Showing papers in "IEEE Transactions on Instrumentation and Measurement in 2010"

Multifocus Image Fusion and Restoration With Sparse Representation

Abstract: To obtain an image with every object in focus, we always need to fuse images taken from the same view point with different focal settings. Multiresolution transforms, such as pyramid decomposition and wavelet, are usually used to solve this problem. In this paper, a sparse representation-based multifocus image fusion method is proposed. In the method, first, the source image is represented with sparse coefficients using an overcomplete dictionary. Second, the coefficients are combined with the choose-max fusion rule. Finally, the fused image is reconstructed from the combined sparse coefficients and the dictionary. Furthermore, the proposed fusion scheme can simultaneously resolve the image restoration and fusion problem by changing the approximate criterion in the sparse representation algorithm. The proposed method is compared with spatial gradient (SG)-, morphological wavelet transform (MWT)-, discrete wavelet transform (DWT)-, stationary wavelet transform (SWT)-, curvelet transform (CVT)-, and nonsubsampling contourlet transform (NSCT)-based methods on several pairs of multifocus images. The experimental results demonstrate that the proposed approach performs better in both subjective and objective qualities.

Digital Image Watermarking Using Discrete Wavelet Transform and Singular Value Decomposition

Abstract: The main objective of developing an image-watermarking technique is to satisfy both imperceptibility and robustness requirements. To achieve this objective, a hybrid image-watermarking scheme based on discrete wavelet transform (DWT) and singular value decomposition (SVD) is proposed in this paper. In our approach, the watermark is not embedded directly on the wavelet coefficients but rather than on the elements of singular values of the cover image's DWT subbands. Experimental results are provided to illustrate that the proposed approach is able to withstand a variety of image-processing attacks.

An Online System of Multispectral Palmprint Verification

Abstract: Palmprint is a unique and reliable biometric characteristic with high usability. With the increasing demand of highly accurate and robust palmprint authentication system, multispectral imaging has been employed to acquire more discriminative information and increase the antispoof capability of palmprint. This paper presents an online multispectral palmprint system that could meet the requirement of real-time application. A data acquisition device is designed to capture the palmprint images under Blue, Green, Red, and near-infrared (NIR) illuminations in less than 1 s. A large multispectral palmprint database is then established to investigate the recognition performance of each spectral band. Our experimental results show that the red channel achieves the best result, whereas the Blue and Green channels have comparable performance but are slightly inferior to the NIR channel. After analyzing the extracted features from different bands, we propose a score level fusion scheme to integrate the multispectral information. The palmprint verification experiments demonstrated the superiority of multispectral fusion to each single spectrum, which results in both higher verification accuracy and antispoofing capability.

Determination of Dielectric Constant of Fabric Materials and Their Use as Substrates for Design and Development of Antennas for Wearable Applications

Abstract: A novel approach to measure the dielectric constant of fabric substrate materials used for the development of wearable antennas (also called textile antennas) is presented in this paper. The technique reported here is based on the resonance method and focused on the use of microstrip patch radiator, which contains fabric material as its substrate. The accurate value of the dielectric constant of the fabric material can easily be extracted from the measured resonant frequency of the patch radiator. The dielectric constant values of six fabric materials, including jeans cotton, polyester combined cotton, and polyester, have been determined by this way. As an extended objective of this paper, initial investigations are done to study the performance/behavioral characteristics of wearable antennas in the Bluetooth industrial, scientific, and medical band. Two of the six textile antenna structures, developed to meet out the primary objective of determining the dielectric constant of fabrics, are tested, and their performance characteristics, such as impedance bandwidth, gain, efficiency, etc., are measured. In addition, another Bluetooth antenna employing polyester fabric substrate is designed considering its measured accurate value of dielectric constant and subjected to radiation pattern measurements. In general, all the measured antennas yield very good results, fulfilling the requirements for practical applications, and in particular, the third fabric antenna utilizing the accurate value of the dielectric constant determined shows superior performance characteristics compared to others, indicating the correctness of our approach. Thus, the suitability of fabric substrate materials for the development of textile antennas with microstrip patch configuration is also well demonstrated.

Orientation Estimation Using a Quaternion-Based Indirect Kalman Filter With Adaptive Estimation of External Acceleration

Abstract: This paper is concerned with orientation estimation using inertial and magnetic sensors. A quaternion-based indirect Kalman filter structure is used. The magnetic sensor output is only used for yaw angle estimation using two-step measurement updates. External acceleration is estimated from the residual of the filter and compensated by increasing the measurement noise covariance. Using the direction information of external information, the proposed method prevents unnecessarily increasing the measurement noise covariance corresponding to the accelerometer output, which is not affected by external acceleration. Through numerical examples, the proposed method is verified.

Measurement and Defect Detection of the Weld Bead Based on Online Vision Inspection

Abstract: Weld bead inspection is important for high-quality welding. This paper summarizes our work on weld bead profile measurement, monitoring, and defect detection using a structured light-based vision inspection system. The configuration of the sensor is described and analyzed. In this configuration, the system presented in this paper can easily be calibrated. The image processing and extraction algorithms for laser profiles and feature points are presented. The dimensional parameters of the weld bead are measured, and the weld defects are detected during multilayer welding processes. Experiments using the vision inspection system were conducted with satisfactory results for online inspection.

Dynamic Phasor and Frequency Estimates Through Maximally Flat Differentiators

Abstract: Estimates of the dynamic phasor and its derivatives are obtained through the weighted least squares solution of a Taylor approximation using classical windows as weighting factors. This solution leads to differentiators with ideal frequency response around the fundamental frequency and to very low sidelobe level over the stopband, which implies low noise sensitivity. The differentiators are maximally flat in the interval centered at the fundamental frequency and have a linear phase response. Therefore, their estimates are free of amplitude and phase distortion and are obtained at once. No further patch is needed to improve their accuracy. Examples of dynamic phasor estimates are illustrated under transient conditions. Special emphasis is put on frequency measurements.

Image-Quality-Based Adaptive Face Recognition

Abstract: The accuracy of automated face recognition systems is greatly affected by intraclass variations between enrollment and identification stages. In particular, changes in lighting conditions is a major contributor to these variations. Common approaches to address the effects of varying lighting conditions include preprocessing face images to normalize intraclass variations and the use of illumination invariant face descriptors. Histogram equalization is a widely used technique in face recognition to normalize variations in illumination. However, normalizing well-lit face images could lead to a decrease in recognition accuracy. The multiresolution property of wavelet transforms is used in face recognition to extract facial feature descriptors at different scales and frequencies. The high-frequency wavelet subbands have shown to provide illumination-invariant face descriptors. However, the approximation wavelet subbands have shown to be a better feature representation for well-lit face images. Fusion of match scores from low- and high-frequency-based face representations have shown to improve recognition accuracy under varying lighting conditions. However, the selection of fusion parameters for different lighting conditions remains unsolved. Motivated by these observations, this paper presents adaptive approaches to face recognition to overcome the adverse effects of varying lighting conditions. Image quality, which is measured in terms of luminance distortion in comparison to a known reference image, will be used as the base for adapting the application of global and region illumination normalization procedures. Image quality is also used to adaptively select fusion parameters for wavelet-based multistream face recognition.

Instrument-Based Noncontact Doppler Radar Vital Sign Detection System Using Heterodyne Digital Quadrature Demodulation Architecture

Abstract: In this paper, we present a fast solution to build a Doppler radar system for noncontact vital sign detection (VSD) using instruments that are generally equipped in radio-frequency and communication laboratories. This paper demonstrates the feasibility of conducting research on VSD in ordinary radio-frequency laboratories. The system is designed with a heterodyne digital quadrature demodulation architecture that helps mitigate quadrature channel imbalance and eliminate the complicated dc offset calibration required for arctangent demodulation. Moreover, its tunable carrier frequency helps select different optimal frequencies for different human objects. Two sets of extensive experiments have been carried out in the laboratory environment with a self-designed 2.4-GHz patch antenna array and a 1-18-GHz broadband antenna. The test results are satisfactory: for a 0-dBm transmit power, the detection range can be extended to 2.5 m with accuracy higher than 80%. The system is also capable of detecting vital signs in the presence of different obstructions between the subject and the antenna.

Multilevel Thresholding for Image Segmentation Through an Improved Quantum-Behaved Particle Swarm Algorithm

Abstract: Multilevel thresholding is one of the most popular image segmentation techniques. Some of these are time-consuming algorithms. In this paper, by preserving the fast convergence rate of particle swarm optimization (PSO), the quantum-behaved PSO employing the cooperative method (CQPSO) is proposed to save computation time and to conquer the curse of dimensionality. Maximization of the measure of separability on the basis of between-classes variance method (often called the OTSU method), which is a popular thresholding technique, is employed to evaluate the performance of the proposed method. The experimental results show that, compared with the existing population-based thresholding methods, the proposed PSO algorithm gets more effective and efficient results. It also shortens the computation time of the traditional OTSU method. Therefore, it can be applied in complex image processing such as automatic target recognition.

Long-Duration Time-Resolved PIV to Study Unsteady Aerodynamics

Abstract: A time-resolved particle image velocimetry (PIV) system has been developed at the University of Western Ontario, London, ON, Canada, with long-recording-time capabilities This system is uniquely suited to the study of unsteady aerodynamics and hydrodynamics, such as avian aerodynamics or bluff-body oscillations Measurements have been made on an elongated bluff body through the initial build-up phase of flutter The possibilities to study this instability, which was responsible for the collapse of the Tacoma Narrows Bridge, are significantly broadened by the use of this system The long-time recording capability of the system allows for novel results since it yields data that are spatially and temporally resolved over a long record length The buildup of flutter is shown to exhibit complex dynamics that are heavily influenced by the flow-induced motion of the body Features of the wake turbulence as a function of time are presented and shown to substantially vary

A New Neural-Network-Based Fault Diagnosis Approach for Analog Circuits by Using Kurtosis and Entropy as a Preprocessor

Abstract: This paper presents a new fault diagnosis method for analog circuits. The proposed method extracts the original signals from the output terminals of the circuits under test (CUTs) by a data acquisition board and finds the kurtoses and entropies of the signals, which are used to measure the high-order statistics of the signals. The entropies and kurtoses are then fed to a neural network as inputs for further fault classification. The proposed method can detect and identify faulty components in an analog circuit by analyzing its output signal with high accuracy and is suitable for nonlinear circuits. Preprocessing based on the kurtosis and entropy of signals for the neural network classifier simplifies the network architecture, reduces the training time, and improves the performance of the network. The results from our examples showed that the trochoid of the entropies and kurtoses is unique when the faulty component's value varies from zero to infinity; thus, we can correctly identify the faulty components when the responses do not overlap. Applying this method for three linear and nonlinear circuits, the average accuracy of the achieved fault recognition is more than 99%, although there are some overlapping data when tolerance is considered. Moreover, all the trochoids converge to one point when the faulty component is open-circuited, and thus, the method can classify not only soft faults but also hard faults.

Signal Transmission by Galvanic Coupling Through the Human Body

Abstract: Galvanic coupling is a promising approach for wireless intrabody data transmission between sensors. Using the human body as a transmission medium for electrical signals becomes a novel data communication technique in biomedical monitoring systems. In this paper, special attention is given to the coupling of the current into the human body. Safety requirements have to be fulfilled, and optimal signal coupling is of essence. Therefore, different electrodes are compared. A test system offers up to 1 mA contact current modulated in the frequency range of 10 kHz to 1 MHz. The injected current is up to 20 times below the maximum allowed contact current. Such a low-current approach enables data communication that is more energy saving than other wireless technologies.

An Adaptive Sampling Algorithm for Effective Energy Management in Wireless Sensor Networks With Energy-Hungry Sensors

Abstract: Energy conservation techniques for wireless sensor networks generally assume that data acquisition and processing have energy consumption that is significantly lower than that of communication. Unfortunately, this assumption does not hold in a number of practical applications, where sensors may consume even more energy than the radio. In this context, effective energy management should include policies for an efficient utilization of the sensors, which become one of the main components that affect the network lifetime. In this paper, we propose an adaptive sampling algorithm that estimates online the optimal sampling frequencies for sensors. This approach, which requires the design of adaptive measurement systems, minimizes the energy consumption of the sensors and, incidentally, that of the radio while maintaining a very high accuracy of collected data. As a case study, we considered a sensor for snow-monitoring applications. Simulation experiments have shown that the suggested adaptive algorithm can reduce the number of acquired samples up to 79% with respect to a traditional fixed-rate approach. We have also found that it can perform similar to a fixed-rate scheme where the sampling frequency is known in advance.

Design of a Novel Efficient Human–Computer Interface: An Electrooculagram Based Virtual Keyboard

Abstract: The aim of this paper is to present the design and application of an electrooculogram (EOG) based on an efficient human-computer interface (HCI). Establishing an alternative channel without speaking and hand movements is important in increasing the quality of life for the handicapped. EOG-based systems are more efficient than electroencephalogram (EEG)-based systems in some cases. By using a realized virtual keyboard, it is possible to notify in writing the needs of the patient in a relatively short time. Considering the biopotential measurement pitfalls, the novel EOG-based HCI system allows people to successfully communicate with their environment by using only eye movements. Classifying horizontal and vertical EOG channel signals in an efficient interface is realized in this study. The new system is microcontroller based, with a common-mode rejection ratio of 88 dB, an electronic noise of 0.6 μV (p-p), and a sampling rate of 176 Hz. The nearest neighborhood algorithm is used to classify the signals, and the classification performance is 95%. The novel EOG-based HCI system allows people to successfully and economically communicate with their environment by using only eye movements.

Wireless Readout of Passive LC Sensors

Abstract: This paper reports simple yet precise equations for automated wireless measurement of the resonance frequency, Q-factor, and coupling coefficient of inductively coupled passive resonant LC circuits. This allows remote sensing of all physical and chemical quantities that can be measured with capacitance transducers. Formerly reported front-end circuit concepts for wireless sensor readout, i.e., phase dip measurement and the dip meter, are subsequently discussed. It is shown that, due to fundamental system limitations, the formerly reported circuit concepts are not applicable if the distance between the sensor and the readout electronic circuit becomes too small, resulting in large coupling coefficients. Therefore, we present an improved concept for an analog front-end circuit of the readout system that overcomes these limitations and hence allows wireless sensor readout under a wider range of operating distances.

Quantitative Permittivity Measurements of Nanoliter Liquid Volumes in Microfluidic Channels to 40 GHz

Abstract: We describe the design, fabrication, and evaluation of a new on-wafer measurement platform for the rapid and quantitative determination of the complex permittivity of nanoliter fluid volumes over the continuous frequency range from 45 MHz to 40 GHz. Our measurement platform integrates micrometer-scale poly(dimethylsiloxane) (PDMS)-based microfluidic channels with high-frequency coplanar waveguide (CPW) transmission lines to accurately place small fluid volumes at well-defined locations within planar measurement structures. We applied new on-wafer calibration techniques to accurately determine the scattering parameters of our integrated devices, and we developed a transmission-line model to extract the distributed circuit parameters of the fluid-loaded transmission line segment from the response of the overall test structure. All the necessary model parameters were experimentally determined directly from a single set of measurements without requiring a reference fluid of known permittivity. We extracted the complex permittivity of the fluid under test from the distributed capacitance and conductance per unit length of the fluid-loaded transmission line segment using finite-element analysis of the transmission line cross section. Our measurements show excellent agreement with bulk fluid permittivity determinations for methanol at room temperature and yield consistent results for the extracted fluid permittivity for the same microfluidic channel embedded in multiple CPW transmission lines of different dimensions.

Detection of Motor Bearing Outer Raceway Defect by Wavelet Packet Transformed Motor Current Signature Analysis

Abstract: Motor current signature analysis (MCSA) is a method of sampling the running current through a data logger at high sampling speed, followed by using mathematical tools such as fast Fourier transform (FFT) to identify relevant motor signature changes in the frequency spectrum for motor fault identification. Although there are numerous types of motor fault, research conducted by Electric Power Research Institute (EPRI) indicated that motor bearing fault accounted for more than 40% of all types of motor fault. The main aim of this paper is to evaluate the use of MCSA for detecting bearing outer raceway defect. Stage-by-stage experimental verification shows that the method of MCSA is effective in detecting bearing fault with the use of wavelet packet transformation (WPT). In addition, a novel linear application of linear regression for wavelet data analysis is applied and presented in this paper.

Personal Navigation via High-Resolution Gait-Corrected Inertial Measurement Units

Abstract: In this paper, a personal micronavigation system that uses high-resolution gait-corrected inertial measurement units is presented. The goal of this paper is to develop a navigation system that uses secondary inertial variables, such as velocity, to enable long-term precise navigation in the absence of Global Positioning System (GPS) and beacon signals. In this scheme, measured zero-velocity duration from the ground reaction sensors is used to reset the accumulated integration errors from accelerometers and gyroscopes in position calculation. With the described system, an average position error of 4 m is achieved at the end of half-hour walks.

Nonlinear System Identification Using Exponential Swept-Sine Signal

Abstract: In this paper, we propose a method for nonlinear system (NLS) identification using a swept-sine input signal and based on nonlinear convolution. The method uses a nonlinear model, namely, the nonparametric generalized polynomial Hammerstein model made of power series associated with linear filters. Simulation results show that the method identifies the nonlinear model of the system under test and estimates the linear filters of the unknown NLS. The method has also been tested on a real-world system: an audio limiter. Once the nonlinear model of the limiter is identified, a test signal can be regenerated to compare the outputs of both the real-world system and its nonlinear model. The results show good agreement between both model-based and real-world system outputs.

A Triaxial Accelerometer Calibration Method Using a Mathematical Model

Abstract: This paper presents a new triaxial accelerometer calibration method using a mathematical model of six calibration parameters: three gain factors and three biases. The fundamental principle of the proposed calibration method is that the sum of the triaxial accelerometer outputs is equal to the gravity vector when the accelerometer is stationary. The proposed method requires the triaxial accelerometer to be placed in six different tilt angles to estimate the six calibration parameters. Since the mathematical model of the calibration parameters is nonlinear, an iterative method is used. The results are verified via simulations by comparing the estimated gain factors and biases with the true gain factors and biases. The simulation results confirm that the proposed method is applicable in extreme cases where the gain factor is 1000 V/(m/s2) and the bias is ±100 V, as well as the cases where the gain factor is 0.001 V/(m/s2) and the bias is 0 V. The proposed calibration method is also experimentally tested with two different triaxial accelerometers, and the results are validated using a mechanical inclinometer. The experimental results show that the proposed method can accurately estimate gain factors and biases even when the initial guesses are not close to the true values. In addition, the proposed method has a low computational cost because the calculation is simple, and the iterative method usually converges within three iteration steps. The error sources of the experiments are discussed in this paper.

Accurate Doppler Radar Noncontact Vital Sign Detection Using the RELAX Algorithm

Abstract: We consider using a Doppler radar for accurate noncontact vital sign detection. The Doppler radar first captures and downconverts the wireless signal that is phase modulated by the physiological movements, and then identifies the human heartbeat and respiration rates by processing the baseband signal. When nonlinear Doppler phase modulation is employed to monitor vital signs without contact, one of the challenges that we encounter is the presence of undesired harmonic terms and intermodulations other than the sinusoids of interest. A spectral estimation algorithm is needed to accurately estimate the sinusoidal frequencies before identifying the heartbeat and respiration rates. The conventional periodogram cannot reliably separate the rich sinusoidal components since it suffers from smearing and leakage problems, particularly for the case of limited data samples. A parametric and cyclic optimization approach, referred to as the RELAX algorithm, is instead suggested to mitigate these difficulties. Both simulated and experimental results are provided to validate the superiority of using the RELAX algorithm for accurate noncontact vital sign detection.

A Smart ECG Measurement System Based on Web-Service-Oriented Architecture for Telemedicine Applications

Abstract: The opportunity for cardiac patients to have constantly monitored their health state at home is now possible by means of telemedicine applications. In fact, today, portable and simple-to-use devices allow one to get preliminary domestic diagnoses of the heart status. In this paper, the authors present an original ECG measurement system based on web-service-oriented architecture to monitor the heart health of cardiac patients. The projected device is a smart patient-adaptive system able to provide personalized diagnoses by using personal data and clinical history of the monitored patient. In the presence of a pathology occurrence, the system is able to call the emergency service for assistance. An ECG sensor has the task to acquire, condition, and sample the heart electrical impulses, whereas a personal digital assistant (PDA) performs the diagnosis according to the measurement uncertainty and, in case of a critical situation, calls the medical staff. The system has two removable and updatable memory devices: the first memory device stores the clinical and personal data of the patient, and the second memory device stores information on the metrological status of the measurement system. This way, according to the personal data and historical information of the patient, the measurement system adapts itself by selecting the best fitted ECG model as a reference to configure the computing algorithm. Further information on the measurement uncertainty is used to qualify the reliability of the final clinical response to reduce the occurrence of a faulty diagnosis. Through the PDA graphic interface, the user can display his personal data, observe the graph of his ECG signal, and read diagnosis information with the relative reliability level. Moreover, the patient can choose to print his ECG graph through a Bluetooth printer or to send it to a specialist by a General Packet Radio Service (GPRS) modem.

Pigment Melanin: Pattern for Iris Recognition

Abstract: Recognition of iris based on visible light (VL) imaging is a difficult problem because of the light reflection from the cornea. Nonetheless, pigment melanin provides a rich feature source in VL, which is unavailable in near-infrared (NIR) imaging. This is due to the biological spectroscopy of eumelanin, a chemical not stimulated in NIR. In this case, a plausible solution to observe such patterns may be provided by an adaptive procedure using a variational technique on the image histogram. To describe the patterns, a shape analysis method is used to derive the feature code for each subject. An important question is how the melanin patterns, which are extracted from VL, are independent of the iris texture in NIR. With this question in mind, the present investigation proposes fusion of features extracted from NIR and VL to boost recognition performance. We have collected our own database (UTIRIS), consisting of both NIR and VL images of 158 eyes of 79 individuals. This investigation demonstrates that the proposed algorithm is highly sensitive to the patterns of chromophores and improves the iris recognition rate.

Joint-Angle Measurement Using Accelerometers and Gyroscopes—A Survey

Abstract: This paper presents an analysis of rigid-body joint-angle measurement based on microelectromechanical-system (MEMS) biaxial accelerometers and uniaxial gyroscopes. In comparison to conventional magnetic and optical joint angular sensors, this new inertial sensing principle has the advantages of flexible installation and true contactless sensing. This paper focuses on the comparison of four different inertial-sensor combination methods that are reported in reference papers and utilizes the theory of rigid-body kinematics to explain and analyze their advantages and weaknesses. Experiments have also been conducted to further verify and strengthen the arguments put forward in the analysis. All experiments in this paper took place on a custom-built rigid-body robot arm model that can be manipulated by hand. Sensor calibration and accelerometer alignment issues are also described, and their details are discussed. The experiment results presented in this paper show significant differences with reference to the achieved angular accuracy for various situations when using the four different sensor combination methods. In some cases, the angular error based on one method is more than 0.04 rad, while that from another method is within ±0.005 rad. The noise levels of angular readings from different methods are also experimentally compared and analyzed. The conclusion drawn serves to guide readers toward a suitable method for their particular application.

Predictive Iterated Kalman Filter for INS/GPS Integration and Its Application to SAR Motion Compensation

Abstract: This paper deals with the problem of state estimation for the integration of an inertial navigation system (INS) and Global Positioning System (GPS). For a nonlinear system that has the model error and white Gaussian noise, a predictive filter (PF) is used to estimate the model error, and based on this, a modified iterated extended Kalman filter (IEKF) is proposed and is called predictive iterated Kalman filter (PIKF). The basic idea of the PIKF is to compensate the state estimate by the estimated model error. An INS/GPS integration system is implemented using the PIKF and applied to synthetic aperture radar (SAR) motion compensation. Through flight tests, it is shown that the PIKF has an obvious accuracy advantage over the IEKF and unscented Kalman filter (UKF) in velocity.

Constructing Online Testable Circuits Using Reversible Logic

Abstract: With the advent of nanometer technology, circuits are more prone to transient faults that can occur during its operation. Of the different types of transient faults reported in the literature, the single-event upset (SEU) is prominent. Traditional techniques such as triple-modular redundancy (TMR) consume large area and power. Reversible logic has been gaining interest in the recent past due to its less heat dissipation characteristics. This paper proposes the following: 1) a novel universal reversible logic gate (URG) and a set of basic sequential elements that could be used for building reversible sequential circuits, with 25% less garbage than the best reported in the literature; (2) a reversible gate that can mimic the functionality of a lookup table (LUT) that can be used to construct a reversible field-programmable gate array (FPGA); and (3) automatic conversion of any given reversible circuit into an online testable circuit that can detect online any single-bit errors, including soft errors in the logic blocks, using theoretically proved minimum garbage, which is significantly lesser than the best reported in the literature.

AR-REHAB: An Augmented Reality Framework for Poststroke-Patient Rehabilitation

Abstract: This paper proposes a novel approach based on augmented-reality (AR) technologies that can increase a stroke-patient's involvement in the rehabilitation process. The approach takes advantage of virtual-reality technologies and provides natural-force interaction with the daily environment by adopting a tangible-object concept. In our framework, the patient manipulates during the treatment session a tangible object that is tracked to measure her/his performance without the direct supervision of an occupational therapist. We called this framework AR-based REHABilitation. In this paper, we introduce the core architecture of the framework and its subsystems that provide more convenience to patients and therapists. We also present two exercises, a shelf exercise and a cup exercise, as examples and perform preliminary usability study. In addition, we introduce assessment measurements such as task-completion time, compactness of task, and speed of hand movement by capturing the patients' hand movements with the tangible object.

Classification of Black Tea Taste and Correlation With Tea Taster's Mark Using Voltammetric Electronic Tongue

Abstract: Tea quality assessment is a difficult task because of the presence of innumerable compounds and their diverse contribution to tea quality. As a result, instrumental evaluation of tea quality is not practiced in the industry, and tea samples are assessed by experienced tea tasters. There had been a very few reports where an electronic tongue has been used for the discrimination of taste of tea samples. In this paper, a voltammetric electronic tongue instrument is described, which can declare tea-taster-like scores for black tea. The electronic tongue is based on the principle of pulse voltammetry and consists of an array of five working electrodes along with a counter and a reference electrode. The five working electrodes are of gold, iridium, palladium, platinum, and rhodium. The voltage equivalent of the output current from between the working electrode and the counterelectrode generated out of the tea liquor when excited with pulse voltage between the working electrode and the reference electrode has been considered for data analysis. First, the sampled data have been compressed using discrete wavelet transform (DWT) and are then processed using principal component analysis (PCA) and linear discriminant analysis (LDA) for visualization of underlying clusters. Finally, different pattern recognition models based on neural networks are investigated to carry out a correlation study with the tea tasters' score of five different grades of black tea samples obtained from a tea garden in India. The efficacy of the classifier has been established using tenfold cross-validation methods.

Reducing Drifts in the Inertial Measurements of Wrist and Elbow Positions

Abstract: In this paper, we present an inertial-sensor-based monitoring system for measuring the movement of human upper limbs. Two wearable inertial sensors are placed near the wrist and elbow joints, respectively. The measurement drift in segment orientation is dramatically reduced after a Kalman filter is applied to estimate inclinations using accelerations and turning rates from gyroscopes. Using premeasured lengths of the upper and lower arms, we compute the position of the wrist and elbow joints via a proposed kinematic model. Experimental results demonstrate that this new motion capture system, in comparison to an optical motion tracker, possesses an RMS position error of less than 0.009 m, with a drift of less than 0.005 ms-1 in five daily activities. In addition, the RMS angle error is less than 3°. This indicates that the proposed approach has performed well in terms of accuracy and reliability.