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Sensors, Volume 14, Issue 9 (September 2014) – 118 articles , Pages 15641-17863

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813 KiB  
Article
In-Vivo Measurement of Muscle Tension: Dynamic Properties of the MC Sensor during Isometric Muscle Contraction
by Srđan Đorđević, Sašo Tomažič, Marco Narici, Rado Pišot and Andrej Meglič
Sensors 2014, 14(9), 17848-17863; https://doi.org/10.3390/s140917848 - 25 Sep 2014
Cited by 20 | Viewed by 10198
Abstract
Skeletal muscle is the largest tissue structure in our body and plays an essential role for producing motion through integrated action with bones, tendons, ligaments and joints, for stabilizing body position, for generation of heat through cell respiration and for blood glucose disposal. [...] Read more.
Skeletal muscle is the largest tissue structure in our body and plays an essential role for producing motion through integrated action with bones, tendons, ligaments and joints, for stabilizing body position, for generation of heat through cell respiration and for blood glucose disposal. A key function of skeletal muscle is force generation. Non-invasive and selective measurement of muscle contraction force in the field and in clinical settings has always been challenging. The aim of our work has been to develop a sensor that can overcome these difficulties and therefore enable measurement of muscle force during different contraction conditions. In this study, we tested the mechanical properties of a “Muscle Contraction” (MC) sensor during isometric muscle contraction in different length/tension conditions. The MC sensor is attached so that it indents the skin overlying a muscle group and detects varying degrees of tension during muscular contraction. We compared MC sensor readings over the biceps brachii (BB) muscle to dynamometric measurements of force of elbow flexion, together with recordings of surface EMG signal of BB during isometric contractions at 15° and 90° of elbow flexion. Statistical correlation between MC signal and force was very high at 15° (r = 0.976) and 90° (r = 0.966) across the complete time domain. Normalized SD or σN = σ/max(FMC) was used as a measure of linearity of MC signal and elbow flexion force in dynamic conditions. The average was 8.24% for an elbow angle of 90° and 10.01% for an elbow of angle 15°, which indicates high linearity and good dynamic properties of MC sensor signal when compared to elbow flexion force. The next step of testing MC sensor potential will be to measure tension of muscle-tendon complex in conditions when length and tension change simultaneously during human motion. Full article
(This article belongs to the Section Physical Sensors)
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1326 KiB  
Article
Data Fusion to Develop a Driver Drowsiness Detection System with Robustness to Signal Loss
by Sajjad Samiee, Shahram Azadi, Reza Kazemi, Ali Nahvi and Arno Eichberger
Sensors 2014, 14(9), 17832-17847; https://doi.org/10.3390/s140917832 - 25 Sep 2014
Cited by 47 | Viewed by 7857
Abstract
This study proposes a drowsiness detection approach based on the combination of several different detection methods, with robustness to the input signal loss. Hence, if one of the methods fails for any reason, the whole system continues to work properly. To choose correct [...] Read more.
This study proposes a drowsiness detection approach based on the combination of several different detection methods, with robustness to the input signal loss. Hence, if one of the methods fails for any reason, the whole system continues to work properly. To choose correct combination of the available methods and to utilize the benefits of methods of different categories, an image processing-based technique as well as a method based on driver-vehicle interaction is used. In order to avoid driving distraction, any use of an intrusive method is prevented. A driving simulator is used to gather real data and then artificial neural networks are used in the structure of the designed system. Several tests were conducted on twelve volunteers while their sleeping situations during one day prior to the tests, were fully under control. Although the impact of the proposed system on the improvement of the detection accuracy is not remarkable, the results indicate the main advantages of the system are the reliability of the detections and robustness to the loss of the input signals. The high reliability of the drowsiness detection systems plays an important role to reduce drowsiness related road accidents and their associated costs. Full article
(This article belongs to the Section Physical Sensors)
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608 KiB  
Editorial
Fluorescent Sensors for Biological Applications
by Hui-wang Ai
Sensors 2014, 14(9), 17829-17831; https://doi.org/10.3390/s140917829 - 25 Sep 2014
Cited by 13 | Viewed by 6247
Abstract
Fluorescence is one of the most important analytical methods used in biological studies. In the past decade or two, instrumentation in this field has greatly advanced, and now it is possible to detect single photons or fluorescent molecules [1,2], or break the Abbe [...] Read more.
Fluorescence is one of the most important analytical methods used in biological studies. In the past decade or two, instrumentation in this field has greatly advanced, and now it is possible to detect single photons or fluorescent molecules [1,2], or break the Abbe diffraction limit to distinguish two points spaced less than 50 nm apart [3]. Concurrently, the development of improved fluorescent probes, which can be coupled with state-of-the-art instruments, has been equally important. This special issue on “fluorescent biosensors” in Sensors reports recent results from eight research groups in the field of sensor development. It includes three review articles, and six research articles reporting original results. [...] Full article
(This article belongs to the Special Issue Fluorescent Biosensors)
1172 KiB  
Article
Gasohol Quality Control for Real Time Applications by Means of a Multimode Interference Fiber Sensor
by Adolfo J. Rodríguez Rodríguez, Oscar Baldovino-Pantaleón, Rene F. Domínguez Cruz, Carlos R. Zamarreño, Ignacio R. Matías and Daniel A. May-Arrioja
Sensors 2014, 14(9), 17817-17828; https://doi.org/10.3390/s140917817 - 25 Sep 2014
Cited by 21 | Viewed by 5775
Abstract
In this work we demonstrate efficient quality control of a variety of gasoline and ethanol (gasohol) blends using a multimode interference (MMI) fiber sensor. The operational principle relies on the fact that the addition of ethanol to the gasohol blend reduces the refractive [...] Read more.
In this work we demonstrate efficient quality control of a variety of gasoline and ethanol (gasohol) blends using a multimode interference (MMI) fiber sensor. The operational principle relies on the fact that the addition of ethanol to the gasohol blend reduces the refractive index (RI) of the gasoline. Since MMI sensors are capable of detecting small RI changes, the ethanol content of the gasohol blend is easily determined by tracking the MMI peak wavelength response. Gasohol blends with ethanol contents ranging from 0% to 50% has been clearly identified using this device, which provides a linear response with a maximum sensitivity of 0.270 nm/% EtOH. The sensor can also distinguish when water incorporated in the blend has exceeded the maximum volume tolerated by the gasohol blend, which is responsible for phase separation of the ethanol and gasoline and could cause serious engine failures. Since the MMI sensor is straightforward to fabricate and does not require any special coating it is a cost effective solution for real time and in-situ monitoring of the quality of gasohol blends. Full article
(This article belongs to the Section Physical Sensors)
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3782 KiB  
Article
Implementation of a Rotational Ultrasound Biomicroscopy System Equipped with a High-Frequency Angled Needle Transducer — Ex Vivo Ultrasound Imaging of Porcine Ocular Posterior Tissues
by Tae-Hoon Bok, Juho Kim, Jinho Bae, Chong Hyun Lee and Dong-Guk Paeng
Sensors 2014, 14(9), 17807-17816; https://doi.org/10.3390/s140917807 - 24 Sep 2014
Cited by 1 | Viewed by 6795
Abstract
The mechanical scanning of a single element transducer has been mostly utilized for high-frequency ultrasound imaging. However, it requires space for the mechanical motion of the transducer. In this paper, a rotational scanning ultrasound biomicroscopy (UBM) system equipped with a high-frequency angled needle [...] Read more.
The mechanical scanning of a single element transducer has been mostly utilized for high-frequency ultrasound imaging. However, it requires space for the mechanical motion of the transducer. In this paper, a rotational scanning ultrasound biomicroscopy (UBM) system equipped with a high-frequency angled needle transducer is designed and implemented in order to minimize the space required. It was applied to ex vivo ultrasound imaging of porcine posterior ocular tissues through a minimal incision hole of 1 mm in diameter. The retina and sclera for the one eye were visualized in the relative rotating angle range of 270° ~ 330° and at a distance range of 6 ~ 7 mm, whereas the tissues of the other eye were observed in relative angle range of 160° ~ 220° and at a distance range of 7.5 ~ 9 mm. The layer between retina and sclera seemed to be bent because the distance between the transducer tip and the layer was varied while the transducer was rotated. Certin features of the rotation system such as the optimal scanning angle, step angle and data length need to be improved for ensure higher accuracy and precision. Moreover, the focal length should be considered for the image quality. This implementation represents the first report of a rotational scanning UBM system. Full article
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567 KiB  
Article
An Efficient Approach for Preprocessing Data from a Large-Scale Chemical Sensor Array
by Marco Leo, Cosimo Distante, Mara Bernabei and Krishna Persaud
Sensors 2014, 14(9), 17786-17806; https://doi.org/10.3390/s140917786 - 24 Sep 2014
Cited by 6 | Viewed by 5826
Abstract
In this paper, an artificial olfactory system (Electronic Nose) that mimics thebiological olfactory system is introduced. The device consists of a Large-Scale ChemicalSensor Array (16; 384 sensors, made of 24 different kinds of conducting polymer materials)that supplies data to software modules, which perform [...] Read more.
In this paper, an artificial olfactory system (Electronic Nose) that mimics thebiological olfactory system is introduced. The device consists of a Large-Scale ChemicalSensor Array (16; 384 sensors, made of 24 different kinds of conducting polymer materials)that supplies data to software modules, which perform advanced data processing. Inparticular, the paper concentrates on the software components consisting, at first, of acrucial step that normalizes the heterogeneous sensor data and reduces their inherent noise.Cleaned data are then supplied as input to a data reduction procedure that extracts the mostinformative and discriminant directions in order to get an efficient representation in a lowerdimensional space where it is possible to more easily find a robust mapping between theobserved outputs and the characteristics of the odors in input to the device. Experimentalqualitative proofs of the validity of the procedure are given by analyzing data acquired fortwo different pure analytes and their binary mixtures. Moreover, a classification task isperformed in order to explore the possibility of automatically recognizing pure compoundsand to predict binary mixture concentrations. Full article
(This article belongs to the Section Chemical Sensors)
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1260 KiB  
Article
Voltammetric Electronic Tongue and Support Vector Machines for Identification of Selected Features in Mexican Coffee
by Rocio Berenice Domínguez, Laura Moreno-Barón, Roberto Muñoz and Juan Manuel Gutiérrez
Sensors 2014, 14(9), 17770-17785; https://doi.org/10.3390/s140917770 - 24 Sep 2014
Cited by 31 | Viewed by 8591
Abstract
This paper describes a new method based on a voltammetric electronic tongue (ET) for the recognition of distinctive features in coffee samples. An ET was directly applied to different samples from the main Mexican coffee regions without any pretreatment before the analysis. The [...] Read more.
This paper describes a new method based on a voltammetric electronic tongue (ET) for the recognition of distinctive features in coffee samples. An ET was directly applied to different samples from the main Mexican coffee regions without any pretreatment before the analysis. The resulting electrochemical information was modeled with two different mathematical tools, namely Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). Growing conditions (i.e., organic or non-organic practices and altitude of crops) were considered for a first classification. LDA results showed an average discrimination rate of 88% ± 6.53% while SVM successfully accomplished an overall accuracy of 96.4% ± 3.50% for the same task. A second classification based on geographical origin of samples was carried out. Results showed an overall accuracy of 87.5% ± 7.79% for LDA and a superior performance of 97.5% ± 3.22% for SVM. Given the complexity of coffee samples, the high accuracy percentages achieved by ET coupled with SVM in both classification problems suggested a potential applicability of ET in the assessment of selected coffee features with a simpler and faster methodology along with a null sample pretreatment. In addition, the proposed method can be applied to authentication assessment while improving cost, time and accuracy of the general procedure. Full article
(This article belongs to the Section Physical Sensors)
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1517 KiB  
Article
Development of a Wireless Computer Vision Instrument to Detect Biotic Stress in Wheat
by Joaquin J. Casanova, Susan A. O'Shaughnessy, Steven R. Evett and Charles M. Rush
Sensors 2014, 14(9), 17753-17769; https://doi.org/10.3390/s140917753 - 23 Sep 2014
Cited by 21 | Viewed by 8219
Abstract
Knowledge of crop abiotic and biotic stress is important for optimal irrigation management. While spectral reflectance and infrared thermometry provide a means to quantify crop stress remotely, these measurements can be cumbersome. Computer vision offers an inexpensive way to remotely detect crop stress [...] Read more.
Knowledge of crop abiotic and biotic stress is important for optimal irrigation management. While spectral reflectance and infrared thermometry provide a means to quantify crop stress remotely, these measurements can be cumbersome. Computer vision offers an inexpensive way to remotely detect crop stress independent of vegetation cover. This paper presents a technique using computer vision to detect disease stress in wheat. Digital images of differentially stressed wheat were segmented into soil and vegetation pixels using expectation maximization (EM). In the first season, the algorithm to segment vegetation from soil and distinguish between healthy and stressed wheat was developed and tested using digital images taken in the field and later processed on a desktop computer. In the second season, a wireless camera with near real-time computer vision capabilities was tested in conjunction with the conventional camera and desktop computer. For wheat irrigated at different levels and inoculated with wheat streak mosaic virus (WSMV), vegetation hue determined by the EM algorithm showed significant effects from irrigation level and infection. Unstressed wheat had a higher hue (118.32) than stressed wheat (111.34). In the second season, the hue and cover measured by the wireless computer vision sensor showed significant effects from infection (p = 0.0014), as did the conventional camera (p < 0.0001). Vegetation hue obtained through a wireless computer vision system in this study is a viable option for determining biotic crop stress in irrigation scheduling. Such a low-cost system could be suitable for use in the field in automated irrigation scheduling applications. Full article
(This article belongs to the Special Issue Agriculture and Forestry: Sensors, Technologies and Procedures)
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1720 KiB  
Review
Algal Biomass Analysis by Laser-Based Analytical Techniques—A Review
by Pavel Pořízka, Petra Prochazková, David Prochazka, Lucia Sládková, Jan Novotný, Michal Petrilak, Michal Brada, Ota Samek, Zdeněk Pilát, Pavel Zemánek, Vojtěch Adam, René Kizek, Karel Novotný and Jozef Kaiser
Sensors 2014, 14(9), 17725-17752; https://doi.org/10.3390/s140917725 - 23 Sep 2014
Cited by 52 | Viewed by 11864
Abstract
Algal biomass that is represented mainly by commercially grown algal strains has recently found many potential applications in various fields of interest. Its utilization has been found advantageous in the fields of bioremediation, biofuel production and the food industry. This paper reviews recent [...] Read more.
Algal biomass that is represented mainly by commercially grown algal strains has recently found many potential applications in various fields of interest. Its utilization has been found advantageous in the fields of bioremediation, biofuel production and the food industry. This paper reviews recent developments in the analysis of algal biomass with the main focus on the Laser-Induced Breakdown Spectroscopy, Raman spectroscopy, and partly Laser-Ablation Inductively Coupled Plasma techniques. The advantages of the selected laser-based analytical techniques are revealed and their fields of use are discussed in detail. Full article
(This article belongs to the Special Issue Advances in Optical Biosensors)
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8936 KiB  
Article
Theoretical Accuracy of Along-Track Displacement Measurements from Multiple-Aperture Interferometry (MAI)
by Hyung-Sup Jung, Won-Jin Lee and Lei Zhang
Sensors 2014, 14(9), 17703-17724; https://doi.org/10.3390/s140917703 - 23 Sep 2014
Cited by 32 | Viewed by 7250
Abstract
The measurement of precise along-track displacements has been made with the multiple-aperture interferometry (MAI). The empirical accuracies of the MAI measurements are about 6.3 and 3.57 cm for ERS and ALOS data, respectively. However, the estimated empirical accuracies cannot be generalized to any [...] Read more.
The measurement of precise along-track displacements has been made with the multiple-aperture interferometry (MAI). The empirical accuracies of the MAI measurements are about 6.3 and 3.57 cm for ERS and ALOS data, respectively. However, the estimated empirical accuracies cannot be generalized to any interferometric pair because they largely depend on the processing parameters and coherence of the used SAR data. A theoretical formula is given to calculate an expected MAI measurement accuracy according to the system and processing parameters and interferometric coherence. In this paper, we have investigated the expected MAI measurement accuracy on the basis of the theoretical formula for the existing X-, C- and L-band satellite SAR systems. The similarity between the expected and empirical MAI measurement accuracies has been tested as well. The expected accuracies of about 2–3 cm and 3–4 cm (γ = 0.8) are calculated for the X- and L-band SAR systems, respectively. For the C-band systems, the expected accuracy of Radarsat-2 ultra-fine is about 3–4 cm and that of Sentinel-1 IW is about 27 cm (γ = 0.8). The results indicate that the expected MAI measurement accuracy of a given interferometric pair can be easily calculated by using the theoretical formula. Full article
(This article belongs to the Section Remote Sensors)
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692 KiB  
Review
Development of Clinically Relevant Implantable Pressure Sensors: Perspectives and Challenges
by Ingelin Clausen and Thomas Glott
Sensors 2014, 14(9), 17686-17702; https://doi.org/10.3390/s140917686 - 22 Sep 2014
Cited by 50 | Viewed by 8671
Abstract
This review describes different aspects to consider when developing implantable pressure sensor systems. Measurement of pressure is in general highly important in clinical practice and medical research. Due to the small size, light weight and low energy consumption Micro Electro Mechanical Systems (MEMS) [...] Read more.
This review describes different aspects to consider when developing implantable pressure sensor systems. Measurement of pressure is in general highly important in clinical practice and medical research. Due to the small size, light weight and low energy consumption Micro Electro Mechanical Systems (MEMS) technology represents new possibilities for monitoring of physiological parameters inside the human body. Development of clinical relevant sensors requires close collaboration between technological experts and medical clinicians. Site of operation, size restrictions, patient safety, and required measurement range and resolution, are only some conditions that must be taken into account. An implantable device has to operate under very hostile conditions. Long-term in vivo pressure measurements are particularly demanding because the pressure sensitive part of the sensor must be in direct or indirect physical contact with the medium for which we want to detect the pressure. New sensor packaging concepts are demanded and must be developed through combined effort between scientists in MEMS technology, material science, and biology. Before launching a new medical device on the market, clinical studies must be performed. Regulatory documents and international standards set the premises for how such studies shall be conducted and reported. Full article
(This article belongs to the Special Issue Implantable Sensors)
2383 KiB  
Review
Boron Nitride Nanotubes for Spintronics
by Kamal B. Dhungana and Ranjit Pati
Sensors 2014, 14(9), 17655-17685; https://doi.org/10.3390/s140917655 - 22 Sep 2014
Cited by 48 | Viewed by 11253
Abstract
With the end of Moore’s law in sight, researchers are in search of an alternative approach to manipulate information. Spintronics or spin-based electronics, which uses the spin state of electrons to store, process and communicate information, offers exciting opportunities to sustain the current [...] Read more.
With the end of Moore’s law in sight, researchers are in search of an alternative approach to manipulate information. Spintronics or spin-based electronics, which uses the spin state of electrons to store, process and communicate information, offers exciting opportunities to sustain the current growth in the information industry. For example, the discovery of the giant magneto resistance (GMR) effect, which provides the foundation behind modern high density data storage devices, is an important success story of spintronics; GMR-based sensors have wide applications, ranging from automotive industry to biology. In recent years, with the tremendous progress in nanotechnology, spintronics has crossed the boundary of conventional, all metallic, solid state multi-layered structures to reach a new frontier, where nanostructures provide a pathway for the spin-carriers. Different materials such as organic and inorganic nanostructures are explored for possible applications in spintronics. In this short review, we focus on the boron nitride nanotube (BNNT), which has recently been explored for possible applications in spintronics. Unlike many organic materials, BNNTs offer higher thermal stability and higher resistance to oxidation. It has been reported that the metal-free fluorinated BNNT exhibits long range ferromagnetic spin ordering, which is stable at a temperature much higher than room temperature. Due to their large band gap, BNNTs are also explored as a tunnel magneto resistance device. In addition, the F-BNNT has recently been predicted as an ideal spin-filter. The purpose of this review is to highlight these recent progresses so that a concerted effort by both experimentalists and theorists can be carried out in the future to realize the true potential of BNNT-based spintronics. Full article
(This article belongs to the Special Issue Molecular Sensing and Molecular Electronics)
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1666 KiB  
Article
MIROS: A Hybrid Real-Time Energy-Efficient Operating System for the Resource-Constrained Wireless Sensor Nodes
by Xing Liu, Kun Mean Hou, Christophe De Vaulx, Hongling Shi and Khalid El Gholami
Sensors 2014, 14(9), 17621-17654; https://doi.org/10.3390/s140917621 - 22 Sep 2014
Cited by 12 | Viewed by 7692
Abstract
Operating system (OS) technology is significant for the proliferation of the wireless sensor network (WSN). With an outstanding OS; the constrained WSN resources (processor; memory and energy) can be utilized efficiently. Moreover; the user application development can be served soundly. In this article; [...] Read more.
Operating system (OS) technology is significant for the proliferation of the wireless sensor network (WSN). With an outstanding OS; the constrained WSN resources (processor; memory and energy) can be utilized efficiently. Moreover; the user application development can be served soundly. In this article; a new hybrid; real-time; memory-efficient; energy-efficient; user-friendly and fault-tolerant WSN OS MIROS is designed and implemented. MIROS implements the hybrid scheduler and the dynamic memory allocator. Real-time scheduling can thus be achieved with low memory consumption. In addition; it implements a mid-layer software EMIDE (Efficient Mid-layer Software for User-Friendly Application Development Environment) to decouple the WSN application from the low-level system. The application programming process can consequently be simplified and the application reprogramming performance improved. Moreover; it combines both the software and the multi-core hardware techniques to conserve the energy resources; improve the node reliability; as well as achieve a new debugging method. To evaluate the performance of MIROS; it is compared with the other WSN OSes (TinyOS; Contiki; SOS; openWSN and mantisOS) from different OS concerns. The final evaluation results prove that MIROS is suitable to be used even on the tight resource-constrained WSN nodes. It can support the real-time WSN applications. Furthermore; it is energy efficient; user friendly and fault tolerant. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and the Internet of Things)
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1056 KiB  
Article
Autonomous Navigation System Using a Fuzzy Adaptive Nonlinear H∞ Filter
by Fariz Outamazirt, Fu Li, Lin Yan and Abdelkrim Nemra
Sensors 2014, 14(9), 17600-17620; https://doi.org/10.3390/s140917600 - 19 Sep 2014
Cited by 11 | Viewed by 6971
Abstract
Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with [...] Read more.
Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds and adaptive disturbance attenuation , which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH∞ filter. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
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6961 KiB  
Article
Novel Wearable and Wireless Ring-Type Pulse Oximeter with Multi-Detectors
by Cheng-Yang Huang, Ming-Che Chan, Chien-Yue Chen and Bor-Shyh Lin
Sensors 2014, 14(9), 17586-17599; https://doi.org/10.3390/s140917586 - 19 Sep 2014
Cited by 39 | Viewed by 10760
Abstract
The pulse oximeter is a popular instrument to monitor the arterial oxygen saturation (SPO2). Although a fingertip-type pulse oximeter is the mainstream one on the market at present, it is still inconvenient for long-term monitoring, in particular, with respect to motion. [...] Read more.
The pulse oximeter is a popular instrument to monitor the arterial oxygen saturation (SPO2). Although a fingertip-type pulse oximeter is the mainstream one on the market at present, it is still inconvenient for long-term monitoring, in particular, with respect to motion. Therefore, the development of a wearable pulse oximeter, such as a finger base-type pulse oximeter, can effectively solve the above issue. However, the tissue structure of the finger base is complex, and there is lack of detailed information on the effect of the light source and detector placement on measuring SPO2. In this study, the practicability of a ring-type pulse oximeter with a multi-detector was investigated by optical human tissue simulation. The optimal design of a ring-type pulse oximeter that can provide the best efficiency of measuring SPO2 was discussed. The efficiency of ring-type pulse oximeters with a single detector and a multi-detector was also discussed. Finally, a wearable and wireless ring-type pulse oximeter was also implemented to validate the simulation results and was compared with the commercial fingertip-type pulse oximeter. Full article
(This article belongs to the Collection Sensors for Globalized Healthy Living and Wellbeing)
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2248 KiB  
Article
In-Flight Estimation of Center of Gravity Position Using All-Accelerometers
by Yazan Mohammad Al-Rawashdeh, Moustafa Elshafei and Mohammad Fahad Al-Malki
Sensors 2014, 14(9), 17567-17585; https://doi.org/10.3390/s140917567 - 19 Sep 2014
Cited by 28 | Viewed by 6931
Abstract
Changing the position of the Center of Gravity (CoG) for an aerial vehicle is a challenging part in navigation, and control of such vehicles. In this paper, an all-accelerometers-based inertial measurement unit is presented, with a proposed method for on-line estimation of the [...] Read more.
Changing the position of the Center of Gravity (CoG) for an aerial vehicle is a challenging part in navigation, and control of such vehicles. In this paper, an all-accelerometers-based inertial measurement unit is presented, with a proposed method for on-line estimation of the position of the CoG. The accelerometers’ readings are used to find and correct the vehicle’s angular velocity and acceleration using an Extended Kalman Filter. Next, the accelerometers’ readings along with the estimated angular velocity and acceleration are used in an identification scheme to estimate the position of the CoG and the vehicle’s linear acceleration. The estimated position of the CoG and motion measurements can then be used to update the control rules to achieve better trim conditions for the air vehicle. Full article
(This article belongs to the Section Physical Sensors)
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1814 KiB  
Article
Motion Planning for Autonomous Vehicle Based on Radial Basis Function Neural Network in Unstructured Environment
by Jiajia Chen, Pan Zhao, Huawei Liang and Tao Mei
Sensors 2014, 14(9), 17548-17566; https://doi.org/10.3390/s140917548 - 18 Sep 2014
Cited by 22 | Viewed by 8992
Abstract
The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the [...] Read more.
The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality. Full article
(This article belongs to the Section Physical Sensors)
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1807 KiB  
Article
Combined GPS/GLONASS Precise Point Positioning with Fixed GPS Ambiguities
by Lin Pan, Changsheng Cai, Rock Santerre and Jianjun Zhu
Sensors 2014, 14(9), 17530-17547; https://doi.org/10.3390/s140917530 - 18 Sep 2014
Cited by 17 | Viewed by 7497
Abstract
Precise point positioning (PPP) technology is mostly implemented with an ambiguity-float solution. Its performance may be further improved by performing ambiguity-fixed resolution. Currently, the PPP integer ambiguity resolutions (IARs) are mainly based on GPS-only measurements. The integration of GPS and GLONASS can speed [...] Read more.
Precise point positioning (PPP) technology is mostly implemented with an ambiguity-float solution. Its performance may be further improved by performing ambiguity-fixed resolution. Currently, the PPP integer ambiguity resolutions (IARs) are mainly based on GPS-only measurements. The integration of GPS and GLONASS can speed up the convergence and increase the accuracy of float ambiguity estimates, which contributes to enhancing the success rate and reliability of fixing ambiguities. This paper presents an approach of combined GPS/GLONASS PPP with fixed GPS ambiguities (GGPPP-FGA) in which GPS ambiguities are fixed into integers, while all GLONASS ambiguities are kept as float values. An improved minimum constellation method (MCM) is proposed to enhance the efficiency of GPS ambiguity fixing. Datasets from 20 globally distributed stations on two consecutive days are employed to investigate the performance of the GGPPP-FGA, including the positioning accuracy, convergence time and the time to first fix (TTFF). All datasets are processed for a time span of three hours in three scenarios, i.e., the GPS ambiguity-float solution, the GPS ambiguity-fixed resolution and the GGPPP-FGA resolution. The results indicate that the performance of the GPS ambiguity-fixed resolutions is significantly better than that of the GPS ambiguity-float solutions. In addition, the GGPPP-FGA improves the positioning accuracy by 38%, 25% and 44% and reduces the convergence time by 36%, 36% and 29% in the east, north and up coordinate components over the GPS-only ambiguity-fixed resolutions, respectively. Moreover, the TTFF is reduced by 27% after adding GLONASS observations. Wilcoxon rank sum tests and chi-square two-sample tests are made to examine the significance of the improvement on the positioning accuracy, convergence time and TTFF. Full article
(This article belongs to the Section Remote Sensors)
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1865 KiB  
Article
A Lossless Multichannel Bio-Signal Compression Based on Low-Complexity Joint Coding Scheme for Portable Medical Devices
by Dong-Sun Kim and Jin-San Kwon
Sensors 2014, 14(9), 17516-17529; https://doi.org/10.3390/s140917516 - 18 Sep 2014
Cited by 6 | Viewed by 5018
Abstract
Research on real-time health systems have received great attention during recent years and the needs of high-quality personal multichannel medical signal compression for personal medical product applications are increasing. The international MPEG-4 audio lossless coding (ALS) standard supports a joint channel-coding scheme for [...] Read more.
Research on real-time health systems have received great attention during recent years and the needs of high-quality personal multichannel medical signal compression for personal medical product applications are increasing. The international MPEG-4 audio lossless coding (ALS) standard supports a joint channel-coding scheme for improving compression performance of multichannel signals and it is very efficient compression method for multi-channel biosignals. However, the computational complexity of such a multichannel coding scheme is significantly greater than that of other lossless audio encoders. In this paper, we present a multichannel hardware encoder based on a low-complexity joint-coding technique and shared multiplier scheme for portable devices. A joint-coding decision method and a reference channel selection scheme are modified for a low-complexity joint coder. The proposed joint coding decision method determines the optimized joint-coding operation based on the relationship between the cross correlation of residual signals and the compression ratio. The reference channel selection is designed to select a channel for the entropy coding of the joint coding. The hardware encoder operates at a 40 MHz clock frequency and supports two-channel parallel encoding for the multichannel monitoring system. Experimental results show that the compression ratio increases by 0.06%, whereas the computational complexity decreases by 20.72% compared to the MPEG-4 ALS reference software encoder. In addition, the compression ratio increases by about 11.92%, compared to the single channel based bio-signal lossless data compressor. Full article
(This article belongs to the Section Physical Sensors)
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3367 KiB  
Article
Estimation of Eye Closure Degree Using EEG Sensors and Its Application in Driver Drowsiness Detection
by Gang Li and Wan-Young Chung
Sensors 2014, 14(9), 17491-17515; https://doi.org/10.3390/s140917491 - 18 Sep 2014
Cited by 38 | Viewed by 10677
Abstract
Currently, driver drowsiness detectors using video based technology is being widely studied. Eyelid closure degree (ECD) is the main measure of the video-based methods, however, drawbacks such as brightness limitations and practical hurdles such as distraction of the drivers limits its success. This [...] Read more.
Currently, driver drowsiness detectors using video based technology is being widely studied. Eyelid closure degree (ECD) is the main measure of the video-based methods, however, drawbacks such as brightness limitations and practical hurdles such as distraction of the drivers limits its success. This study presents a way to compute the ECD using EEG sensors instead of video-based methods. The premise is that the ECD exhibits a linear relationship with changes of the occipital EEG. A total of 30 subjects are included in this study: ten of them participated in a simple proof-of-concept experiment to verify the linear relationship between ECD and EEG, and then twenty participated in a monotonous highway driving experiment in a driving simulator environment to test the robustness of the linear relationship in real-life applications. Taking the video-based method as a reference, the Alpha power percentage from the O2 channel is found to be the best input feature for linear regression estimation of the ECD. The best overall squared correlation coefficient (SCC, denoted by r2) and mean squared error (MSE) validated by linear support vector regression model and leave one subject out method is r2 = 0.930 and MSE = 0.013. The proposed linear EEG-ECD model can achieve 87.5% and 70.0% accuracy for male and female subjects, respectively, for a driver drowsiness application, percentage eyelid closure over the pupil over time (PERCLOS). This new ECD estimation method not only addresses the video-based method drawbacks, but also makes ECD estimation more computationally efficient and easier to implement in EEG sensors in a real time way. Full article
(This article belongs to the Special Issue HCI In Smart Environments)
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14043 KiB  
Article
Calibration of Action Cameras for Photogrammetric Purposes
by Caterina Balletti, Francesco Guerra, Vassilios Tsioukas and Paolo Vernier
Sensors 2014, 14(9), 17471-17490; https://doi.org/10.3390/s140917471 - 18 Sep 2014
Cited by 86 | Viewed by 14587
Abstract
The use of action cameras for photogrammetry purposes is not widespread due to the fact that until recently the images provided by the sensors, using either still or video capture mode, were not big enough to perform and provide the appropriate analysis with [...] Read more.
The use of action cameras for photogrammetry purposes is not widespread due to the fact that until recently the images provided by the sensors, using either still or video capture mode, were not big enough to perform and provide the appropriate analysis with the necessary photogrammetric accuracy. However, several manufacturers have recently produced and released new lightweight devices which are: (a) easy to handle, (b) capable of performing under extreme conditions and more importantly (c) able to provide both still images and video sequences of high resolution. In order to be able to use the sensor of action cameras we must apply a careful and reliable self-calibration prior to the use of any photogrammetric procedure, a relatively difficult scenario because of the short focal length of the camera and its wide angle lens that is used to obtain the maximum possible resolution of images. Special software, using functions of the OpenCV library, has been created to perform both the calibration and the production of undistorted scenes for each one of the still and video image capturing mode of a novel action camera, the GoPro Hero 3 camera that can provide still images up to 12 Mp and video up 8 Mp resolution. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Italy 2014)
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2723 KiB  
Article
Active Disaster Response System for a Smart Building
by Chun-Yen Lin, Edward T.-H Chu, Lun-Wei Ku and Jane W. S. Liu
Sensors 2014, 14(9), 17451-17470; https://doi.org/10.3390/s140917451 - 18 Sep 2014
Cited by 38 | Viewed by 9253
Abstract
Disaster warning and surveillance systems have been widely applied to help the public be aware of an emergency. However, existing warning systems are unable to cooperate with household appliances or embedded controllers; that is, they cannot provide enough time for preparedness and evacuation, [...] Read more.
Disaster warning and surveillance systems have been widely applied to help the public be aware of an emergency. However, existing warning systems are unable to cooperate with household appliances or embedded controllers; that is, they cannot provide enough time for preparedness and evacuation, especially for disasters like earthquakes. In addition, the existing warning and surveillance systems are not responsible for collecting sufficient information inside a building for relief workers to conduct a proper rescue action after a disaster happens. In this paper, we describe the design and implementation of a proof of concept prototype, named the active disaster response system (ADRS), which automatically performs emergency tasks when an earthquake happens. ADRS can interpret Common Alerting Protocol (CAP) messages, published by an official agency, and actuate embedded controllers to perform emergency tasks to respond to the alerts. Examples of emergency tasks include opening doors and windows and cutting off power lines and gas valves. In addition, ADRS can maintain a temporary network by utilizing the embedded controllers; hence, victims trapped inside a building are still able to post emergency messages if the original network is disconnected. We conducted a field trial to evaluate the effectiveness of ADRS after an earthquake happened. Our results show that compared to manually operating emergency tasks, ADRS can reduce the operation time by up to 15 s, which is long enough for people to get under sturdy furniture, or to evacuate from the third floor to the first floor, or to run more than 100 m. Full article
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3060 KiB  
Article
Statistical Analysis-Based Error Models for the Microsoft KinectTM Depth Sensor
by Benjamin Choo, Michael Landau, Michael DeVore and Peter A. Beling
Sensors 2014, 14(9), 17430-17450; https://doi.org/10.3390/s140917430 - 18 Sep 2014
Cited by 33 | Viewed by 6579
Abstract
The stochastic error characteristics of the Kinect sensing device are presented for each axis direction. Depth (z) directional error is measured using a flat surface, and horizontal (x) and vertical (y) errors are measured using a novel [...] Read more.
The stochastic error characteristics of the Kinect sensing device are presented for each axis direction. Depth (z) directional error is measured using a flat surface, and horizontal (x) and vertical (y) errors are measured using a novel 3D checkerboard. Results show that the stochastic nature of the Kinect measurement error is affected mostly by the depth at which the object being sensed is located, though radial factors must be considered, as well. Measurement and statistics-based models are presented for the stochastic error in each axis direction, which are based on the location and depth value of empirical data measured for each pixel across the entire field of view. The resulting models are compared against existing Kinect error models, and through these comparisons, the proposed model is shown to be a more sophisticated and precise characterization of the Kinect error distributions. Full article
(This article belongs to the Section Physical Sensors)
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3250 KiB  
Review
Gas Sensors Based on Semiconducting Nanowire Field-Effect Transistors
by Ping Feng, Feng Shao, Yi Shi and Qing Wan
Sensors 2014, 14(9), 17406-17429; https://doi.org/10.3390/s140917406 - 17 Sep 2014
Cited by 75 | Viewed by 12982
Abstract
One-dimensional semiconductor nanostructures are unique sensing materials for the fabrication of gas sensors. In this article, gas sensors based on semiconducting nanowire field-effect transistors (FETs) are comprehensively reviewed. Individual nanowires or nanowire network films are usually used as the active detecting channels. In [...] Read more.
One-dimensional semiconductor nanostructures are unique sensing materials for the fabrication of gas sensors. In this article, gas sensors based on semiconducting nanowire field-effect transistors (FETs) are comprehensively reviewed. Individual nanowires or nanowire network films are usually used as the active detecting channels. In these sensors, a third electrode, which serves as the gate, is used to tune the carrier concentration of the nanowires to realize better sensing performance, including sensitivity, selectivity and response time, etc. The FET parameters can be modulated by the presence of the target gases and their change relate closely to the type and concentration of the gas molecules. In addition, extra controls such as metal decoration, local heating and light irradiation can be combined with the gate electrode to tune the nanowire channel and realize more effective gas sensing. With the help of micro-fabrication techniques, these sensors can be integrated into smart systems. Finally, some challenges for the future investigation and application of nanowire field-effect gas sensors are discussed. Full article
(This article belongs to the Special Issue Gas Sensors Based on the Field Effect)
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710 KiB  
Article
Application of an Online-Biomass Sensor in an Optical Multisensory Platform Prototype for Growth Monitoring of Biotechnical Relevant Microorganism and Cell Lines in Single-Use Shake Flasks
by Christian Ude, Jörg Schmidt-Hager, Michael Findeis, Gernot Thomas John, Thomas Scheper and Sascha Beutel
Sensors 2014, 14(9), 17390-17405; https://doi.org/10.3390/s140917390 - 17 Sep 2014
Cited by 39 | Viewed by 8672
Abstract
In the context of this work we evaluated a multisensory, noninvasive prototype platform for shake flask cultivations by monitoring three basic parameters (pH, pO2 and biomass). The focus lies on the evaluation of the biomass sensor based on backward light scattering. The [...] Read more.
In the context of this work we evaluated a multisensory, noninvasive prototype platform for shake flask cultivations by monitoring three basic parameters (pH, pO2 and biomass). The focus lies on the evaluation of the biomass sensor based on backward light scattering. The application spectrum was expanded to four new organisms in addition to E. coli K12 and S. cerevisiae [1]. It could be shown that the sensor is appropriate for a wide range of standard microorganisms, e.g., L. zeae, K. pastoris, A. niger and CHO-K1. The biomass sensor signal could successfully be correlated and calibrated with well-known measurement methods like OD600, cell dry weight (CDW) and cell concentration. Logarithmic and Bleasdale-Nelder derived functions were adequate for data fitting. Measurements at low cell concentrations proved to be critical in terms of a high signal to noise ratio, but the integration of a custom made light shade in the shake flask improved these measurements significantly. This sensor based measurement method has a high potential to initiate a new generation of online bioprocess monitoring. Metabolic studies will particularly benefit from the multisensory data acquisition. The sensor is already used in labscale experiments for shake flask cultivations. Full article
(This article belongs to the Special Issue Sensors for Bioprocess Monitoring and Control)
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1510 KiB  
Article
A Novel Position Estimation Method Based on Displacement Correction in AIS
by Yi Jiang, Shufang Zhang and Dongkai Yang
Sensors 2014, 14(9), 17376-17389; https://doi.org/10.3390/s140917376 - 17 Sep 2014
Cited by 11 | Viewed by 5507
Abstract
A new position estimation method by using the signals from two automatic identification system (AIS) stations is proposed in this paper. The time of arrival (TOA) method is enhanced with the displacement correction, so that the vessel’s position can be determined even for [...] Read more.
A new position estimation method by using the signals from two automatic identification system (AIS) stations is proposed in this paper. The time of arrival (TOA) method is enhanced with the displacement correction, so that the vessel’s position can be determined even for the situation where it can receive the signals from only two AIS base stations. Its implementation scheme based on the mathematical model is presented. Furthermore, performance analysis is carried out to illustrate the relation between the positioning errors and the displacement vector provided by auxiliary sensors. Finally, the positioning method is verified and its performance is evaluated by simulation. The results show that the positioning accuracy is acceptable. Full article
(This article belongs to the Section Physical Sensors)
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4540 KiB  
Article
An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation
by Honghang Yan, Fang Deng, Jian Sun and Jie Chen
Sensors 2014, 14(9), 17353-17375; https://doi.org/10.3390/s140917353 - 17 Sep 2014
Cited by 1 | Viewed by 4765
Abstract
In this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and memory space [...] Read more.
In this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and memory space of the training process. A linear decomposition algorithm, which automatically finds the optimal decomposition N and reduces the training time to 1 N and memory cost to 1 N , has been implemented on nonlinear data obtained from an encoder. Particular focus is given to the theoretical access of estimating the numbers of hidden nodes and the precision of varying the decomposition method. Numerical experiments are designed to evaluate the effect of this algorithm. Moreover, a designed device for angular sensor calibration is presented. We conduct an experiment that samples the data of an encoder and compensates for the nonlinearity of the encoder to testify this novel algorithm. Full article
(This article belongs to the Section Physical Sensors)
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1729 KiB  
Article
Combining Non Selective Gas Sensors on a Mobile Robot for Identification and Mapping of Multiple Chemical Compounds
by Victor Hernandez Bennetts, Erik Schaffernicht, Victor Pomareda, Achim J. Lilienthal, Santiago Marco and Marco Trincavelli
Sensors 2014, 14(9), 17331-17352; https://doi.org/10.3390/s140917331 - 17 Sep 2014
Cited by 30 | Viewed by 10314
Abstract
In this paper, we address the task of gas distribution modeling in scenarios where multiple heterogeneous compounds are present. Gas distribution modeling is particularly useful in emission monitoring applications where spatial representations of the gaseous patches can be used to identify emission hot [...] Read more.
In this paper, we address the task of gas distribution modeling in scenarios where multiple heterogeneous compounds are present. Gas distribution modeling is particularly useful in emission monitoring applications where spatial representations of the gaseous patches can be used to identify emission hot spots. In realistic environments, the presence of multiple chemicals is expected and therefore, gas discrimination has to be incorporated in the modeling process. The approach presented in this work addresses the task of gas distribution modeling by combining different non selective gas sensors. Gas discrimination is addressed with an open sampling system, composed by an array of metal oxide sensors and a probabilistic algorithm tailored to uncontrolled environments. For each of the identified compounds, the mapping algorithm generates a calibrated gas distribution model using the classification uncertainty and the concentration readings acquired with a photo ionization detector. The meta parameters of the proposed modeling algorithm are automatically learned from the data. The approach was validated with a gas sensitive robot patrolling outdoor and indoor scenarios, where two different chemicals were released simultaneously. The experimental results show that the generated multi compound maps can be used to accurately predict the location of emitting gas sources. Full article
(This article belongs to the Section Chemical Sensors)
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7767 KiB  
Article
Integration of Multisensor Hybrid Reasoners to Support Personal Autonomy in the Smart Home
by Miguel Ángel Valero, José Bravo, Juan Manuel García Chamizo and Diego López-de-Ipiña
Sensors 2014, 14(9), 17313-17330; https://doi.org/10.3390/s140917313 - 17 Sep 2014
Cited by 10 | Viewed by 7428
Abstract
The deployment of the Ambient Intelligence (AmI) paradigm requires designing and integrating user-centered smart environments to assist people in their daily life activities. This research paper details an integration and validation of multiple heterogeneous sensors with hybrid reasoners that support decision making in [...] Read more.
The deployment of the Ambient Intelligence (AmI) paradigm requires designing and integrating user-centered smart environments to assist people in their daily life activities. This research paper details an integration and validation of multiple heterogeneous sensors with hybrid reasoners that support decision making in order to monitor personal and environmental data at a smart home in a private way. The results innovate on knowledge-based platforms, distributed sensors, connected objects, accessibility and authentication methods to promote independent living for elderly people. TALISMAN+, the AmI framework deployed, integrates four subsystems in the smart home: (i) a mobile biomedical telemonitoring platform to provide elderly patients with continuous disease management; (ii) an integration middleware that allows context capture from heterogeneous sensors to program environment´s reaction; (iii) a vision system for intelligent monitoring of daily activities in the home; and (iv) an ontologies-based integrated reasoning platform to trigger local actions and manage private information in the smart home. The framework was integrated in two real running environments, the UPM Accessible Digital Home and MetalTIC house, and successfully validated by five experts in home care, elderly people and personal autonomy. Full article
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3757 KiB  
Article
Screen-Printed Resistive Pressure Sensors Containing Graphene Nanoplatelets and Carbon Nanotubes
by Daniel Janczak, Marcin Słoma, Grzegorz Wróblewski, Anna Młożniak and Małgorzata Jakubowska
Sensors 2014, 14(9), 17304-17312; https://doi.org/10.3390/s140917304 - 16 Sep 2014
Cited by 50 | Viewed by 9209
Abstract
Polymer composites with nanomaterials such as graphene nanoplatelets and carbon nanotubes are a new group of materials with high application possibilities in printed and flexible electronics. In this study such carbon nanomaterials were used as a conductive phase in polymer composites. Pastes with [...] Read more.
Polymer composites with nanomaterials such as graphene nanoplatelets and carbon nanotubes are a new group of materials with high application possibilities in printed and flexible electronics. In this study such carbon nanomaterials were used as a conductive phase in polymer composites. Pastes with dispersed nanomaterials in PMMA and PVDF vehicles were screen printed on flexible substrates, and used as an active layer in pressure sensors, exploiting contact resistance phenomena. The relationship between resistance and pressure is nearly linear on a logarithmic scale for selected types of samples, and their response is several times higher than for similar sensors with graphite layers. The use of surfactants allowed us to fabricate evenly dispersed nanomaterials with different amount of nanoplatelets and nanotubes in the composites. The samples contained from 1.25 wt.% to 2 wt.% of graphene and 1 wt.% to 0.5 wt.% of nanotubes and exhibited diverse sheet resistivity. Experiments revealed the relationship between morphology and loading of functional phase in the polymer matrix and the sensors’ sensitivity. Full article
(This article belongs to the Special Issue Printed Sensors)
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