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Sensors, Volume 21, Issue 3 (February-1 2021) – 347 articles

Cover Story (view full-size image): In the last decade, Wake-up Radio technology has gained more and more importance for IoT applications. This technology is based on an ultra-low-power, always-listening radio receiver that prevents the main IoT transceiver to continuously listen to the channel, lowering its power consumption. On the other hand, LoRa is one of the emerging long-range standards that facilitate the environmental monitoring of wide areas, but generally suffer from high latency in downlink. This paper proposes an original combination of Lora technology and Wake-up radio to improve the performance (latency and energy) of the LoRaWAN downlink transmission. It is also shown that this combination is particularly suitable to nodes that have the capability to harvest surrounding energy. This research is mainly funded by French ANR and takes place in the collaborative project “Wake-Up”. View this paper
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Open AccessArticle
Characterisation of Textile Embedded Electrodes for Use in a Neonatal Smart Mattress Electrocardiography System
Sensors 2021, 21(3), 999; https://doi.org/10.3390/s21030999 - 02 Feb 2021
Viewed by 471
Abstract
Heart rate monitoring is the predominant quantitative health indicator of a newborn in the delivery room. A rapid and accurate heart rate measurement is vital during the first minutes after birth. Clinical recommendations suggest that electrocardiogram (ECG) monitoring should be widely adopted in [...] Read more.
Heart rate monitoring is the predominant quantitative health indicator of a newborn in the delivery room. A rapid and accurate heart rate measurement is vital during the first minutes after birth. Clinical recommendations suggest that electrocardiogram (ECG) monitoring should be widely adopted in the neonatal intensive care unit to reduce infant mortality and improve long term health outcomes in births that require intervention. Novel non-contact electrocardiogram sensors can reduce the time from birth to heart rate reading as well as providing unobtrusive and continuous monitoring during intervention. In this work we report the design and development of a solution to provide high resolution, real time electrocardiogram data to the clinicians within the delivery room using non-contact electric potential sensors embedded in a neonatal intensive care unit mattress. A real-time high-resolution electrocardiogram acquisition solution based on a low power embedded system was developed and textile embedded electrodes were fabricated and characterised. Proof of concept tests were carried out on simulated and human cardiac signals, producing electrocardiograms suitable for the calculation of heart rate having an accuracy within ±1 beat per minute using a test ECG signal, ECG recordings from a human volunteer with a correlation coefficient of ~ 87% proved accurate beat to beat morphology reproduction of the waveform without morphological alterations and a time from application to heart rate display below 6 s. This provides evidence that flexible non-contact textile-based electrodes can be embedded in wearable devices for assisting births through heart rate monitoring and serves as a proof of concept for a complete neonate electrocardiogram monitoring system. Full article
(This article belongs to the Special Issue ECG Sensors)
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Open AccessArticle
Signal Diversity for Laser-Doppler Vibrometers with Raw-Signal Combination
Sensors 2021, 21(3), 998; https://doi.org/10.3390/s21030998 - 02 Feb 2021
Viewed by 386
Abstract
The intensity of the reflected measuring beam is greatly reduced for laser-Doppler vibrometer (LDV) measurements on rough surfaces since a considerable part of the light is scattered and cannot reach the photodetector (laser speckle effect). The low intensity of the reflected laser beam [...] Read more.
The intensity of the reflected measuring beam is greatly reduced for laser-Doppler vibrometer (LDV) measurements on rough surfaces since a considerable part of the light is scattered and cannot reach the photodetector (laser speckle effect). The low intensity of the reflected laser beam leads to a so-called signal dropout, which manifests as noise peaks in the demodulated velocity signal. In such cases, no light reaches the detector at a specific time and, therefore, no signal can be detected. Consequently, the overall quality of the signal decreases significantly. In the literature, first attempts and a practical implementation to reduce this effect by signal diversity can be found. In this article, a practical implementation with four measuring heads of a Multipoint Vibrometer (MPV) and an evaluation and optimization of an algorithm from the literature is presented. The limitations of the algorithm, which combines velocity signals, are shown by evaluating our measurements. We present a modified algorithm, which generates a combined detector signal from the raw signals of the individual channels, reducing the mean noise level in our measurement by more than 10 dB. By comparing the results of our new algorithm with the algorithms of the state-of-the-art, we can show an improvement of the noise reduction with our approach. Full article
(This article belongs to the Special Issue Laser Doppler Sensors)
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Open AccessArticle
A FOD Detection Approach on Millimeter-Wave Radar Sensors Based on Optimal VMD and SVDD
Sensors 2021, 21(3), 997; https://doi.org/10.3390/s21030997 - 02 Feb 2021
Viewed by 359
Abstract
Foreign object debris (FOD) on airport runways can cause serious accidents and huge economic losses. FOD detection systems based on millimeter-wave (MMW) radar sensors have the advantages of higher range resolution and lower power consumption. However, it is difficult for traditional FOD detection [...] Read more.
Foreign object debris (FOD) on airport runways can cause serious accidents and huge economic losses. FOD detection systems based on millimeter-wave (MMW) radar sensors have the advantages of higher range resolution and lower power consumption. However, it is difficult for traditional FOD detection methods to detect and distinguish weak signals of targets from strong ground clutter. To solve this problem, this paper proposes a new FOD detection approach based on optimized variational mode decomposition (VMD) and support vector data description (SVDD). This approach utilizes SVDD as a classifier to distinguish FOD signals from clutter signals. More importantly, the VMD optimized by whale optimization algorithm (WOA) is used to improve the accuracy and stability of the classifier. The results from both the simulation and field case show the excellent FOD detection performance of the proposed VMD-SVDD method. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle
Comparison of Femtosecond Laser-Assisted and Ultrasound-Assisted Cataract Surgery with Focus on Endothelial Analysis
Sensors 2021, 21(3), 996; https://doi.org/10.3390/s21030996 - 02 Feb 2021
Viewed by 358
Abstract
Femtosecond laser-assisted cataract surgery has the potential to make critical steps of cataract surgery easier and safer, and reduce endothelial cell loss, thus, improving postoperative outcomes. This study compared FLACS with the conventional method in terms of endothelial cells behavior, clinical outcomes, and [...] Read more.
Femtosecond laser-assisted cataract surgery has the potential to make critical steps of cataract surgery easier and safer, and reduce endothelial cell loss, thus, improving postoperative outcomes. This study compared FLACS with the conventional method in terms of endothelial cells behavior, clinical outcomes, and capsulotomy precision. Methods: In a single-center, randomized controlled study, 130 patients with cataracta senilis received FLACS or conventional cataract surgery. Results: A significant endothelial cell loss was observed postoperatively, compared to the preoperative values in both groups. The endothelial cell counts was significantly better in the FLACS group in cataract grade 2 (p = 0.048) patients, compared to conventionally at 4 weeks. The effective phaco time was notably shorter in grade 2 of the FLACS group (p = 0.007) compared to the conventional. However, no statistically significant differences were found for the whole sample, including all cataract grades, due to the overall cataract density in the FLACS group being significantly higher (2.60 ± 0.58, p < 0.001) as compared to conventional methods (2.23 ± 0.42). Conclusions: Low energy FLACS provides a better result compared to endothelial cell loss, size, and shape variations, as well as in effective phaco time within certain cataract grade subgroups. A complete comparison between two groups was not possible because of the higher cataract grade in the FLACS. FLACS displayed a positive effect on endothelial cell preservation and was proven to be much more precise. Full article
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Open AccessReview
Carbon Nanotube Field-Effect Transistor-Based Chemical and Biological Sensors
Sensors 2021, 21(3), 995; https://doi.org/10.3390/s21030995 - 02 Feb 2021
Viewed by 410
Abstract
Chemical and biological sensors have attracted great interest due to their importance in applications of healthcare, food quality monitoring, environmental monitoring, etc. Carbon nanotube (CNT)-based field-effect transistors (FETs) are novel sensing device configurations and are very promising for their potential to drive many [...] Read more.
Chemical and biological sensors have attracted great interest due to their importance in applications of healthcare, food quality monitoring, environmental monitoring, etc. Carbon nanotube (CNT)-based field-effect transistors (FETs) are novel sensing device configurations and are very promising for their potential to drive many technological advancements in this field due to the extraordinary electrical properties of CNTs. This review focuses on the implementation of CNT-based FETs (CNTFETs) in chemical and biological sensors. It begins with the introduction of properties, and surface functionalization of CNTs for sensing. Then, configurations and sensing mechanisms for CNT FETs are introduced. Next, recent progresses of CNTFET-based chemical sensors, and biological sensors are summarized. Finally, we end the review with an overview about the current application status and the remaining challenges for the CNTFET-based chemical and biological sensors. Full article
(This article belongs to the Special Issue State-of-the-Art Biosensors Technology in China 2020–2021)
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Open AccessArticle
No Reference, Opinion Unaware Image Quality Assessment by Anomaly Detection
Sensors 2021, 21(3), 994; https://doi.org/10.3390/s21030994 - 02 Feb 2021
Viewed by 495
Abstract
We propose an anomaly detection based image quality assessment method which exploits the correlations between feature maps from a pre-trained Convolutional Neural Network (CNN). The proposed method encodes the intra-layer correlation through the Gram matrix and then estimates the quality score combining the [...] Read more.
We propose an anomaly detection based image quality assessment method which exploits the correlations between feature maps from a pre-trained Convolutional Neural Network (CNN). The proposed method encodes the intra-layer correlation through the Gram matrix and then estimates the quality score combining the average of the correlation and the output from an anomaly detection method. The latter evaluates the degree of abnormality of an image by computing a correlation similarity with respect to a dictionary of pristine images. The effectiveness of the method is tested on different benchmarking datasets (LIVE-itW, KONIQ, and SPAQ). Full article
(This article belongs to the Section Sensing and Imaging)
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Open AccessArticle
Structural Health Monitoring Using Ultrasonic Guided-Waves and the Degree of Health Index
Sensors 2021, 21(3), 993; https://doi.org/10.3390/s21030993 - 02 Feb 2021
Viewed by 468
Abstract
This paper proposes a new damage index named degree of health (DoH) to efficiently tackle structural damage monitoring in real-time. As a key contribution, the proposed index relies on a pattern matching methodology that measures the time-of-flight mismatch of sequential ultrasonic guided-wave measurements [...] Read more.
This paper proposes a new damage index named degree of health (DoH) to efficiently tackle structural damage monitoring in real-time. As a key contribution, the proposed index relies on a pattern matching methodology that measures the time-of-flight mismatch of sequential ultrasonic guided-wave measurements using fuzzy logic fundamentals. The ultrasonic signals are generated using the transmission beamforming technique with a phased-array of piezoelectric transducers. The acquisition is carried out by two phased-arrays to compare the influence of pulse-echo and pitch-catch modes in the damage assessment. The proposed monitoring approach is illustrated in a fatigue test of an aluminum sheet with an initial notch. As an additional novelty, the proposed pattern matching methodology uses the data stemming from the transmission beamforming technique for structural health monitoring. The results demonstrate the efficiency and robustness of the proposed framework in providing a qualitative and quantitative assessment for fatigue crack damage. Full article
(This article belongs to the Special Issue Structural Health Monitoring with Ultrasonic Guided-Waves Sensors)
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Open AccessArticle
The Application of Electromagnetic Sensors for Determination of Cherenkov Cone Inside and in the Vicinity of the Detector Volume in Any Environment Known
Sensors 2021, 21(3), 992; https://doi.org/10.3390/s21030992 - 02 Feb 2021
Viewed by 352
Abstract
The neutrinos of cosmic radiation, due to interaction with any known medium in which the Cherenkov detector is used, produce energy radiation phenomena in the form of a Cherenkov cone, in very large frequency spectrum. These neutrinos carry with them the information about [...] Read more.
The neutrinos of cosmic radiation, due to interaction with any known medium in which the Cherenkov detector is used, produce energy radiation phenomena in the form of a Cherenkov cone, in very large frequency spectrum. These neutrinos carry with them the information about the phenomena that produced them and by detecting the electromagnetic energies generated by the Cherenkov cone, we can find information about the phenomena that formed in the universe, at a much greater distance, than possibility of actually detection with current technologies. At present, a very high number of sensors for detection electromagnetic energy is required. Thus, some sensors may detect very low energy levels, which can lead to the erroneous determination of the Cherenkov cone, thus leading to information errors. As a novelty, we propose, to use these sensors for determination of the dielectrically permittivity of any known medium in which the Cherenkov detector is used, by preliminary measurements, the subsequent simulation of the data and the reconstruction of the Cherenkov cone, leading to a significant reduction of problems and minimizing the number of sensors, implicitly the cost reductions. At the same time, we offer the possibility of reconstructing the Cherenkov cone outside the detector volume. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Romania 2020)
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Open AccessArticle
Social Collective Attack Model and Procedures for Large-Scale Cyber-Physical Systems
Sensors 2021, 21(3), 991; https://doi.org/10.3390/s21030991 - 02 Feb 2021
Viewed by 297
Abstract
A large-scale Cyber-Physical System (CPS) such as a smart grid usually provides service to a vast number of users as a public utility. Security is one of the most vital aspects in such critical infrastructures. The existing CPS security usually considers the attack [...] Read more.
A large-scale Cyber-Physical System (CPS) such as a smart grid usually provides service to a vast number of users as a public utility. Security is one of the most vital aspects in such critical infrastructures. The existing CPS security usually considers the attack from the information domain to the physical domain, such as injecting false data to damage sensing. Social Collective Attack on CPS (SCAC) is proposed as a new kind of attack that intrudes into the social domain and manipulates the collective behavior of social users to disrupt the physical subsystem. To provide a systematic description framework for such threats, we extend MITRE ATT&CK, the most used cyber adversary behavior modeling framework, to cover social, cyber, and physical domains. We discuss how the disinformation may be constructed and eventually leads to physical system malfunction through the social-cyber-physical interfaces, and we analyze how the adversaries launch disinformation attacks to better manipulate collective behavior. Finally, simulation analysis of SCAC in a smart grid is provided to demonstrate the possibility of such an attack. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle
On the Use of Movement-Based Interaction with Smart Textiles for Emotion Regulation
Sensors 2021, 21(3), 990; https://doi.org/10.3390/s21030990 - 02 Feb 2021
Viewed by 397
Abstract
Research from psychology has suggested that body movement may directly activate emotional experiences. Movement-based emotion regulation is the most readily available but often underutilized strategy for emotion regulation. This research aims to investigate the emotional effects of movement-based interaction and its sensory feedback [...] Read more.
Research from psychology has suggested that body movement may directly activate emotional experiences. Movement-based emotion regulation is the most readily available but often underutilized strategy for emotion regulation. This research aims to investigate the emotional effects of movement-based interaction and its sensory feedback mechanisms. To this end, we developed a smart clothing prototype, E-motionWear, which reacts to four movements (elbow flexion/extension, shoulder flexion/extension, open and closed arms, neck flexion/extension), fabric-based detection sensors, and three-movement feedback mechanisms (audio, visual and vibrotactile). An experiment was conducted using a combined qualitative and quantitative approach to collect participants’ objective and subjective emotional feelings. Results indicate that there was no interaction effect between movement and feedback mechanism on the final emotional results. Participants preferred vibrotactile and audio feedback rather than visual feedback when performing these four kinds of upper body movements. Shoulder flexion/extension and open-closed arm movements were more effective for improving positive emotion than elbow flexion/extension movements. Participants thought that the E-motionWear prototype were comfortable to wear and brought them new emotional experiences. From these results, a set of guidelines were derived that can help frame the design and use of smart clothing to support users’ emotional regulation. Full article
(This article belongs to the Special Issue Wearable Sensors for Healthcare)
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Open AccessArticle
3D Multiple-Antenna Channel Modeling and Propagation Characteristics Analysis for Mobile Internet of Things
Sensors 2021, 21(3), 989; https://doi.org/10.3390/s21030989 - 02 Feb 2021
Viewed by 305
Abstract
The demand for optimization design and performance evaluation of wireless communication links in a mobile Internet of Things (IoT) motivates the exploitation of realistic and tractable channel models. In this paper, we develop a novel three-dimensional (3D) multiple-antenna channel model to adequately characterize [...] Read more.
The demand for optimization design and performance evaluation of wireless communication links in a mobile Internet of Things (IoT) motivates the exploitation of realistic and tractable channel models. In this paper, we develop a novel three-dimensional (3D) multiple-antenna channel model to adequately characterize the scattering environment for mobile IoT scenarios. Specifically, taking into consideration both accuracy and mathematical tractability, a 3D double-spheres model and ellipsoid model are introduced to describe the distribution region of the local scatterers and remote scatterers, respectively. Based on the explicit geometry relationships between transmitter, receiver, and scatterers, we derive the complex channel gains by adopting the radio-wave propagation model. Subsequently, the correlation-based approach for theoretical analysis is performed, and the detailed impacts with respect to the antenna deployment, scatterer distribution, and scatterer density on the vital statistical properties are investigated. Numerical simulation results have shown that the statistical channel characteristics in the developed simulation model nicely match those of the corresponding theoretical results, which demonstrates the utility of our model. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle
Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging
Sensors 2021, 21(3), 988; https://doi.org/10.3390/s21030988 - 02 Feb 2021
Viewed by 305
Abstract
In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. [...] Read more.
In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. Household activity recognition includes the recognition of electrical appliances and their heat radiation with the help of thermal images. A FLIR ONE PRO camera is used to capture RGB-thermal image pairs for a scene. Duration and pattern of activities are also determined using an iterative algorithm, to explore kitchen safety situations. For more accurate monitoring of hazardous events such as stove gas leakage, a 3D reconstruction approach is proposed to determine the temperature of all points in the 3D space of a scene. The 3D thermal model is obtained using the stereo RGB and thermal images for a particular scene. Accurate results are observed for activity detection, and a significant improvement in the temperature estimation is recorded in the 3D thermal model compared to the 2D thermal image. Results from this research can find applications in home automation, heat automation in smart homes, and energy management in residential spaces. Full article
(This article belongs to the Section Internet of Things)
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Open AccessArticle
Influence of Noise-Limited Censored Path Loss on Model Fitting and Path Loss-Based Positioning
Sensors 2021, 21(3), 987; https://doi.org/10.3390/s21030987 - 02 Feb 2021
Viewed by 317
Abstract
Positioning is considered one of the key features in various novel industry verticals in future radio systems. Since path loss (PL) or received signal strength-based measurements are widely available in the majority of wireless standards, PL-based positioning has an important role among positioning [...] Read more.
Positioning is considered one of the key features in various novel industry verticals in future radio systems. Since path loss (PL) or received signal strength-based measurements are widely available in the majority of wireless standards, PL-based positioning has an important role among positioning technologies. Conventionally, PL-based positioning has two phases—fitting a PL model to training data and positioning based on the link distance estimates. However, in both phases, the maximum measurable PL is limited by measurement noise. Such immeasurable samples are called censored PL data and such noisy data are commonly neglected in both the model fitting and in the positioning phase. In the case of censored PL, the loss is known to be above a known threshold level and that information can be used in model fitting and in the positioning phase. In this paper, we examine and propose how to use censored PL data in PL model-based positioning. Additionally, we demonstrate with several simulations the potential of the proposed approach for considerable improvements in positioning accuracy (23–57%) and improved robustness against PL model fitting errors. Full article
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Open AccessArticle
Use of Multiple Bacteriophage-Based Structural Color Sensors to Improve Accuracy for Discrimination of Geographical Origins of Agricultural Products
Sensors 2021, 21(3), 986; https://doi.org/10.3390/s21030986 - 02 Feb 2021
Viewed by 333
Abstract
A single M13 bacteriophage color sensor was previously utilized for discriminating the geographical origins of agricultural products (garlic, onion, and perilla). The resulting discrimination accuracy was acceptable, ranging from 88.6% to 94.0%. To improve the accuracy further, the use of three separate M13 [...] Read more.
A single M13 bacteriophage color sensor was previously utilized for discriminating the geographical origins of agricultural products (garlic, onion, and perilla). The resulting discrimination accuracy was acceptable, ranging from 88.6% to 94.0%. To improve the accuracy further, the use of three separate M13 bacteriophage color sensors containing different amino acid residues providing unique individual color changes (Wild sensor: glutamic acid (E)-glycine (G)-aspartic acid (D), WHW sensor: tryptophan (W)-histidine (H)-tryptophan (W), 4E sensor: four repeating glutamic acids (E)) was proposed. This study was driven by the possibility of enhancing sample discrimination by combining mutually characteristic and complimentary RGB signals obtained from each color sensor, which resulted from dissimilar interactions of sample odors with the employed color sensors. When each color sensor was used individually, the discrimination accuracy based on support vector machine (SVM) ranged from 91.8–94.0%, 88.6–90.3%, and 89.8–92.1% for garlic, onion, and perilla samples, respectively. Accuracy improved to 98.0%, 97.5%, and 97.1%, respectively, by integrating all of the RGB signals acquired from the three color sensors. Therefore, the proposed strategy was effective for improving sample discriminability. To further examine the dissimilar responses of each color sensor to odor molecules, typical odor components in the samples (allyl disulfide, allyl methyl disulfide, and perillaldehyde) were measured using each color sensor, and differences in RGB signals were analyzed. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessCommunication
Assessment of the Shank-to-Vertical Angle While Changing Heel Heights Using a Single Inertial Measurement Unit in Individuals with Incomplete Spinal Cord Injury Wearing an Ankle-Foot-Orthosis
Sensors 2021, 21(3), 985; https://doi.org/10.3390/s21030985 - 02 Feb 2021
Viewed by 478
Abstract
Previous research showed that an Inertial Measurement Unit (IMU) on the anterior side of the shank can accurately measure the Shank-to-Vertical Angle (SVA), which is a clinically-used parameter to guide tuning of ankle-foot orthoses (AFOs). However, in this context it is specifically important [...] Read more.
Previous research showed that an Inertial Measurement Unit (IMU) on the anterior side of the shank can accurately measure the Shank-to-Vertical Angle (SVA), which is a clinically-used parameter to guide tuning of ankle-foot orthoses (AFOs). However, in this context it is specifically important that differences in the SVA are detected during the tuning process, i.e., when adjusting heel height. This study investigated the validity of the SVA as measured by an IMU and its responsiveness to changes in AFO-footwear combination (AFO-FC) heel height in persons with incomplete spinal cord injury (iSCI). Additionally, the effect of heel height on knee flexion-extension angle and internal moment was evaluated. Twelve persons with an iSCI walked with their own AFO-FC in three different conditions: (1) without a heel wedge (refHH), (2) with 5 mm heel wedge (lowHH) and (3) with 10 mm heel wedge (highHH). Walking was recorded by a single IMU on the anterior side of the shank and a 3D gait analysis (3DGA) simultaneously. To estimate validity, a paired t-test and intraclass correlation coefficient (ICC) between the SVAIMU and SVA3DGA were calculated for the refHH. A repeated measures ANOVA was performed to evaluate the differences between the heel heights. A good validity with a mean difference smaller than 1 and an ICC above 0.9 was found for the SVA during midstance phase and at midstance. Significant differences between the heel heights were found for changes in SVAIMU (p = 0.036) and knee moment (p = 0.020) during the midstance phase and in SVAIMU (p = 0.042) and SVA3DGA (p = 0.006) at midstance. Post-hoc analysis revealed a significant difference between the ref and high heel height condition for the SVAIMU (p = 0.005) and knee moment (p = 0.006) during the midstance phase and for the SVAIMU (p = 0.010) and SVA3DGA (p = 0.006) at the instant of midstance. The SVA measured with an IMU is valid and responsive to changing heel heights and equivalent to the gold standard 3DGA. The knee joint angle and knee joint moment showed concomitant changes compared to SVA as a result of changing heel height. Full article
(This article belongs to the Special Issue Wearable Sensors for Movement Analysis)
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Open AccessArticle
The Simulated Characterization and Suitability of Semiconductor Detectors for Strontium 90 Assay in Groundwater
Sensors 2021, 21(3), 984; https://doi.org/10.3390/s21030984 - 02 Feb 2021
Viewed by 256
Abstract
This paper examines the potential deployment of a 10 mm × 10 mm × 1 mm cadmium telluride detector for strontium-90 measurement in groundwater boreholes at nuclear decommissioning sites. Geant4 simulation was used to model the deployment of the detector in a borehole [...] Read more.
This paper examines the potential deployment of a 10 mm × 10 mm × 1 mm cadmium telluride detector for strontium-90 measurement in groundwater boreholes at nuclear decommissioning sites. Geant4 simulation was used to model the deployment of the detector in a borehole monitoring contaminated groundwater. It was found that the detector was sensitive to strontium-90, yttrium-90, caesium-137, and potassium-40 decay, some of the significant beta emitters found at Sellafield. However, the device showed no sensitivity to carbon-14 decay, due to the inability of the weak beta emission to penetrate both the groundwater and the detector shielding. The limit of detection for such a sensor when looking at solely strontium-90 decay was calculated as 323 BqL1 after a 1-h measurement and 66 BqL1 after a 24-h measurement. A gallium-arsenide (GaAs) sensor with twice the surface area, but 0.3% of the thickness was modelled for comparison. Using this sensor, sensitivity was increased, such that the limit of detection for strontium-90 was 91 BqL1 after 1 h and 18 BqL1 after 24 h. However, this sensor sacrifices the potential to identify the present radionuclides by their end-point energy. Additionally, the feasibility of using flexible detectors based on solar cell designs to maximise the surface area of detectors has been modelled. Full article
(This article belongs to the Section Intelligent Sensors)
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Open AccessArticle
Efficient Wind Speed Forecasting for Resource-Constrained Sensor Devices
Sensors 2021, 21(3), 983; https://doi.org/10.3390/s21030983 - 02 Feb 2021
Viewed by 267
Abstract
Wind energy harvesting technology is one of the most popular power sources for wireless sensor networks. However, given its irregular nature, wind energy availability experiences significant variations and, therefore, wind-powered devices need reliable forecasting models to effectively adjust their energy consumption to the [...] Read more.
Wind energy harvesting technology is one of the most popular power sources for wireless sensor networks. However, given its irregular nature, wind energy availability experiences significant variations and, therefore, wind-powered devices need reliable forecasting models to effectively adjust their energy consumption to the dynamics of energy harvesting. On the other hand, resource-constrained devices with limited hardware capacities (such as sensor nodes) must resort to forecasting schemes of low complexity for their predictions in order to avoid squandering their scarce power and computing capabilities. In this paper, we present a new efficient ARIMA-based forecasting model for predicting wind speed at short-term horizons. The performance results obtained using real data sets show that the proposed ARIMA model can be an excellent choice for wind-powered sensor nodes due to its potential for achieving accurate enough predictions with very low computational burden and memory overhead. In addition, it is very simple to setup, since it can dynamically adapt to varying wind conditions and locations without requiring any particular reconfiguration or previous data training phase for each different scenario. Full article
(This article belongs to the Special Issue Green Sensors Networking)
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Open AccessArticle
Fluid–Structure Coupling Effects in a Dual U-Tube Coriolis Mass Flow Meter
Sensors 2021, 21(3), 982; https://doi.org/10.3390/s21030982 - 02 Feb 2021
Viewed by 255
Abstract
Coriolis mass flowmeters are highly customized products involving high-degree fluid-structure coupling dynamics and high-precision manufacture. The typical delay from from order to shipment is at least 4 months. This paper presents some important design considerations through simulation and experiments, so as to provide [...] Read more.
Coriolis mass flowmeters are highly customized products involving high-degree fluid-structure coupling dynamics and high-precision manufacture. The typical delay from from order to shipment is at least 4 months. This paper presents some important design considerations through simulation and experiments, so as to provide manufacturers with a more time-efficient product design and manufacture process. This paper aims at simulating the fluid-structure coupling dynamics of a dual U-tube Coriolis mass flowmeter through the COMSOL simulation package. The simulation results are experimentally validated using a dual U-tube CMF manufactured by Yokogawa Co., Ltd. in a TAF certified flow testing factory provided by FineTek Co., Ltd. Some important design considerations are drawn from simulation and experiment. The zero drift will occur when the dual U-tube structure is unbalanced and therefore the dynamic balance is very important in the manufacturing of dual U-tube CMF. The fluid viscosity can be determined from the driving current of the voice coil actuator or the pressure loss between the inlet and outlet of CMF. Finally, the authors develop a simulation application based on COMSOL’s development platform. Users can quickly evaluate their design through by using this application. The present application can significantly shorten product design and manufacturing time. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
A-WEAR Bracelet for Detection of Hand Tremor and Bradykinesia in Parkinson’s Patients
Sensors 2021, 21(3), 981; https://doi.org/10.3390/s21030981 - 02 Feb 2021
Viewed by 433
Abstract
Parkinson’s disease patients face numerous motor symptoms that eventually make their life different from those of normal healthy controls. Out of these motor symptoms, tremor and bradykinesia, are relatively prevalent in all stages of this disease. The assessment of these symptoms is usually [...] Read more.
Parkinson’s disease patients face numerous motor symptoms that eventually make their life different from those of normal healthy controls. Out of these motor symptoms, tremor and bradykinesia, are relatively prevalent in all stages of this disease. The assessment of these symptoms is usually performed by traditional methods where the accuracy of results is still an open question. This research proposed a solution for an objective assessment of tremor and bradykinesia in subjects with PD (10 older adults aged greater than 60 years with tremor and 10 older adults aged greater than 60 years with bradykinesia) and 20 healthy older adults aged greater than 60 years. Physical movements were recorded by means of an AWEAR bracelet developed using inertial sensors, i.e., 3D accelerometer and gyroscope. Participants performed upper extremities motor activities as adopted by neurologists during the clinical assessment based on Unified Parkinson’s Disease Rating Scale (UPDRS). For discriminating the patients from healthy controls, temporal and spectral features were extracted, out of which non-linear temporal and spectral features show greater difference. Both supervised and unsupervised machine learning classifiers provide good results. Out of 40 individuals, neural net clustering discriminated 34 individuals in correct classes, while the KNN approach discriminated 91.7% accurately. In a clinical environment, the doctor can use the device to comprehend the tremor and bradykinesia of patients quickly and with higher accuracy. Full article
(This article belongs to the Special Issue Applications and Innovations on Sensor-Enabled Wearable Devices)
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Open AccessArticle
Intelligent Control Method of Hoisting Prefabricated Components Based on Internet-of-Things
Sensors 2021, 21(3), 980; https://doi.org/10.3390/s21030980 - 02 Feb 2021
Viewed by 349
Abstract
Prefabricated buildings are widely used because of their green environmental protection and high degree of industrialization. However, in construction process, there are some defects such as small wireless network coverage, high-energy consumption, inaccurate control, and backward blind hoisting methods in the hoisting process [...] Read more.
Prefabricated buildings are widely used because of their green environmental protection and high degree of industrialization. However, in construction process, there are some defects such as small wireless network coverage, high-energy consumption, inaccurate control, and backward blind hoisting methods in the hoisting process of prefabricated components (PC). Internet-of-Things (IoT) technology can be used to collect and transmit data to strengthen the management of construction sites. The purpose of this study was to establish an intelligent control method in the construction and hoisting process of PC by using IoT technology. Long Range Radio (LoRa) technology was used to conduct data terminal acquisition and wireless transmission in the construction site. The Inertial Measurement Unit (IMU), Global Positioning System (GPS), and other multi-sensor fusion was used to collect information during the hoisting process of PC, and multi-sensor information was fused by fusion location algorithm for location control. Finally, the feasibility of this method was verified by a project as a case. The results showed that the IoT technology can strengthen the management ability of PC in the hoisting process, and improve the visualization level of the hoisting process of PC. Analysis of the existing outdated PC hoisting management methods, LoRa, IMU, GPS and other sensors were used for data acquisition and transmission, the PC hoisting multi-level management and intelligent control. Full article
(This article belongs to the Special Issue LoRa Sensor Network)
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Open AccessReview
Recent Advances in Aptamer Sensors
Sensors 2021, 21(3), 979; https://doi.org/10.3390/s21030979 - 02 Feb 2021
Viewed by 447
Abstract
Recently, aptamers have attracted attention in the biosensing field as signal recognition elements because of their high binding affinity toward specific targets such as proteins, cells, small molecules, and even metal ions, antibodies for which are difficult to obtain. Aptamers are single oligonucleotides [...] Read more.
Recently, aptamers have attracted attention in the biosensing field as signal recognition elements because of their high binding affinity toward specific targets such as proteins, cells, small molecules, and even metal ions, antibodies for which are difficult to obtain. Aptamers are single oligonucleotides generated by in vitro selection mechanisms via the systematic evolution of ligand exponential enrichment (SELEX) process. In addition to their high binding affinity, aptamers can be easily functionalized and engineered, providing several signaling modes such as colorimetric, fluorometric, and electrochemical, in what are known as aptasensors. In this review, recent advances in aptasensors as powerful biosensor probes that could be used in different fields, including environmental monitoring, clinical diagnosis, and drug monitoring, are described. Advances in aptamer-based colorimetric, fluorometric, and electrochemical aptasensing with their advantages and disadvantages are summarized and critically discussed. Additionally, future prospects are pointed out to facilitate the development of aptasensor technology for different targets. Full article
(This article belongs to the Special Issue Recent Advances in Apta-Biosensors)
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Open AccessArticle
A 3D Informational Database for Automatic Archiving of Archaeological Pottery Finds
Sensors 2021, 21(3), 978; https://doi.org/10.3390/s21030978 - 02 Feb 2021
Viewed by 286
Abstract
From archaeological excavations, huge quantities of material are recovered, usually in the form of fragments. Their correct interpretation and classification are laborious and time-consuming and requires measurement, analysis and comparison of several items. Basing these activities on quantitative methods that process 3D digital [...] Read more.
From archaeological excavations, huge quantities of material are recovered, usually in the form of fragments. Their correct interpretation and classification are laborious and time-consuming and requires measurement, analysis and comparison of several items. Basing these activities on quantitative methods that process 3D digital data from experimental measurements allows optimizing the entire restoration process, making it faster, more accurate and cheaper. The 3D point clouds, captured by the scanning process, are raw data that must be properly processed to be used in automatic systems for the analysis of archeological finds. This paper focuses on the integration of a shape feature recognizer, able to support the semantic decomposition of the ancient artifact into archaeological features, with a structured database, able to query the large amount of information extracted. Through the automatic measurement of the dimensional attributes of the various features, it is possible to facilitate the comparative analyses between archaeological artifacts and the inferences of the archaeologist and to reduce the routine work. Here, a dedicated database has been proposed, able to store the information extracted from huge quantities of archaeological material using a specific shape feature recognizer. This information is useful for making comparisons but also to improve the archaeological knowledge. The database has been implemented and used for the identification of pottery fragments and the reconstruction of archaeological vessels. Reconstruction, in particular, often requires the solution of complex problems, especially when it involves types of potsherds that cannot be treated with traditional methods. Full article
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Open AccessCommunication
Gradiometer Using Separated Diamond Quantum Magnetometers
Sensors 2021, 21(3), 977; https://doi.org/10.3390/s21030977 - 02 Feb 2021
Viewed by 356
Abstract
The negatively charged nitrogen-vacancy (NV) center in diamonds is known as the spin defect and using its electron spin, magnetometry can be realized even at room temperature with extremely high sensitivity as well as a high dynamic range. However, a magnetically shielded enclosure [...] Read more.
The negatively charged nitrogen-vacancy (NV) center in diamonds is known as the spin defect and using its electron spin, magnetometry can be realized even at room temperature with extremely high sensitivity as well as a high dynamic range. However, a magnetically shielded enclosure is usually required to sense weak magnetic fields because environmental magnetic field noises can disturb high sensitivity measurements. Here, we fabricated a gradiometer with variable sensor length that works at room temperature using a pair of diamond samples containing negatively charged NV centers. Each diamond is attached to an optical fiber to enable free sensor placement. Without any magnetically shielding, our gradiometer realizes a magnetic noise spectrum comparable to that of a three-layer magnetically shielded enclosure, reducing the noises at the low-frequency range below 1 Hz as well as at the frequency of 50 Hz (power line frequency) and its harmonics. These results indicate the potential of highly sensitive magnetic sensing by the gradiometer using the NV center for applications in noisy environments such as outdoor and in vehicles. Full article
(This article belongs to the Special Issue Magnetic Sensing/Functionalized Devices and Applications)
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Open AccessCommunication
Development of an Automated Minimum Foot Clearance Measurement System: Proof of Principle
Sensors 2021, 21(3), 976; https://doi.org/10.3390/s21030976 - 02 Feb 2021
Viewed by 322
Abstract
Over half of older adult falls are caused by tripping. Many of these trips are likely due to obstacles present on walkways that put older adults or other individuals with low foot clearance at risk. Yet, Minimum Foot Clearance (MFC) values have not [...] Read more.
Over half of older adult falls are caused by tripping. Many of these trips are likely due to obstacles present on walkways that put older adults or other individuals with low foot clearance at risk. Yet, Minimum Foot Clearance (MFC) values have not been measured in real-world settings and existing methods make it difficult to do so. In this paper, we present the Minimum Foot Clearance Estimation (MFCE) system that includes a device for collecting calibrated video data from pedestrians on outdoor walkways and a computer vision algorithm for estimating MFC values for these individuals. This system is designed to be positioned at ground level next to a walkway to efficiently collect sagittal plane videos of many pedestrians’ feet, which is then processed offline to obtain MFC estimates. Five-hundred frames of video data collected from 50 different pedestrians was used to train (370 frames) and test (130 frames) a convolutional neural network. Finally, data from 10 pedestrians was analyzed manually by three raters and compared to the results of the network. The footwear detection network had an Intersection over Union of 85% and was able to find the bottom of a segmented shoe with a 3-pixel average error. Root Mean Squared (RMS) errors for the manual and automated methods for estimating MFC values were 2.32 mm, and 3.70 mm, respectively. Future work will compare the accuracy of the MFCE system to a gold standard motion capture system and the system will be used to estimate the distribution of MFC values for the population. Full article
(This article belongs to the Special Issue Artificial Intelligence and Internet of Things in Health Applications)
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Open AccessArticle
Changes of Corneal Biomechanical Properties upon Exclusive Ytt-/Sr-90 Irradiation of Pterygium
Sensors 2021, 21(3), 975; https://doi.org/10.3390/s21030975 - 02 Feb 2021
Viewed by 320
Abstract
Background: It is known that pterygia above a certain size cause astigmatism and other aberrations of the human cornea and thus impair the quality of vision. Exclusive Sr-/Ytt-90 beta irradiation is a highly effective treatment for primary pterygia. The aim of this retrospective [...] Read more.
Background: It is known that pterygia above a certain size cause astigmatism and other aberrations of the human cornea and thus impair the quality of vision. Exclusive Sr-/Ytt-90 beta irradiation is a highly effective treatment for primary pterygia. The aim of this retrospective study is to determine the extent to which higher order corneal aberrations are affected by this treatment. Methods: Evaluation of corneal topographies and wavefront aberration data of 20 primary pterygia patients generated before and at different points in time in the first year after irradiation. Additionally, the size of the pterygium was measured. Results: The study showed a significant increase in coma and triple leaf aberrations in pterygia with a horizontal length of 2 mm and more. It was also found that a pterygium size greater than 2 mm significantly induces astigmatism. Both phenomena reduce visual quality. In none of the patients could a pterygium recurrence be detected after irradiation. Conclusions: If the pterygium size is less than 2 mm, early exclusive Sr/Ytt-90 beta irradiation can be recommended. If the size is more than 2 mm, a pterygium excision 6 months after beta irradiation can be discussed. Full article
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Open AccessArticle
Autonomous Vision-Based Primary Distribution Systems Porcelain Insulators Inspection Using UAVs
Sensors 2021, 21(3), 974; https://doi.org/10.3390/s21030974 - 02 Feb 2021
Viewed by 364
Abstract
The early detection of damaged (partially broken) outdoor insulators in primary distribution systems is of paramount importance for continuous electricity supply and public safety. Unmanned aerial vehicles (UAVs) present a safer, autonomous, and efficient way to examine the power system components without closing [...] Read more.
The early detection of damaged (partially broken) outdoor insulators in primary distribution systems is of paramount importance for continuous electricity supply and public safety. Unmanned aerial vehicles (UAVs) present a safer, autonomous, and efficient way to examine the power system components without closing the power distribution system. In this work, a novel dataset is designed by capturing real images using UAVs and manually generated images collected to overcome the data insufficiency problem. A deep Laplacian pyramid-based super-resolution network is implemented to reconstruct high-resolution training images. To improve the visibility of low-light images, a low-light image enhancement technique is used for the robust exposure correction of the training images. A different fine-tuning strategy is implemented for fine-tuning the object detection model to increase detection accuracy for the specific faulty insulators. Several flight path strategies are proposed to overcome the shuttering effect of insulators, along with providing a less complex and time- and energy-efficient approach for capturing a video stream of the power system components. The performance of different object detection models is presented for selecting the most suitable one for fine-tuning on the specific faulty insulator dataset. For the detection of damaged insulators, our proposed method achieved an F1-score of 0.81 and 0.77 on two different datasets and presents a simple and more efficient flight strategy. Our approach is based on real aerial inspection of in-service porcelain insulators by extensive evaluation of several video sequences showing robust fault recognition and diagnostic capabilities. Our approach is demonstrated on data acquired by a drone in Swat, Pakistan. Full article
(This article belongs to the Section Electronic Sensors)
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Open AccessArticle
A Spectral-Based Approach for BCG Signal Content Classification
Sensors 2021, 21(3), 1020; https://doi.org/10.3390/s21031020 - 02 Feb 2021
Viewed by 473
Abstract
This paper has two objectives: the first is to generate two binary flags to indicate useful frames permitting the measurement of cardiac and respiratory rates from Ballistocardiogram (BCG) signals—in fact, human body activities during measurements can disturb the BCG signal content, leading to [...] Read more.
This paper has two objectives: the first is to generate two binary flags to indicate useful frames permitting the measurement of cardiac and respiratory rates from Ballistocardiogram (BCG) signals—in fact, human body activities during measurements can disturb the BCG signal content, leading to difficulties in vital sign measurement; the second objective is to achieve refined BCG signal segmentation according to these activities. The proposed framework makes use of two approaches: an unsupervised classification based on the Gaussian Mixture Model (GMM) and a supervised classification based on K-Nearest Neighbors (KNN). Both of these approaches consider two spectral features, namely the Spectral Flatness Measure (SFM) and Spectral Centroid (SC), determined during the feature extraction step. Unsupervised classification is used to explore the content of the BCG signals, justifying the existence of different classes and permitting the definition of useful hyper-parameters for effective segmentation. In contrast, the considered supervised classification approach aims to determine if the BCG signal content allows the measurement of the heart rate (HR) and the respiratory rate (RR) or not. Furthermore, two levels of supervised classification are used to classify human-body activities into many realistic classes from the BCG signal (e.g., coughing, holding breath, air expiration, movement, et al.). The first one considers frame-by-frame classification, while the second one, aiming to boost the segmentation performance, transforms the frame-by-frame SFM and SC features into temporal series which track the temporal variation of the measures of the BCG signal. The proposed approach constitutes a novelty in this field and represents a powerful method to segment BCG signals according to human body activities, resulting in an accuracy of 94.6%. Full article
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Open AccessArticle
Intelligent Decision-Making of Scheduling for Dynamic Permutation Flowshop via Deep Reinforcement Learning
Sensors 2021, 21(3), 1019; https://doi.org/10.3390/s21031019 - 02 Feb 2021
Viewed by 423
Abstract
Dynamic scheduling problems have been receiving increasing attention in recent years due to their practical implications. To realize real-time and the intelligent decision-making of dynamic scheduling, we studied dynamic permutation flowshop scheduling problem (PFSP) with new job arrival using deep reinforcement learning (DRL). [...] Read more.
Dynamic scheduling problems have been receiving increasing attention in recent years due to their practical implications. To realize real-time and the intelligent decision-making of dynamic scheduling, we studied dynamic permutation flowshop scheduling problem (PFSP) with new job arrival using deep reinforcement learning (DRL). A system architecture for solving dynamic PFSP using DRL is proposed, and the mathematical model to minimize total tardiness cost is established. Additionally, the intelligent scheduling system based on DRL is modeled, with state features, actions, and reward designed. Moreover, the advantage actor-critic (A2C) algorithm is adapted to train the scheduling agent. The learning curve indicates that the scheduling agent learned to generate better solutions efficiently during training. Extensive experiments are carried out to compare the A2C-based scheduling agent with every single action, other DRL algorithms, and meta-heuristics. The results show the well performance of the A2C-based scheduling agent considering solution quality, CPU times, and generalization. Notably, the trained agent generates a scheduling action only in 2.16 ms on average, which is almost instantaneous and can be used for real-time scheduling. Our work can help to build a self-learning, real-time optimizing, and intelligent decision-making scheduling system. Full article
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Open AccessArticle
Emotion Recognition Based on Skin Potential Signals with a Portable Wireless Device
Sensors 2021, 21(3), 1018; https://doi.org/10.3390/s21031018 - 02 Feb 2021
Viewed by 395
Abstract
Emotion recognition is of great importance for artificial intelligence, robots, and medicine etc. Although many techniques have been developed for emotion recognition, with certain successes, they rely heavily on complicated and expensive equipment. Skin potential (SP) has been recognized to be correlated with [...] Read more.
Emotion recognition is of great importance for artificial intelligence, robots, and medicine etc. Although many techniques have been developed for emotion recognition, with certain successes, they rely heavily on complicated and expensive equipment. Skin potential (SP) has been recognized to be correlated with human emotions for a long time, but has been largely ignored due to the lack of systematic research. In this paper, we propose a single SP-signal-based method for emotion recognition. Firstly, we developed a portable wireless device to measure the SP signal between the middle finger and left wrist. Then, a video induction experiment was designed to stimulate four kinds of typical emotion (happiness, sadness, anger, fear) in 26 subjects. Based on the device and video induction, we obtained a dataset consisting of 397 emotion samples. We extracted 29 features from each of the emotion samples and used eight well-established algorithms to classify the four emotions based on these features. Experimental results show that the gradient-boosting decision tree (GBDT), logistic regression (LR) and random forest (RF) algorithms achieved the highest accuracy of 75%. The obtained accuracy is similar to, or even better than, that of other methods using multiple physiological signals. Our research demonstrates the feasibility of the SP signal’s integration into existing physiological signals for emotion recognition. Full article
(This article belongs to the Special Issue Sensor-Based Human Activity Monitoring)
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Open AccessCommunication
Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis
Sensors 2021, 21(3), 1017; https://doi.org/10.3390/s21031017 - 02 Feb 2021
Viewed by 478
Abstract
This work is dedicated to developing enzyme biosensor software to solve problems regarding soil pollution analysis. An algorithm and specialised software have been developed which stores, analyses and visualises data using JavaScript programming language. The developed software is based on matching data of [...] Read more.
This work is dedicated to developing enzyme biosensor software to solve problems regarding soil pollution analysis. An algorithm and specialised software have been developed which stores, analyses and visualises data using JavaScript programming language. The developed software is based on matching data of 51 non-commercial standard soil samples and their inhibitory effects on three enzyme systems of varying complexity. This approach is able to identify the influence of chemical properties soil samples, without toxic agents, on enzyme biosensors. Such software may find wide use in environmental monitoring. Full article
(This article belongs to the Special Issue Fluorescence and Chemical Luminescence Sensors)
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