Trans-radial prosthesis is a wearable device that intends to help amputees under the elbow to replace the function of the missing anatomical segment that resembles an actual human hand. However, there are some challenging aspects faced mainly on the robot hand structural design itself. Improvements are needed as this is closely related to structure efficiency. This paper proposes a robot hand structure with improved features (four-bar linkage mechanism) to overcome the deficiency of using the cable-driven actuated mechanism that leads to less structure durability and inaccurate motion range. Our proposed robot hand structure also took into account the existing design problems such as bulky structure, unindividual actuated finger, incomplete fingers and a lack of finger joints compared to the actual finger in its design. This paper presents the improvements achieved by applying the proposed design such as the use of a four-bar linkage mechanism instead of using the cable-driven mechanism, the size of an average human hand, five-fingers with completed joints where each finger is moved by motor individually, joint protection using a mechanical stopper, detachable finger structure from the palm frame, a structure that has sufficient durability for everyday use and an easy to fabricate structure using 3D printing technology. The four-bar linkage mechanism is the use of the solid linkage that connects the actuator with the structure to allow the structure to move. The durability was investigated using static analysis simulation. The structural details and simulation results were validated through motion capture analysis and load test. The motion analyses towards the 3D printed robot structure show 70-98% similar motion range capability to the designed structure in the CAD software, and it can withstand up to 1.6 kg load in the simulation and the real test. The improved robot hand structure with optimum durability for prosthetic uses was successfully developed.
Transparent object detection and reconstruction are significant, due to their practical applications. The appearance and characteristics of light in these objects make reconstruction methods tailored for Lambertian surfaces fail disgracefully. In this paper, we introduce a fixed multi-viewpoint approach to ascertain the shape of transparent objects, thereby avoiding the rotation or movement of the object during imaging. In addition, a simple and cost-effective experimental setup is presented, which employs two single-pixel detectors and a digital micromirror device, for imaging transparent objects by projecting binary patterns. In the system setup, a dark framework is implemented around the object, to create shades at the boundaries of the object. By triangulating the light path from the object, the surface shape is recovered, neither considering the reflections nor the number of refractions. It can, therefore, handle transparent objects with a relatively complex shape with the unknown refractive index. The implementation of compressive sensing in this technique further simplifies the acquisition process, by reducing the number of measurements. The experimental results show that 2D images obtained from the single-pixel detectors are better in quality with a resolution of 32×32. Additionally, the obtained disparity and error map indicate the feasibility and accuracy of the proposed method. This work provides a new insight into 3D transparent object detection and reconstruction, based on single-pixel imaging at an affordable cost, with the implementation of a few numbers of detectors.
The enzyme-linked Immunosorbent Assay (ELISA) is the gold standard clinical diagnostic tool for the detection and quantification of protein biomarkers. However, conventional ELISA tests have drawbacks in their requirement of time, expensive equipment and expertise for operation. Hence, for the purpose of rapid, high throughput screening and point-of-care diagnosis, researchers are miniaturizing sandwich ELISA procedures on Lab-on-a-Chip and Lab-on-Compact Disc (LOCD) platforms. This paper presents a novel integrated device to detect and interpret the ELISA test results on a LOCD platform. The system applies absorption spectrophotometry to measure the absorbance (optical density) of the sample using a monochromatic light source and optical sensor. The device performs automated analysis of the results and presents absorbance values and diagnostic test results via a graphical display or via Bluetooth to a smartphone platform which also acts as controller of the device. The efficacy of the device was evaluated by performing dengue antibody IgG ELISA on 64 hospitalized patients suspected of dengue. The results demonstrate high accuracy of the device, with 95% sensitivity and 100% specificity in detection when compared with gold standard commercial ELISA microplate readers. This sensor platform represents a significant step towards establishing ELISA as a rapid, inexpensive and automatic testing method for the purpose of point-of-care-testing (POCT) in resource-limited settings.
A developed colorimetric pH sensor film based on edible materials for real-time monitoring of food freshness is described. The mixed natural dyes from edible plants Clitoria sp and Brassica sp were extracted and incorporated into ι-carrageenan film as a colorimetric pH sensor film for monitoring food spoilage and its freshness. The color changes of the developed colorimetric sensor film were measured with chromametry and UV-vis spectroscopy, respectively. Experimental results show that colorimetric pH sensor film demonstrated statistically significant differences (p < 0.05) between CIE-L*a*b* coordinates color system indicated that the developed colorimetric sensor film was able to give a gradual change in color over a wide pH range. The color of the colorimetric sensor film also changes discretely and linearly with factors that contribute to food spoilage using shrimp and durian samples. Moreover, the developed colorimetric pH sensor film has the potential to be used as a safe, non-destructive testing and also a flexibly visual method for direct assessment of food freshness indicator during storage.
A minimally-sized, triple-notched band ultra-wideband (UWB) antenna, useful for many applications, is designed, analyzed, and experimentally validated in this paper. A modified maple leaf-shaped main radiating element with partial ground is used in the proposed design. An E-shaped resonator, meandered slot, and U-shaped slot are implemented in the proposed design to block the co-existing bands. The E-shaped resonator stops frequencies ranging from 1.8⁻2.3 GHz (Advanced Wireless System (AWS1⁻AWS2) band), while the meandered slot blocks frequencies from 3.2⁻3.8 GHz (WiMAX band). The co-existing band ranging from 5.6⁻6.1 GHz (IEEE 802.11/HIPERLANband) is blocked by utilizing the U-shaped section in the feeding network. The notched bands can be independently controlled over a wide range of frequencies using specific parameters. The proposed antenna is suitable for many applications because of its flat gain, good radiation characteristics at both principal planes, uniform group delay, and non-varying transfer function ( S 21 ) for the entire UWB frequency range.
A compact ultrawideband (UWB) antenna based on a hexagonal split-ring resonator (HSRR) is presented in this paper for sensing the pH factor. The modified HSRR is a new concept regarding the conventional square split-ring resonator (SSRR). Two HSRRs are interconnected with a strip line and a split in one HSRR is introduced to increase the electrical length and coupling effect. The presented UWB antenna consists of three unit cells on top of the radiating patch element. This combination of UWB antenna and HSRR gives double-negative characteristics which increase the sensitivity of the UWB antenna for the pH sensor. The proposed ultrawideband antenna metamaterial sensor was designed and fabricated on FR-4 substrate. The electrical length of the proposed metamaterial antenna sensor is 0.238 × 0.194 × 0.016 λ, where λ is the lowest frequency of 3 GHz. The fractional bandwidth and bandwidth dimension ratio were achieved with the metamaterial-inspired antenna as 146.91% and 3183.05, respectively. The operating frequency of this antenna sensor covers the bandwidth of 17 GHz, starting from 3 to 20 GHz with a realized gain of 3.88 dB. The proposed HSRR-based ultrawideband antenna sensor is found to reach high gain and bandwidth while maintaining the smallest electrical size, a highly desired property for pH-sensing applications.
In this paper, a dielectric resonator antenna (DRA) with high gain and wide impedance bandwidth for fifth-generation (5G) wireless communication applications is proposed. The dielectric resonator antenna is designed to operate at higher-order TEδ15x mode to achieve high antenna gain, while a hollow cylinder at the center of the DRA is introduced to improve bandwidth by reducing the quality factor. The DRA is excited by a 50Ω microstrip line with a narrow aperture slot. The reflection coefficient, antenna gain, and radiation pattern of the proposed DRAs are analyzed using the commercially available full-wave electromagnetic simulation tool CST Microwave Studio (CST MWS). In order to verify the simulation results, the proposed antenna structures were fabricated and experimentally validated. Measured results of the fabricated prototypes show a 10-dB return loss impedance bandwidth of 10.7% (14.3-15.9GHz) and 16.1% (14.1-16.5 GHz) for DRA1 and DRA2, respectively, at the operating frequency of 15 GHz. The results show that the designed antenna structure can be used in the Internet of things (IoT) for device-to-device (D2D) communication in 5G systems.
This paper demonstrates the use of Universal Software Radio Peripheral (USRP), together with Raspberry Pi3 B+ (RP3) as the brain (or the decision making engine), to develop a distributed wireless network in which nodes can communicate with other nodes independently and make decision autonomously. In other words, each USRP node (i.e., sensor) is embedded with separate processing units (i.e., RP3), which has not been investigated in the literature, so that each node can make independent decisions in a distributed manner. The proposed testbed in this paper is compared with the traditional distributed testbed, which has been widely used in the literature. In the traditional distributed testbed, there is a single processing unit (i.e., a personal computer) that makes decisions in a centralized manner, and each node (i.e., USRP) is connected to the processing unit via a switch. The single processing unit exchanges control messages with nodes via the switch, while the nodes exchange data packets among themselves using a wireless medium in a distributed manner. The main disadvantage of the traditional testbed is that, despite the network being distributed in nature, decisions are made in a centralized manner. Hence, the response delay of the control message exchange is always neglected. The use of such testbed is mainly due to the limited hardware and monetary cost to acquire a separate processing unit for each node. The experiment in our testbed has shown the increase of end-to-end delay and decrease of packet delivery ratio due to software and hardware delays. The observed multihop transmission is performed using device-to-device (D2D) communication, which has been enabled in 5G. Therefore, nodes can either communicate with other nodes via: (a) a direct communication with the base station at the macrocell, which helps to improve network performance; or (b) D2D that improve spectrum efficiency, whereby traffic is offloaded from macrocell to small cells. Our testbed is the first of its kind in this scale, and it uses RP3 as the distributed decision-making engine incorporated into the USRP/GNU radio platform. This work provides an insight to the development of a 5G network.
In acoustic receiver design, the receiving sensitivity and bandwidth are two primary parameters that determine the performance of a device. The trade-off between sensitivity and bandwidth makes the design very challenging, meaning it needs to be fine-tuned to suit specific applications. The ability to design a PMUT with high receiving sensitivity and a wide bandwidth is crucial to allow a wide spectrum of transmitted frequencies to be efficiently received. This paper presents a novel structure involving a double flexural membrane with a fluidic backing layer based on an in-plane polarization mode to optimize both the receiving sensitivity and frequency bandwidth for medium-range underwater acoustic applications. In this structure, the membrane material and electrode configuration are optimized to produce good receiving sensitivity. Simultaneously, a fluidic backing layer is introduced into the double flexural membrane to increase the bandwidth. Several piezoelectric membrane materials and various electrode dimensions were simulated using finite element analysis (FEA) techniques to study the receiving performance of the proposed structure. The final structure was then fabricated based on the findings from the simulation work. The pulse-echo experimental method was used to characterize and verify the performance of the proposed device. The proposed structure was found to have an improved bandwidth of 56.6% with a receiving sensitivity of -1.8864 dB rel 1 V µPa. For the proposed device, the resonance frequency and center frequency were 600 and 662.5 kHz, respectively, indicating its suitability for the targeted frequency range.
The bi-directional information transfer in optical body area networks (OBANs) is crucial at all the three tiers of communication, i.e., intra-, inter-, and beyond-BAN communication, which correspond to tier-I, tier-II, and tier-III, respectively. However, the provision of uninterrupted uplink (UL) and downlink (DL) connections at tier II (inter-BAN) are extremely critical, since these links serve as a bridge between tier-I (intra-BAN) and tier-III (beyond-BAN) communication. Any negligence at this level could be life-threatening; therefore, enabling quality-of-service (QoS) remains a fundamental design issue at tier-II. Consequently, to provide QoS, a key parameter is to ensure link reliability and communication quality by maintaining a nearly uniform signal-to-noise ratio (SNR) within the coverage area. Several studies have reported the effects of transceiver related parameters on OBAN link performance, nevertheless the implications of changing transmitter locations on the SNR uniformity and communication quality have not been addressed. In this work, we undertake a DL scenario and analyze how the placement of light-emitting diode (LED) lamps can improve the SNR uniformity, regardless of the receiver position. Subsequently, we show that using the principle of reciprocity (POR) and with transmitter-receiver positions switched, the analysis is also applicable to UL, provided that the optical channel remains linear. Moreover, we propose a generalized optimal placement scheme along with a heuristic design formula to achieve uniform SNR and illuminance for DL using a fixed number of transmitters and compare it with an existing technique. The study reveals that the proposed placement technique reduces the fluctuations in SNR by 54% and improves the illuminance uniformity up to 102% as compared to the traditional approach. Finally, we show that, for very low luminous intensity, the SNR values remain sufficient to maintain a minimum bit error rate (BER) of 10-9 with on-off keying non-return-to-zero (OOK-NRZ) modulation format.
A novel label-free electrochemical DNA biosensor was constructed for the determination of Escherichia coli bacteria in environmental water samples. The aminated DNA probe was immobilized onto hollow silica microspheres (HSMs) functionalized with 3-aminopropyltriethoxysilane and deposited onto a screen-printed electrode (SPE) carbon paste with supported gold nanoparticles (AuNPs). The biosensor was optimized for higher specificity and sensitivity. The label-free E. coli DNA biosensor exhibited a dynamic linear response range of 1 × 10-10 µM to 1 × 10-5 µM (R2 = 0.982), with a limit of detection at 1.95 × 10-15 µM, without a redox mediator. The sensitivity of the developed DNA biosensor was comparable to the non-complementary and single-base mismatched DNA. The DNA biosensor demonstrated a stable response up to 21 days of storage at 4 ℃ and pH 7. The DNA biosensor response was regenerable over three successive regeneration and rehybridization cycles.
Microwave breast imaging has been reported as having the most potential to become an alternative or additional tool to the existing X-ray mammography technique for detecting breast tumors. Microwave antenna sensor performance plays a significant role in microwave imaging system applications because the image quality is mostly affected by the microwave antenna sensor array properties like the number of antenna sensors in the array and the size of the antenna sensors. In this paper, a new system for successful early detection of a breast tumor using a balanced slotted antipodal Vivaldi Antenna (BSAVA) sensor is presented. The designed antenna sensor has an overall dimension of 0.401λ × 0.401λ × 0.016λ at the first resonant frequency and operates between 3.01 to 11 GHz under 10 dB. The radiating fins are modified by etching three slots on both fins which increases the operating bandwidth, directionality of radiation pattern, gain and efficiency. The antenna sensor performance of both the frequency domain and time domain scenarios and high-fidelity factor with NFD is also investigated. The antenna sensor can send and receive short electromagnetic pulses in the near field with low loss, little distortion and highly directionality. A realistic homogenous breast phantom is fabricated, and a breast phantom measurement system is developed where a two antennas sensor is placed on the breast model rotated by a mechanical scanner. The tumor response was investigated by analyzing the backscattering signals and successful image construction proves that the proposed microwave antenna sensor can be a suitable candidate for a high-resolution microwave breast imaging system.
Driver drowsiness is a major cause of fatal accidents, injury, and property damage, and has become an area of substantial research attention in recent years. The present study proposes a method to detect drowsiness in drivers which integrates features of electrocardiography (ECG) and electroencephalography (EEG) to improve detection performance. The study measures differences between the alert and drowsy states from physiological data collected from 22 healthy subjects in a driving simulator-based study. A monotonous driving environment is used to induce drowsiness in the participants. Various time and frequency domain feature were extracted from EEG including time domain statistical descriptors, complexity measures and power spectral measures. Features extracted from the ECG signal included heart rate (HR) and heart rate variability (HRV), including low frequency (LF), high frequency (HF) and LF/HF ratio. Furthermore, subjective sleepiness scale is also assessed to study its relationship with drowsiness. We used paired t-tests to select only statistically significant features (p < 0.05), that can differentiate between the alert and drowsy states effectively. Significant features of both modalities (EEG and ECG) are then combined to investigate the improvement in performance using support vector machine (SVM) classifier. The other main contribution of this paper is the study on channel reduction and its impact to the performance of detection. The proposed method demonstrated that combining EEG and ECG has improved the system's performance in discriminating between alert and drowsy states, instead of using them alone. Our channel reduction analysis revealed that an acceptable level of accuracy (80%) could be achieved by combining just two electrodes (one EEG and one ECG), indicating the feasibility of a system with improved wearability compared with existing systems involving many electrodes. Overall, our results demonstrate that the proposed method can be a viable solution for a practical driver drowsiness system that is both accurate and comfortable to wear.
Electrocardiogram (ECG) signals play a vital role in diagnosing and monitoring patients suffering from various cardiovascular diseases (CVDs). This research aims to develop a robust algorithm that can accurately classify the electrocardiogram signal even in the presence of environmental noise. A one-dimensional convolutional neural network (CNN) with two convolutional layers, two down-sampling layers, and a fully connected layer is proposed in this work. The same 1D data was transformed into two-dimensional (2D) images to improve the model's classification accuracy. Then, we applied the 2D CNN model consisting of input and output layers, three 2D-convolutional layers, three down-sampling layers, and a fully connected layer. The classification accuracy of 97.38% and 99.02% is achieved with the proposed 1D and 2D model when tested on the publicly available Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database. Both proposed 1D and 2D CNN models outperformed the corresponding state-of-the-art classification algorithms for the same data, which validates the proposed models' effectiveness.
High demand of semiconductor gas sensor works at low operating temperature to as low as 100 °C has led to the fabrication of gas sensor based on TiO₂ nanoparticles. A sensing film of gas sensor was prepared by mixing the sensing material, TiO₂ (P25) and glass powder, and B₂O₃ with organic binder. The sensing film was annealed at temperature of 500 °C in 30 min. The morphological and structural properties of the sensing film were characterized by field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD). The gas sensor was exposed to hydrogen with concentration of 100⁻1000 ppm and was tested at different operating temperatures which are 100 °C, 200 °C, and 300 °C to find the optimum operating temperature for producing the highest sensitivity. The gas sensor exhibited p-type conductivity based on decreased current when exposed to hydrogen. The gas sensor showed capability in sensing low concentration of hydrogen to as low as 100 ppm at 100 °C.
A low-cost, low-power, and low data-rate solution is proposed to fulfill the requirements of information monitoring for actual large-scale agricultural farms. A small-scale farm can be easily managed. By contrast, a large farm will require automating equipment that contributes to crop production. Sensor based soil properties measurement plays an integral role in designing a fully automated agricultural farm, also provides more satisfactory results than any manual method. The existing information monitoring solutions are inefficient in terms of higher deployment cost and limited communication range to adapt the need of large-scale agriculture farms. A serial based low-power, long-range, and low-cost communication module is proposed to confront the challenges of monitoring information over long distances. In the proposed system, a tree-based communication mechanism is deployed to extend the communication range by adding intermediate nodes. Each sensor node consists of a solar panel, a rechargeable cell, a microcontroller, a moisture sensor, and a communication unit. Each node is capable to work as a sensor node and router node for network traffic. Minimized data logs from the central node are sent daily to the cloud for future analytics purpose. After conducting a detailed experiment in open sight, the communication distance measured 250 m between two points and increased to 750 m by adding two intermediate nodes. The minimum working current of each node was 2 mA, and the packet loss rate was approximately 2-5% on different packet sizes of the entire network. Results show that the proposed approach can be used as a reference model to meet the requirements for soil measurement, transmission, and storage in a large-scale agricultural farm.
The assessment of moisture loss from meat during the aging period is a critical issue for the meat industry. In this article, a non-invasive microwave ring-resonator sensor is presented to evaluate the moisture content, or more precisely water holding capacity (WHC) of broiler meat over a four-week period. The developed sensor has shown significant changes in its resonance frequency and return loss due to reduction in WHC in the studied duration. The obtained results are also confirmed by physical measurements. Further, these results are evaluated using the Fricke model, which provides a good fit for electric circuit components in biological tissue. Significant changes were observed in membrane integrity, where the corresponding capacitance decreases 30% in the early aging (0D-7D) period. Similarly, the losses associated with intracellular and extracellular fluids exhibit changed up to 42% and 53%, respectively. Ultimately, empirical polynomial models are developed to predict the electrical component values for a better understanding of aging effects. The measured and calculated values are found to be in good agreement.
Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental studies. Many essential layers can be extracted from this land surface information, including slope, aspect, rivers, and curvature. Therefore, DEM quality and accuracy will affect the extracted features and the whole process of modeling. Despite freely available DEMs from various sources, many researchers generate this information for their areas from various observations. Sentinal-1 synthetic aperture radar (SAR) images are among the best Earth observations for DEM generation thanks to their availabilities, high-resolution, and C-band sensitivity to surface structure. This paper presents a comparative study, from a hydrological point of view, on the quality and reliability of the DEMs generated from Sentinel-1 data and DEMs from other sources such as AIRSAR, ALOS-PALSAR, TanDEM-X, and SRTM. To this end, pair of Sentinel-1 data were acquired and processed using the SAR interferometry technique to produce a DEM for two different study areas of a part of the Cameron Highlands, Pahang, Malaysia, a part of Sanandaj, Iran. Based on the estimated linear regression and standard errors, generating DEM from Sentinel-1 did not yield promising results. The river streams for all DEMs were extracted using geospatial analysis tool in a geographic information system (GIS) environment. The results indicated that because of the higher spatial resolution (compared to SRTM and TanDEM-X), more stream orders were delineated from AIRSAR and Sentinel-1 DEMs. Due to the shorter perpendicular baseline, the phase decorrelation in the created DEM resulted in a lot of noise. At the same time, results from ground control points (GCPs) showed that the created DEM from Sentinel-1 is not promising. Therefore, other DEMs' performance, such as 90-meters' TanDEM-X and 30-meters' SRTM, are better than Sentinel-1 DEM (with a better spatial resolution).
The importance of body area sensor networks (BASNs) is increasing day by day because of their increasing use in Internet of things (IoT)-enabled healthcare application services. They help humans in improving their quality of life by continuously monitoring various vital signs through biosensors strategically placed on the human body. However, BASNs face serious challenges, in terms of the short life span of their batteries and unreliable data transmission, because of the highly unstable and unpredictable channel conditions of tiny biosensors located on the human body. These factors may result in poor data gathering quality in BASNs. Therefore, a more reliable data transmission mechanism is greatly needed in order to gather quality data in BASN-based healthcare applications. Therefore, this study proposes a novel, multiobjective, lion mating optimization inspired routing protocol, called self-organizing multiobjective routing protocol (SARP), for BASN-based IoT healthcare applications. The proposed routing scheme significantly reduces local search problems and finds the best dynamic cluster-based routing solutions between the source and destination in BASNs. Thus, it significantly improves the overall packet delivery rate, residual energy, and throughput with reduced latency and packet error rates in BASNs. Extensive simulation results validate the performance of our proposed SARP scheme against the existing routing protocols in terms of the packet delivery ratio, latency, packet error rate, throughput, and energy efficiency for BASN-based health monitoring applications.
This paper presents a negative index metamaterial incorporated UWB antenna with an integration of complementary SRR (split-ring resonator) and CLS (capacitive loaded strip) unit cells for microwave imaging sensor applications. This metamaterial UWB antenna sensor consists of four unit cells along one axis, where each unit cell incorporates a complementary SRR and CLS pair. This integration enables a design layout that allows both a negative value of permittivity and a negative value of permeability simultaneous, resulting in a durable negative index to enhance the antenna sensor performance for microwave imaging sensor applications. The proposed MTM antenna sensor was designed and fabricated on an FR4 substrate having a thickness of 1.6 mm and a dielectric constant of 4.6. The electrical dimensions of this antenna sensor are 0.20 λ × 0.29 λ at a lower frequency of 3.1 GHz. This antenna sensor achieves a 131.5% bandwidth (VSWR < 2) covering the frequency bands from 3.1 GHz to more than 15 GHz with a maximum gain of 6.57 dBi. High fidelity factor and gain, smooth surface-current distribution and nearly omni-directional radiation patterns with low cross-polarization confirm that the proposed negative index UWB antenna is a promising entrant in the field of microwave imaging sensors.