulation testing, wherein simulating the output of real radar through radar models plays a crucial role. Currently, there are numerous distinctive radar modeling methods. To facilitate the better application and development of radar modeling methods, this study first analyzes the mechanism of radar detection and the interference factors it faces, to clarify the content of modeling and the key factors influencing modeling quality. Then, based on the actual application requirements, key indicators for measuring radar model performance are proposed. Furthermore, a comprehensive introduction is provided to various radar modeling techniques, along with the principles and relevant research progress. The advantages and disadvantages of these modeling methods are evaluated to determine their characteristics. Lastly, considering the development trends of autonomous driving technology, the future direction of radar modeling techniques is analyzed. Through the above content, this paper provides useful references and assistance for the development and application of radar modeling methods.
Full article
(This article belongs to the Special Issue Recent Advances of FMCW-Based Radar Sensors)
Open AccessArticle
Combining Dipole and Loop Coil Elements for 7 T Magnetic Resonance Studies of the Human Calf Muscle
by
Veronika Cap, Vasco Rafael Rocha dos Santos, Kostiantyn Repnin, David Červený, Elmar Laistler, Martin Meyerspeer and Roberta Frass-Kriegl
Sensors 2024, 24(11), 3309; https://doi.org/10.3390/s24113309 - 22 May 2024
Abstract
Combining proton and phosphorus magnetic resonance spectroscopy offers a unique opportunity to study the oxidative and glycolytic components of metabolism in working muscle. This paper presents a 7 T proton calf coil design that combines dipole and loop elements to achieve the high
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Combining proton and phosphorus magnetic resonance spectroscopy offers a unique opportunity to study the oxidative and glycolytic components of metabolism in working muscle. This paper presents a 7 T proton calf coil design that combines dipole and loop elements to achieve the high performance necessary for detecting metabolites with low abundance and restricted visibility, specifically lactate, while including the option of adding a phosphorus array. We investigated the transmit, receive, and parallel imaging performance of three transceiver dipoles with six pair-wise overlap-decoupled standard or twisted pair receive-only coils. With a higher SNR and more efficient transmission decoupling, standard loops outperformed twisted pair coils. The dipoles with standard loops provided a four-fold-higher image SNR than a multinuclear reference coil comprising two proton channels and 32% more than a commercially available 28-channel proton knee coil. The setup enabled up to three-fold acceleration in the right–left direction, with acceptable g-factors and no visible aliasing artefacts. Spectroscopic phantom measurements revealed a higher spectral SNR for lactate with the developed setup than with either reference coil and fewer restrictions in voxel placement due to improved transmit homogeneity. This paper presents a new use case for dipoles and highlights their advantages for the integration in multinuclear calf coils.
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(This article belongs to the Special Issue Sensors in Magnetic Resonance Imaging)
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Open AccessCorrection
Correction: Gligoric et al. IOTA-Based Distributed Ledger in the Mining Industry: Efficiency, Sustainability and Transparency. Sensors 2024, 24, 923
by
Nenad Gligoric, David Escuín, Lorena Polo, Angelos Amditis, Tasos Georgakopoulos and Alberto Fraile
Sensors 2024, 24(11), 3308; https://doi.org/10.3390/s24113308 - 22 May 2024
Abstract
In the original publication [...]
Full article
(This article belongs to the Section Industrial Sensors)
Open AccessReview
Impact of Insertion Speed, Depth, and Robotic Assistance on Cochlear Implant Insertion Forces and Intracochlear Pressure: A Scoping Review
by
Filip Hrnčiřík, Leo Nagy, Hannah L. Grimes, Haissan Iftikhar, Jameel Muzaffar and Manohar Bance
Sensors 2024, 24(11), 3307; https://doi.org/10.3390/s24113307 - 22 May 2024
Abstract
Cochlear implants are crucial for addressing severe-to-profound hearing loss, with the success of the procedure requiring careful electrode placement. This scoping review synthesizes the findings from 125 studies examining the factors influencing insertion forces (IFs) and intracochlear pressure (IP), which are crucial for
[...] Read more.
Cochlear implants are crucial for addressing severe-to-profound hearing loss, with the success of the procedure requiring careful electrode placement. This scoping review synthesizes the findings from 125 studies examining the factors influencing insertion forces (IFs) and intracochlear pressure (IP), which are crucial for optimizing implantation techniques and enhancing patient outcomes. The review highlights the impact of variables, including insertion depth, speed, and the use of robotic assistance on IFs and IP. Results indicate that higher insertion speeds generally increase IFs and IP in artificial models, a pattern not consistently observed in cadaveric studies due to variations in methodology and sample size. The study also explores the observed minimal impact of robotic assistance on reducing IFs compared to manual methods. Importantly, this review underscores the need for a standardized approach in cochlear implant research to address inconsistencies and improve clinical practices aimed at preserving hearing during implantation.
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(This article belongs to the Section Biomedical Sensors)
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Open AccessArticle
Prediction of Pre-Loading Relaxation of Bolt Structure of Complex Equipment under Tangential Cyclic Load
by
Xiaohan Lu, Min Zhu, Chao Li, Shengnan Li, Shengao Wang and Ziwei Li
Sensors 2024, 24(11), 3306; https://doi.org/10.3390/s24113306 - 22 May 2024
Abstract
Bolts have the advantages of simple installation and easy removal. They are widely applied in aerospace and high-speed railway traffic. However, the loosening of bolts under mixed loads can lead to nonlinear decreases in pre-loading. This affects the safety performance of the structure
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Bolts have the advantages of simple installation and easy removal. They are widely applied in aerospace and high-speed railway traffic. However, the loosening of bolts under mixed loads can lead to nonlinear decreases in pre-loading. This affects the safety performance of the structure and may lead to catastrophic consequences. Existing techniques cannot be used to monitor the bolt performance status in time. This has caused significant problems with the safety and reliability of equipment. In order to study the relaxation law of bolt pre-loading, this paper carries out an experimental analysis for 8.8-grade hexagonal bolts and calibrates the torque coefficient. We also studied different loading waveforms, nickel steel plate surface roughnesses, tangential displacement frequencies, four different strengths and bolt head contact areas of the bolt, the initial pre-loading, and the effects of tangential cyclic displacement on pre-loading relaxation. This was done in order to accurately predict the degree of bolt pre-loading loosening under external loads. The laws are described using the allometric model function and the nine-stage polynomial function. The least squares method is used to identify the parameters in the function. The results show that bolts with a smooth surface of the connected structure nickel steel flat plate, high-frequency working conditions, half-sine wave, and a high-strength have better anti-loosening properties. Taking 5–10 cycles of cyclic loading as a boundary, the pre-loading relaxation is divided into two stages. The first stage is a stage of rapid decrease in bolt pre-loading, and the second stage is the slow decrease process. The performance prediction study shows that the allometric model function is the worst fitted, at 71.7% for the small displacement condition. Other than that, the allometric model function and the nine-stage polynomial function can predict more than 85.5% and 90.4%, which require the use of least squares to identify two and ten unknown parameters, respectively. The complexity of the two is different, but both can by better indicators than the pre-loading relaxation law under specific conditions. It helps to improve the monitoring of bolt loosening and the system use cycle, and it can provide theoretical support for complex equipment working for a long time.
Full article
(This article belongs to the Special Issue Machine Health Monitoring and Fault Diagnosis Techniques (Volume II))
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Open AccessArticle
Human-in-the-Loop Optimization of Knee Exoskeleton Assistance for Minimizing User’s Metabolic and Muscular Effort
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Sara Monteiro, Joana Figueiredo, Pedro Fonseca, J. Paulo Vilas-Boas and Cristina P. Santos
Sensors 2024, 24(11), 3305; https://doi.org/10.3390/s24113305 - 22 May 2024
Abstract
Lower limb exoskeletons have the potential to mitigate work-related musculoskeletal disorders; however, they often lack user-oriented control strategies. Human-in-the-loop (HITL) controls adapt an exoskeleton’s assistance in real time, to optimize the user–exoskeleton interaction. This study presents a HITL control for a knee exoskeleton
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Lower limb exoskeletons have the potential to mitigate work-related musculoskeletal disorders; however, they often lack user-oriented control strategies. Human-in-the-loop (HITL) controls adapt an exoskeleton’s assistance in real time, to optimize the user–exoskeleton interaction. This study presents a HITL control for a knee exoskeleton using a CMA-ES algorithm to minimize the users’ physical effort, a parameter innovatively evaluated using the interaction torque with the exoskeleton (a muscular effort indicator) and metabolic cost. This work innovates by estimating the user’s metabolic cost within the HITL control through a machine-learning model. The regression model estimated the metabolic cost, in real time, with a root mean squared error of 0.66 W/kg and mean absolute percentage error of 26% (n = 5), making faster (10 s) and less noisy estimations than a respirometer (K5, Cosmed). The HITL reduced the user’s metabolic cost by 7.3% and 5.9% compared to the zero-torque and no-device conditions, respectively, and reduced the interaction torque by 32.3% compared to a zero-torque control (n = 1). The developed HITL control surpassed a non-exoskeleton and zero-torque condition regarding the user’s physical effort, even for a task such as slow walking. Furthermore, the user-specific control had a lower metabolic cost than the non-user-specific assistance. This proof-of-concept demonstrated the potential of HITL controls in assisted walking.
Full article
(This article belongs to the Special Issue Applications of Smart Sensing Textiles for Assessment and Assistance of Motion)
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Open AccessArticle
Improving Autonomous Vehicle Perception through Evaluating LiDAR Capabilities and Handheld Retroreflectivity Assessments
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Ziyad N. Aldoski and Csaba Koren
Sensors 2024, 24(11), 3304; https://doi.org/10.3390/s24113304 - 22 May 2024
Abstract
Road safety is a serious concern worldwide, and traffic signs play a critical role in confirming road safety, particularly in the context of AVs. Therefore, there is a need for ongoing advancements in traffic sign evaluation methodologies. This paper comprehensively analyzes the relationship
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Road safety is a serious concern worldwide, and traffic signs play a critical role in confirming road safety, particularly in the context of AVs. Therefore, there is a need for ongoing advancements in traffic sign evaluation methodologies. This paper comprehensively analyzes the relationship between traffic sign retroreflectivity and LiDAR intensity to enhance visibility and communication on road networks. Using Python 3.10 programming and statistical techniques, we thoroughly analyzed handheld retroreflectivity coefficients alongside LiDAR intensity data from two LiDAR configurations: 2LRLiDAR and 1CLiDAR systems. The study focused specifically on RA1 and RA2 traffic sign classes, exploring correlations between retroreflectivity and intensity and identifying factors that may impact their performance. Our findings reveal variations in retroreflectivity compliance rates among different sign categories and color compositions, emphasizing the necessity for targeted interventions in sign design and production processes. Additionally, we observed distinct patterns in LiDAR intensity distributions, indicating the potential of LiDAR technology for assessing sign visibility. However, the limited correlations between retroreflectivity and LiDAR intensity underscore the need for further investigation and standardization efforts. This study provides valuable insights into optimizing traffic sign effectiveness, ultimately contributing to improved road safety conditions.
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(This article belongs to the Section Radar Sensors)
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Open AccessArticle
Crossing-Point Estimation in Human–Robot Navigation—Statistical Linearization versus Sigma-Point Transformation
by
Rainer Palm and Achim J. Lilienthal
Sensors 2024, 24(11), 3303; https://doi.org/10.3390/s24113303 - 22 May 2024
Abstract
Interactions between mobile robots and human operators in common areas require a high level of safety, especially in terms of trajectory planning, obstacle avoidance and mutual cooperation. In this connection, the crossings of planned trajectories and their uncertainty based on model fluctuations, system
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Interactions between mobile robots and human operators in common areas require a high level of safety, especially in terms of trajectory planning, obstacle avoidance and mutual cooperation. In this connection, the crossings of planned trajectories and their uncertainty based on model fluctuations, system noise and sensor noise play an outstanding role. This paper discusses the calculation of the expected areas of interactions during human–robot navigation with respect to fuzzy and noisy information. The expected crossing points of the possible trajectories are nonlinearly associated with the positions and orientations of the robots and humans. The nonlinear transformation of a noisy system input, such as the directions of the motion of humans and robots, to a system output, the expected area of intersection of their trajectories, is performed by two methods: statistical linearization and the sigma-point transformation. For both approaches, fuzzy approximations are presented and the inverse problem is discussed where the input distribution parameters are computed from the given output distribution parameters.
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(This article belongs to the Special Issue Mobile Robots: Navigation, Control and Sensing)
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Open AccessArticle
IR.WoT: An Architecture and Vision for a Unified Web of Things Search Engine
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Cristyan Manta-Caro and Juan M. Fernández-Luna
Sensors 2024, 24(11), 3302; https://doi.org/10.3390/s24113302 - 22 May 2024
Abstract
The revolution of the Internet of Things (IoT) and the Web of Things (WoT) has brought new opportunities and challenges for the information retrieval (IR) field. The exponential number of interconnected physical objects and real-time data acquisition requires new approaches and architectures for
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The revolution of the Internet of Things (IoT) and the Web of Things (WoT) has brought new opportunities and challenges for the information retrieval (IR) field. The exponential number of interconnected physical objects and real-time data acquisition requires new approaches and architectures for IR systems. Research and prototypes can be crucial in designing and developing new systems and refining architectures for IR in the WoT. This paper proposes a unified and holistic approach for IR in the WoT, called IR.WoT. The proposed system contemplates the critical indexing, scoring, and presentation stages applied to some smart cities’ use cases and scenarios. Overall, this paper describes the research, architecture, and vision for advancing the field of IR in the WoT and addresses some of the remaining challenges and opportunities in this exciting area. The article also describes the design considerations, cloud implementation, and experimentation based on a simulated collection of synthetic XML documents with technical efficiency measures. The experimentation results show promising outcomes, whereas further studies are required to improve IR.WoT effectiveness, considering the WoT dynamic characteristics and, more importantly, the heterogeneity and divergence of WoT modeling proposals in the IR domain.
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(This article belongs to the Special Issue Sensor-Enabled IoT, Edge Computing and Artificial Intelligence: Emerging Intelligent Applications)
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Open AccessArticle
Effect of Skin Pigmentation and Finger Choice on Accuracy of Oxygen Saturation Measurement in an IoT-Based Pulse Oximeter
by
Shyqyri Haxha, Chike Nwibor, Mian Ali, Mohamed Sakel, Karen Saunders, Vladimir Dyo and Shakira Nabakooza
Sensors 2024, 24(11), 3301; https://doi.org/10.3390/s24113301 - 22 May 2024
Abstract
Pulse oximeters are widely used in hospitals and homes for measurement of blood oxygen saturation level (SpO2) and heart rate (HR). Concern has been raised regarding a possible bias in obtaining pulse oximeter measurements from different fingertips and the potential effect
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Pulse oximeters are widely used in hospitals and homes for measurement of blood oxygen saturation level (SpO2) and heart rate (HR). Concern has been raised regarding a possible bias in obtaining pulse oximeter measurements from different fingertips and the potential effect of skin pigmentation (white, brown, and dark). In this study, we obtained 600 SpO2 measurements from 20 volunteers using three UK NHS-approved commercial pulse oximeters alongside our custom-developed sensor, and used the Munsell colour system (5YR and 7.5YR cards) to classify the participants’ skin pigmentation into three distinct categories (white, brown, and dark). The statistical analysis using ANOVA post hoc tests (Bonferroni correction), a Bland–Altman plot, and a correlation test were then carried out to determine if there was clinical significance in measuring the SpO2 from different fingertips and to highlight if skin pigmentation affects the accuracy of SpO2 measurement. The results indicate that although the three commercial pulse oximeters had different means and standard deviations, these differences had no clinical significance.
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(This article belongs to the Special Issue The Sensing Technologies and Computational Methods for Biomedical Engineering)
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Open AccessArticle
Assessment of Temporal Somatosensory Discrimination in Females with Fibromyalgia: Reliability and Discriminative Ability of a New Assessment Tool
by
Christophe Demoulin, Léonore Jodogne, Charline David, Jean-François Kaux and Marc Vanderthommen
Sensors 2024, 24(11), 3300; https://doi.org/10.3390/s24113300 - 22 May 2024
Abstract
We assessed the test–retest reliability and discriminative ability of a somatosensory temporal discrimination (SSTD) assessment tool for fibromyalgia syndrome (FMS) and determined if pain-related variables were associated with SSTD performance. Twenty-five women with FMS and twenty-five asymptomatic women were assessed during two sessions
[...] Read more.
We assessed the test–retest reliability and discriminative ability of a somatosensory temporal discrimination (SSTD) assessment tool for fibromyalgia syndrome (FMS) and determined if pain-related variables were associated with SSTD performance. Twenty-five women with FMS and twenty-five asymptomatic women were assessed during two sessions 7 to 10 days apart. The proportion of correct responses (range 0–100) was calculated. Sociodemographic information was collected for both groups. The participants with FMS also completed the widespread pain index and the Brief Pain Inventory. Test–retest reliability was verified by calculating intraclass correlation coefficients. Discriminative ability was verified by a between-group comparison of scores using a t-test. Associations between SSTD score and pain variables were tested using Pearson or Spearman correlation coefficients. The test–retest reliability of the SSTD score was excellent (ICC > 0.9, CI: 0.79–0.96) for the asymptomatic group and good for the FMS group (ICC: 0.81, 95% CI: 0.62–0.91). The median (Q1–Q3) test session SSTD score differed significantly between the FMS 84.1 (71–88) and the asymptomatic 91.6 (83.4–96.1) groups (p < 0.001). Only pain duration was associated with the SSTD score. In conclusion, the new SSTD test seems reliable for people with FMS and is discriminative. Further studies should examine its sensitivity to change and correlations with other SSTD tests.
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(This article belongs to the Special Issue Biomedical Sensors for Diagnosis and Rehabilitation-2nd Edition)
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