Real-time monitoring and precise diagnosis of the severity of Dengue infection is needed for better decisions in disease management. The aim of this study is to use the Bioimpedance Vector Analysis (BIVA) method to differentiate between healthy subjects and severe and non-severe Dengue-infected patients. Bioimpedance was measured using a 50 KHz single-frequency bioimpedance analyzer. Data from 299 healthy subjects (124 males and 175 females) and 205 serologically confirmed Dengue patients (123 males and 82 females) were analyzed in this study. The obtained results show that the BIVA method was able to assess and classify the body fluid and cell mass condition between the healthy subjects and the Dengue-infected patients. The bioimpedance mean vectors (95% confidence ellipse) for healthy subjects, severe and non-severe Dengue-infected patients were illustrated. The vector is significantly shortened from healthy subjects to Dengue patients; for both genders the p-value is less than 0.0001. The mean vector of severe Dengue patients is significantly shortened compare to non-severe patients with a p-value of 0.0037 and 0.0023 for males and females, respectively. This study confirms that the BIVA method is a valid method in differentiating the healthy, severe and non-severe Dengue-infected subjects. All tests performed had a significance level with a p-value less than 0.05.
An on-chip optical humidity sensor using Nano-anatase TiO₂ coating is presented here. The coating material was prepared so that the result is in solution form, making the fabrication process quick and simple. Then, the solution was effortlessly spin-coated on an SU8 straight channel waveguide. Investigating the sensitivity and performance (response time) of the device revealed a great linearity in the wide range (35% to 98%) of relative humidity (RH). In addition, a variation of more than 14 dB in transmitted optical power was observed, with a response time of only ~0.7 s. The effect of coating concentration and UV treatment was examined on the performance and repeatability of the sensor. Interesting observations were found, and the attributed mechanisms were described. In addition, the proposed sensor was extensively compared with other state-of-the-art proposed counterparts from the literature and remarkable advantages were found. Since a high sensitivity of ~0.21 dB/%RH and high dynamic performances were demonstrated, this sensor is proposed for use in biomedical applications.
We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed on the scalp following the 10-20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1-db20), Symlets (sym1-sym20), and Coiflets (coif1-coif5). Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using "sym9" across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions.
The lack of information on ground truth gas dispersion and experiment verification information has impeded the development of mobile olfaction systems, especially for real-world conditions. In this paper, an integrated testbed for mobile gas sensing experiments is presented. The integrated 3 m × 6 m testbed was built to provide real-time ground truth information for mobile olfaction system development. The testbed consists of a 72-gas-sensor array, namely Large Gas Sensor Array (LGSA), a localization system based on cameras and a wireless communication backbone for robot communication and integration into the testbed system. Furthermore, the data collected from the testbed may be streamed into a simulation environment to expedite development. Calibration results using ethanol have shown that using a large number of gas sensor in the LGSA is feasible and can produce coherent signals when exposed to the same concentrations. The results have shown that the testbed was able to capture the time varying characteristics and the variability of gas plume in a 2 h experiment thus providing time dependent ground truth concentration maps. The authors have demonstrated the ability of the mobile olfaction testbed to monitor, verify and thus, provide insight to gas distribution mapping experiment.
Localization is an apparent aspect of a wireless sensor network, which is the focus of much interesting research. One of the severe conditions that needs to be taken into consideration is localizing a mobile target through a dispersed sensor network in the presence of physical barrier attacks. These attacks confuse the localization process and cause location estimation errors. Range-based methods, like the received signal strength indication (RSSI), face the major influence of this kind of attack. This paper proposes a solution based on a combination of multi-frequency multi-power localization (C-MFMPL) and step function multi-frequency multi-power localization (SF-MFMPL), including the fingerprint matching technique and lateration, to provide a robust and accurate localization technique. In addition, this paper proposes a grid coloring algorithm to detect the signal hole map in the network, which refers to the attack-prone regions, in order to carry out corrective actions. The simulation results show the enhancement and robustness of RSS localization performance in the face of log normal shadow fading effects, besides the presence of physical barrier attacks, through detecting, filtering and eliminating the effect of these attacks.
Biosensors fabricated with whole-cell bacteria appear to be suitable for detecting bioavailability and toxicity effects of the chemical(s) of concern, but they are usually reported to have drawbacks like long response times (ranging from hours to days), narrow dynamic range and instability during long term storage. Our aim is to fabricate a sensitive whole-cell oxidative stress biosensor which has improved properties that address the mentioned weaknesses. In this paper, we report a novel high-throughput whole-cell biosensor fabricated by immobilizing roGFP2 expressing Escherichia coli cells in a k-carrageenan matrix, for the detection of oxidative stress challenged by metalloid compounds. The E. coli roGFP2 oxidative stress biosensor shows high sensitivity towards arsenite and selenite, with wide linear range and low detection limit (arsenite: 1.0 × 10(-3)-1.0 × 10(1) mg·L(-1), LOD: 2.0 × 10(-4) mg·L(-1); selenite: 1.0 × 10(-5)-1.0 × 10(2) mg·L(-1), LOD: 5.8 × 10(-6) mg·L(-1)), short response times (0-9 min), high stability and reproducibility. This research is expected to provide a new direction in performing high-throughput environmental toxicity screening with living bacterial cells which is capable of measuring the bioavailability and toxicity of environmental stressors in a friction of a second.
The fabrication of Metal-DNA-Metal (MDM) structure-based high sensitivity sensors from DNA micro-and nanoarray strands is a key issue in their development. The tunable semiconducting response of DNA in the presence of external electromagnetic and thermal fields is a gift for molecular electronics. The impact of temperatures (25-55 °C) and magnetic fields (0-1200 mT) on the current-voltage (I-V) features of Au-DNA-Au (GDG) structures with an optimum gap of 10 μm is reported. The I-V characteristics acquired in the presence and absence of magnetic fields demonstrated the semiconducting diode nature of DNA in GDG structures with high temperature sensitivity. The saturation current in the absence of magnetic field was found to increase sharply with the increase of temperature up to 45 °C and decrease rapidly thereafter. This increase was attributed to the temperature-assisted conversion of double bonds into single bond in DNA structures. Furthermore, the potential barrier height and Richardson constant for all the structures increased steadily with the increase of external magnetic field irrespective of temperature variations. Our observation on magnetic field and temperature sensitivity of I-V response in GDG sandwiches may contribute towards the development of DNA-based magnetic sensors.
Ferroelectric poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) copolymer 70/30 thin films are prepared by spin coating. The crystalline structure of these films is investigated by varying the annealing temperature from the ferroelectric phase to the paraelectric phase. A hot plate was used to produce a direct and an efficient annealing effect on the thin film. The dielectric, ferroelectric and pyroelectric properties of the P(VDF-TrFE) thin films are measured as a function of different annealing temperatures (80 to 140 °C). It was found that an annealing temperature of 100 °C (slightly above the Curie temperature, Tc) has induced a highly crystalline β phase with a rod-like crystal structure, as examined by X-ray. Such a crystal structure yields a high remanent polarization, Pr = 94 mC/m2, and pyroelectric constant, p = 24 μC/m2K. A higher annealing temperature exhibits an elongated needle-like crystal domain, resulting in a decrease in the crystalline structure and the functional electrical properties. This study revealed that highly crystalline P(VDF-TrFE) thin films could be induced at 100 °C by annealing the thin film with a simple and cheap method.
Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of Everything (IoE). WSNs have a wide range of applications but are usually deployed in a particular application. However, the future of WSNs lies in the aggregation and allocation of resources, serving diverse applications. WSN virtualization by the middleware is an emerging concept that enables aggregation of multiple independent heterogeneous devices, networks, radios and software platforms; and enhancing application development. WSN virtualization, middleware can further be categorized into sensor virtualization and network virtualization. Middleware for WSN virtualization poses several challenges like efficient decoupling of networks, devices and software. In this paper efforts have been put forward to bring an overview of the previous and current middleware designs for WSN virtualization, the design goals, software architectures, abstracted services, testbeds and programming techniques. Furthermore, the paper also presents the proposed model, challenges and future opportunities for further research in the middleware designs for WSN virtualization.
With the development of communication technologies, the use of wireless systems in biomedical implanted devices has become very useful. Bio-implantable devices are electronic devices which are used for treatment and monitoring brain implants, pacemakers, cochlear implants, retinal implants and so on. The inductive coupling link is used to transmit power and data between the primary and secondary sides of the biomedical implanted system, in which efficient power amplifier is very much needed to ensure the best data transmission rates and low power losses. However, the efficiency of the implanted devices depends on the circuit design, controller, load variation, changes of radio frequency coil's mutual displacement and coupling coefficients. This paper provides a comprehensive survey on various power amplifier classes and their characteristics, efficiency and controller techniques that have been used in bio-implants. The automatic frequency controller used in biomedical implants such as gate drive switching control, closed loop power control, voltage controlled oscillator, capacitor control and microcontroller frequency control have been explained. Most of these techniques keep the resonance frequency stable in transcutaneous power transfer between the external coil and the coil implanted inside the body. Detailed information including carrier frequency, power efficiency, coils displacement, power consumption, supplied voltage and CMOS chip for the controllers techniques are investigated and summarized in the provided tables. From the rigorous review, it is observed that the existing automatic frequency controller technologies are more or less can capable of performing well in the implant devices; however, the systems are still not up to the mark. Accordingly, current challenges and problems of the typical automatic frequency controller techniques for power amplifiers are illustrated, with a brief suggestions and discussion section concerning the progress of implanted device research in the future. This review will hopefully lead to increasing efforts towards the development of low powered, highly efficient, high data rate and reliable automatic frequency controllers for implanted devices.
We present a ternary blend-based bulk heterojunction ITO/PEDOT:PSS/PFO-DBT: MEH-PPV:PC71BM/LiF/Al photodetector. Enhanced optical absorption range of the active film has been achieved by blending two donor components viz. poly[2,7-(9,9-di-octyl-fluorene)-alt-4,7-bis(thiophen-2-yl)benzo-2,1,3-thiadiazole] (PFO-DBT) and poly(2-methoxy-5(2'-ethylhexyloxy) phenylenevinylene (MEH-PPV) along with an acceptor component, i.e., (6,6)-phenyl-C71 hexnoic acid methyl ester. The dependency of the generation rate of free charge carriers in the organic photodetector (OPD) on varied incident optical power density was investigated as a function of different reverse biasing voltages. The photocurrent showed significant enhancement as the intensity of light impinging on active area of OPD is increased. The ratio of Ilight to Idark of fabricated device at -3 V was ~3.5 × 10(4). The dynamic behaviour of the OPD under on/off switching irradiation revealed that sensor exhibits quick response and recovery time of ∼800 ms and 500 ms, respectively. Besides reliability and repeatability in the photoresponse characteristics, the cost-effective and eco-friendly fabrication is the added benefit of the fabricated OPD.
Alternative sensory systems for the development of prosthetic knees are being increasingly highlighted nowadays, due to the rapid advancements in the field of lower limb prosthetics. This study presents the use of piezoelectric bimorphs as in-socket sensors for transfemoral amputees. An Instron machine was used in the calibration procedure and the corresponding output data were further analyzed to determine the static and dynamic characteristics of the piezoelectric bimorph. The piezoelectric bimorph showed appropriate static operating range, repeatability, hysteresis, and frequency response for application in lower prosthesis, with a force range of 0-100 N. To further validate this finding, an experiment was conducted with a single transfemoral amputee subject to measure the stump/socket pressure using the piezoelectric bimorph embedded inside the socket. The results showed that a maximum interface pressure of about 27 kPa occurred at the anterior proximal site compared to the anterior distal and posterior sites, consistent with values published in other studies. This paper highlighted the capacity of piezoelectric bimorphs to perform as in-socket sensors for transfemoral amputees. However, further experiments are recommended to be conducted with different amputees with different socket types.
The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity.
A double SAW resonator system was developed as a novel method for gas sensing applications. The proposed system was investigated for hydrogen sensing. Commercial Surface Acoustic Wave (SAW) resonators with resonance frequencies of 433.92 MHz and 433.42 MHz were employed in the double SAW resonator system configuration. The advantages of using this configuration include its ability for remote measurements, and insensitivity to vibrations and other external disturbances. The sensitive layer is composed of functionalized multiwalled carbon nanotubes and polyaniline nanofibers which were deposited on pre-patterned platinum metal electrodes fabricated on a piezoelectric substrate. This was mounted into the DSAWR circuit and connected in parallel. The sensor response was measured as the difference between the resonance frequencies of the SAW resonators, which is a measure of the gas concentration. The sensor showed good response towards hydrogen with a minimum detection limit of 1%.
Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.
The staggering growth in smartphone and wearable device use has led to a massive scale generation of personal (user-specific) data. To explore, analyze, and extract useful information and knowledge from the deluge of personal data, one has to leverage these devices as the data-mining platforms in ubiquitous, pervasive, and big data environments. This study presents the personal ecosystem where all computational resources, communication facilities, storage and knowledge management systems are available in user proximity. An extensive review on recent literature has been conducted and a detailed taxonomy is presented. The performance evaluation metrics and their empirical evidences are sorted out in this paper. Finally, we have highlighted some future research directions and potentially emerging application areas for personal data mining using smartphones and wearable devices.
As the main exporter in the oil palm industry, the need to improve the quality of palm oil has become the main interest among all the palm oil millers in Malaysia. To produce good quality palm oil, it is important for the miller to harvest a good oil palm Fresh Fruit Bunch (FFB). Conventionally, the main reference used by Malaysian harvesters is the manual grading standard published by the Malaysian Palm Oil Board (MPOB). A good oil palm FFB consists of all matured fruitlets, aged between 18 to 21 weeks of antheses (WAA). To expedite the harvesting process, it is crucial to implement an automated detection system for determining the maturity of the oil palm FFB. Various automated detection methods have been proposed by researchers in the field to replace the conventional method. In our preliminary study, a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunch was proposed. The design of the proposed air coil sensor based on the inductive sensor was further investigated mainly in the context of the effect of coil diameter to improve its sensitivity. In this paper, the sensitivity of the inductive sensor was further examined with a dual flat-type shape of air coil. The dual air coils were tested on fifteen samples of fruitlet from two categories, namely ripe and unripe. Samples were tested within 20 Hz to 10 MHz while evaluations on both peaks were done separately before the gap between peaks was analyzed. A comparative analysis was conducted to investigate the improvement in sensitivity of the induction-based oil palm fruit sensor as compared to previous works. Results from the comparative study proved that the inductive sensor using a dual flat-type shape air coil has improved by up to 167%. This provides an indication in the improvement in the coil sensitivity of the palm oil fruit sensor based on the induction concept.
The optical characteristics of graphene oxide (GO) were explored to design and fabricate a GO-based optical humidity sensor. GO film was coated onto a SU8 polymer channel waveguide using the drop-casting technique. The proposed sensor shows a high TE-mode absorption at 1550 nm. Due to the dependence of the dielectric properties of the GO film on water content, this high TE-mode absorption decreases when the ambient relative humidity increases. The proposed sensor shows a rapid response (<1 s) to periodically interrupted humid air flow. The transmission of the proposed sensor shows a linear response of 0.553 dB/% RH in the range of 60% to 100% RH.
This paper presents a performance analysis of two open-source, laser scanner-based Simultaneous Localization and Mapping (SLAM) techniques (i.e., Gmapping and Hector SLAM) using a Microsoft Kinect to replace the laser sensor. Furthermore, the paper proposes a new system integration approach whereby a Linux virtual machine is used to run the open source SLAM algorithms. The experiments were conducted in two different environments; a small room with no features and a typical office corridor with desks and chairs. Using the data logged from real-time experiments, each SLAM technique was simulated and tested with different parameter settings. The results show that the system is able to achieve real time SLAM operation. The system implementation offers a simple and reliable way to compare the performance of Windows-based SLAM algorithm with the algorithms typically implemented in a Robot Operating System (ROS). The results also indicate that certain modifications to the default laser scanner-based parameters are able to improve the map accuracy. However, the limited field of view and range of Kinect's depth sensor often causes the map to be inaccurate, especially in featureless areas, therefore the Kinect sensor is not a direct replacement for a laser scanner, but rather offers a feasible alternative for 2D SLAM tasks.
The success of a Wireless Sensor Network (WSN) deployment strongly depends on the quality of service (QoS) it provides regarding issues such as data accuracy, data aggregation delays and network lifetime maximisation. This is especially challenging in data fusion mechanisms, where a small fraction of low quality data in the fusion input may negatively impact the overall fusion result. In this paper, we present a fuzzy-based data fusion approach for WSN with the aim of increasing the QoS whilst reducing the energy consumption of the sensor network. The proposed approach is able to distinguish and aggregate only true values of the collected data as such, thus reducing the burden of processing the entire data at the base station (BS). It is also able to eliminate redundant data and consequently reduce energy consumption thus increasing the network lifetime. We studied the effectiveness of the proposed data fusion approach experimentally and compared it with two baseline approaches in terms of data collection, number of transferred data packets and energy consumption. The results of the experiments show that the proposed approach achieves better results than the baseline approaches.