Showing papers presented at "Virtual Environments, Human-Computer Interfaces and Measurement Systems in 2012"

Implementation of SSVEP based BCI with Emotiv EPOC

Abstract: In recent years, steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) has received much attentions. However, most SSVEP based BCI devices are not portable and have high price, which are not suitable to be used for clinical and commercial purpose. Thanks to the low cost and portable Emotiv EPOC, it brings BCI into daily life. In this paper, SSVEP based BCI through Emotiv EPOC is implemented. BCI 2000 is employed to connect Emotiv EPOC and Matlab to implement the online system. The online experiments have the accuracy of 95.83±3.59 %, information transfer rate (ITR) with 22.85±1.85 bits/min and detection duration of 5.25±2.14 sec.

A new image quality metric based on human visual system

Abstract: In this paper we propose a new image quality metric based on human visual system (HVS) called PSNR-JND. This metric is based on the values of DCT coefficients of 8×8 pixel block of an image. In particular, it assumes the same formula as the PSNR (Peak Signal-to-Noise Ratio), but it computes the MSE (Mean Squared Error) on the perceptual error calculated by dividing the DCT error by the minimum DCT coefficient able to produce a visible signal called also JND (Just Noticeable Difference) or differential threshold. The differential thresholds were experimentally calculated in order to maximise the correlation between the evaluations of the metric and the human visual system. The metric PSNR-JND has outperformed other reference based quality metrics and demonstrated high correlation with the results of subjective experiments of the database TID2008.

Visual identification of medicine boxes using features matching

Abstract: This paper proposes to use visual features matching in the identification of medicine boxes for visually impaired people. We use a camera device, available in several popular devices such as computers, televisions and cell phones, to identify relevant features on medicine box. After box detection, audio files are played to inform about dosage, indications and contraindications of the medication. Making use of this vision system can help many visually impaired people to take the right medicine at the time indicated in advance by the doctor. Experiments with 15 blindfolded volunteers demonstrated that 93% of them believes that the system was useful or very useful to identify the medicine boxes.

Fingerprint image segmentation based on a combined method

Abstract: Fingerprint image segmentation is part of pre-processing in fingerprint image recognition system. It has a critical effect to the fingerprint image recognition system. A combined method segmentation method is proposed in this article. We use the orientation field information combined with statistical characteristics of gray. The fingerprint image realized the second segmentation with the method proposed in this paper. The experimental results show that the method used in this paper achieves a good effect.

EMG-muscle force estimation model based on back-propagation neural network

Abstract: Electromyography (EMG) signal precede many information about muscle activity, which can be used to analyze muscle functions, such as muscle forces. Muscle forces estimation is important for orthopedists, bio-mechanists, and physical therapists because of joint contact forces.

Virtual environment for 3-D synthetic fingerprints

Abstract: Contactless biometric recognition performed using three-dimensional fingerprint models has the advantages of reducing problems related to the deformations of the skin, dust on the sensor, and spoofing of latent fingerprints. Moreover, the fingerprint area usable for the recognition is wider than the one captured by traditional contact-based acquisition techniques.

On the efficiency issues of virtual keyboard design

Abstract: Virtual keyboards are useful tools, which ease effortless entry of textual data and enable typing with alternative input hardware such as a single switch. Early virtual keyboards are designed similar to physical keyboards in terms of appearance. Since a physical keyboard is designed for tactile-use; the usability of the first virtual keyboards comes up short in utilization with pointing devices. For this reason, more useful virtual keyboards are proposed with improvements in modal and functional properties. In this study, we examine a couple of design issues for virtual keyboards to provide their efficient utilization with pointing devices. We analyze the effects of visual key layout to the performance of virtual keyboards in connection with the statistical properties of the target language's vocabulary. We also propose a virtual keyboard design for a comfortable text entry experience based on our observations.

Neurofeedback for the treatment of schizophrenia: Case study

Abstract: The paper presents a case report of the therapy by neurofeedback training of a chronic female schizophrenia outpatient. The purpose of the neurofeedback training was to enhance cognition, memory and behavioral performance. We used an intensive approach. All the training sessions were performed during 4 consecutive days. The results showed that the patient learnt to increase individual alpha amplitude and simultaneously decrease beta2 (20–30 Hz) amplitude at P4 site during active state over sessions. The individual alpha increased 74.73% and beta2 decreased 13.73%. The short term memory was enhanced after training. Her mood had positive change and her speech was much clearer than before. She started to associate the meaning of her life and illness. These results support that neurofeedback is not only a feasible therapy for schizophrenia but also positive results could be obtained using a much more intensive training sessions than the one reported in the literature.

A hybrid brain-computer interface combining the EEG and NIRS

Abstract: Compared to the conventional brain-computer interface (BCI) system, the hybrid BCI provides a more efficient way for the communication between the brain and the external device The Electroencephalography (EEG) signal and the change of oxygenation in the brain are two prevailing approaches used in the BCI However, single physiological signal couldn't provide enough information for a satisfied BCI This paper proposes a hybrid BCI system based on the combination of the EEG signal and the cerebral blood oxygen changes measured by the near-infrared spectroscopy system (NIRS) to detect the state of motor imagery (MI) The result shows that the average recognition rate can achieve above 7504% and the highest rate 9111%, which are higher than when only using EEG or NIRS It suggests that the proposed hybrid BCI system has a good performance in the combination of these two different signals Further investigation may help develop better BCIs with high accuracy and significant efficiency

Simultaneous quantitative detection of tetracyclines derivatives by raman spectroscopy

Abstract: Our work was to develop a methodology to qualitatively and quantitatively detect tetracyclines (TCs) derivatives, such as doxycycline (DOTC) and oxytetracycline (OTC). The Raman spectra region of 500–1800 cm−1 reveals distinctive spectra features of TCs. We applied principal component analysis (PCA) to investigate the antibiotics composition from Raman spectra. The capability of the model was evaluated by partial least square analysis (PLS) with a leave-one-out-cross-validation method. The result shows the feasibility of simultaneous quantitative detection of tetracycline derivatives by portable Raman spectroscopy.

Camshift algorithm -based moving target recognition and tracking system

Abstract: In order to achieve intelligent feedback tracking of moving target, an embedded system for recognition and tracking of moving target based on the DSP chip and Camshift algorithm was designed. The system uses frame difference method to recognize the moving target and Camshift algorithm to track the moving target. Controls of the PTZ are used to track its moving path. The system demonstrates good performance in effectiveness, real-time response and strong anti-interference ability as tracking a single moving object.

Design of a novel mobile assistive robot with haptic interaction

Abstract: This paper presents a prototype of noval assistive robotic system, for which the user can interact with a mobile robot using a haptic interface, for senior and disabled people. The system consists of a nonholonomic PeopleBot mobile robot and a Phantom Omni haptic interface. Several technical problems related to the system are addressed and solved. Specifically, a nonlinear tracking algorithm is developed for the robot to follow the user. To preserve the safety operation of the haptic device, a safety control algorithm is applied. Besides, a simple haptic rendering algorithm is designed to generate the haptic feedback based on the position error. Experiments show that the user can guide the movement of the robot quite safely and smoothly using the haptic interface.

A task ontology model for domain independent dialogue management

Abstract: Dialogue systems have been a rapidly growing area in the field of human computer interaction They can be applied in various fields, such as education, business and healthcare Due to its complexity, the design and development of a dialogue system is time consuming and costly It is highly desirable for a generic dialogue system, especially dialogue management that is independent of specific domains Methods for domain independent dialogue systems have been proposed in previous research, however each of them has its own limitations This paper presents a new approach, a task ontology model for domain independent dialogue management An abstract task ontology is developed and based on that a generic dialogue manager is created Knowledge about a specific task is modeled in its task ontology and retrieved by an ontology reasoning component situated in the dialogue manager Thus the dialogue system based on this model is task or domain independent The dialogue system has been experimented with two different tutorial tasks: the book borrowing and the online train ticket booking The results indicate that the dialogue system can be readily applied to tasks from different domains This paper has implications on future research and development of domain independent dialogue systems and its application in tutoring and training in virtual environments It also contributes to the knowledge sharing and reuse of human computer interfaces

Research on mental fatigue based on entropy changes in space environment

Abstract: This paper detects mental fatigue based on entropy changes in imitating space environment. We calculated changes of sample entropy and power spectrum entropy of fNIR (Functional near-infrared spectroscopy) at normal status and fatigue status, the results indicate that the sample entropy and the power spectrum entropy decreases at fatigue status in imitating space environment comparing to normal status. We proposed the mental fatigue detection method based entropy change of fNIR in space environment and the method is verified by daily routine fatigue experiment.The methodology was validated using imitating space task mental fatigue induction model. The mental fatigue detection methodology based on cw-fNIR (continuous wave-fNIR), which adopts integrate entropies as feature parameters other than concentration changes of hemodynamic indexes can overcome the disadvantages of cw-fNIR, improve convenience of measurement and contract measurement period. It can be concluded that mental fatigue can be reliably and noninvasively detected by applying sample entropy and power spectrum entropy of fNIR. Sample entropy reflects complex of a time sequence, it can measure the probability of generating new patterns of a signal. Power spectrum entropy reflects complex of a signal from frequent domain. The decline of integrate entropies shows that brain is inactive. Through the aforementioned applications it is remarked that integrate entropy can be considered as a very promising and useful tool towards the non-invasive understanding of mental fatigue.

Analysis of knee joint kinematics during walking in patients with cerebral palsy through human motion capture and gait model-based measurement

Abstract: Cerebral palsy is leading cause of physical disability in childhood This interferes with normal ambulation Rectus femoris muscle spasticity has been reported to be a cause of stiff knee gait in the patients with cerebral palsy This study aimed to analyse changes in sagittal knee joint kinematic parameters following botulinum toxin injection to the rectus femoris Fifteen patients were included in the study A Vicon Motion capture system with Plug-in-Gait model was used for the pre- and post-treatment gait analysis of knee joint angles as well as knee joint flexion velocity The results from statistical analysis revealed that there were no significant differences in the knee joint range of motion as well as velocity of knee joint flexion in the pre-swing and early swing phase of gait cycle Although statistical results did not show any significant improvement, it was noted that there was variation in the outcomes for individual patients, with some showing improvements

A portable in-vivo device of friction force and torque measurement for vascular surgery

Abstract: In-vivo measurement of force signals between surgical tool and human tissues is an important research topic in high-fidelity surgical simulations. In this paper, we introduce a portable device for real-time in-vivo measurement of friction force and torque during vascular surgery operations. To measure multi-region contacts between the guide wire and the vascular wall, two portable sensor modules are mounted on surgeon's fingertip of thumb and index finger. Based on relative motion between an inner shaft and an outer socket, the sensor module can detect in real-time one-dimensional pushing or retracting resistance force and one-dimensional twisting resistance torque between the guide wire and the vascular wall. The sensor module is based on a modular design of three off-the-shelf one-dimensional force sensors, which provides a flexible solution to realize compact design. Preliminary experiments indicate the sensor modules can provide a portable solution for real-time measuring the force and torque signals during vascular surgery operations.

Arm movement recognition for flag signaling with Kinect sensor

Abstract: This paper propose a simple recognition method for arm movement in Japanese flag semaphore. The method consists of three main process, detection of an arm position, discrimination of a semaphore form to the detected one, and identification of a Japanese Katakana character from a sequence of semaphore forms. Based on the method, an experimental system for flag signaling was implemented by Kinect sensor device and OpenNI/NITE software library. A preliminary experiment indicated that the method might be usable for beginner to learn the flag signaling. But it was also found that the method should be improved in some misrecognition.

Study on virtual coordinate measuring machine based on augmented virtuality

Abstract: In this paper, a new method for constructing a virtual coordinate measuring machine (VCMM) is proposed based on augmented virtuality. The VCMM consists of two main parts: hardware and software. An operation-simulating mechanism and a binocular-stereo vision system compose the hardware, which are used to the extract operation information of an operator. There are four modules in software, including hand-segmentation, motion-analysis, model-render and augmented-virtual module, which are used to integrate the physical information into the VCMM environment. To verify the proposed VCMM, experiments are conducted and the result shows it feasible and reliable.

A new automatic segmentation method for lung tumor based on SUV threshold on 18 F-FDG PET images

Abstract: Heart metabolizes more glucose and “light up” more brightly on PET lung images than other healthy or normal tissues and organs because of its constant pumping of blood and accumulation of radiotracer concentration. It affects the results of lung tumor detection and segmentation using the thresholding methods, which is the most used methodcurrently. Standardized uptake value (SUV) on 18F-FDG PET images isan important indicator to differentiate malignant from benign tumors, and has been applied in tumor volume segmentation. However, some methods based on SUV have been shown unable to distinguish regions between tumor and heart. In this paper, we present a novel segmentation method based on SUV to extract the tumor alone from the background ofhealthy tissues and image noise. Firstly we use SUV to enhance the images and then apply an iterative thresholding method to get a coarse result. Secondly we label the fragmented parts and fuse them with the SUV distribution image, and then calculate the SUV mean for each part. Finally we use the maximum of SUV mean to locate the tumor region. The proposed method is compared with current segmentation methods on PET images. The results show that the new method is able to detect tumors in the background of heart effectively, and can potentially be used as a toolof automatic segmenting tumor from 18F-FDG PET images.

Digital spelling BCI based on visual-auditory associate stimulation

Abstract: Brain-computer interfaces (BCI) provide direct and non-muscular communication methods for the people with severe motor impairments. Event-related potentials (ERPs) as efficient modals are commonly used in some of the BCI systems, including visual stimulus, auditory stimulus as well as tactile stimulus. In this experiment, the corresponding Chinese pronunciations were inserted into the visual Oddball series of 1–9 numbers to carry out the cross-sense stimuli of BCI. The experimental data analysis result proves that the P300 components produced by visual-auditory associate stimulation have higher amplitudes and shorter latencies than those produced by visual-only stimulus. For further analysis the constrained independent component analysis (cICA) method was applied when extracting the signal features of ERP and the support vector machine (SVM) method was used to BCI classification. Result proves that the ERPs produced by visual-auditory associate stimulation modal have better recognition efficiency than those in visual-only stimulation. It can relevant the capacity of information alteration in BCI and is worth to do more studies.

iFeel6-BH1500: A large-scale 6-DOF haptic device

Abstract: It is a challenge to design a haptic device with a large workspace, high stiffness while maintain a good back drivability. In this paper, we present a large-scale haptic device iFeel6- BH1500, which is based on a cable-driven parallel mechanism and can achieve 6 dimensional force feedback by controlling the tension of eight cables. The components and working principle of the device is presented, followed by the analysis of the statics and kinematic models. Moreover, a method of friction compensation is proposed to decrease the tension error for achieving good back drivability. The measurement results show that the tension error of the cables is greatly reduced by using the friction compensation. Finally, two demos for the application of iFeel6- BH1500 are presented: virtual assembly of aircraft engine and virtual shooting for entertainment. The demos show the proposed device can provide large workspace, high stiffness and good back drivability.

Nonpassive teleoperation systems with time varying communication delay

Abstract: We address the stability problem for a class of nonpassive teleoperators in the presence of the symmetrical and unsymmetrical time varying transmission delay. The design combines local velocity and nonlinear adaptive terms with the delayed position signals. Nonlinear adaptive terms for master and slave devices are used to cope with the unknown uncertainties that appeared into closed-loop systems. The Lyapunov-Krasovskii-like functionals are used to derive stability condition for the closed-loop systems under time varying communication delay. These condition allows the designer to estimate the control gains in order to achieve bounded position and velocity of the master and slave systems. Finally, simulation is conducted to demonstrate the validity of the proposed design for real-time teleoperation.

Extraction of microsphere size from diffraction images with an STFT method

Abstract: This paper presents an image analysis method based on a short-time-Fourier-transform (STFT) for extracting the size of polystyrene microspheres with different nominal diameters from diffraction images obtained with a newly developed diffraction imaging flow cytometer. The center frequency of STFT and its relation with the image row index are explored to extract the microspheres' diameter. We have shown that the STFT based method provides a new and rapid method for determination of microsphere sizes and their distribution using the diffraction imaging flow cytometer.

Performance optimisation of mobile robots in dynamic environments

Abstract: This paper presents a robotic simulation system, that combines task allocation and motion planning of multiple mobile robots, for performance optimisation in dynamic environments. While task allocation assigns jobs to robots, motion planning generates routes for robots to execute the assigned jobs. Task allocation and motion planning together play a pivotal role in optimisation of robot team performance. These two issues become more challenging when there are often operational uncertainties in dynamic environments. We address these issues by proposing an auction-based closed-loop module for task allocation and a bio-inspired intelligent module for motion planning to optimise robot team performance in dynamic environments. The task allocation module is characterised by a closed-loop bid adjustment mechanism to improve the bid accuracy even in light of stochastic disturbances. The motion planning module is bio-inspired intelligent in that it features detection of imminent neighbours and responsiveness of virtual force navigation in dynamic traffic conditions. Simulations show that the proposed system is a practical tool to optimise the operations by a team of robots in dynamic environments.

Research on auditory BCI based on wavelet transform

Abstract: It is significant that auditory brain-computer interface (BCI) technology can provide a means of non-muscular communication. For most severely disabled people, limitations in eye mobility or visual acuity may necessitate auditory BCI systems. The auditory BCI based on three-stimulus paradigm was studied to obtain a binary decision in this paper. Coherence average and one-dimensional discrete wavelet transform were used to reduce noise and improved signal-to-noise ratio, and extract P300 feature in low-frequency signals. The target and non-target stimuli were classified by support vector machines. The results show that three-stimulus paradigm could elicit P300 potential and an auditory P300 BCI is feasible. The identification correct rates achieved more than 80%, which can be comparable to the BCI based on visual.

Error analysis in parallel-axes binocular stereoscopic measurement system caused by the calibrated parameters

Abstract: This paper focuses on the errors in parallel-axes binocular stereoscopic measurement system caused by the calibrated parameters. The Monte-Carlo method was used in simulating and analyzing the errors. In the view of complex algebraic expression of 3D point from the positioning model of binocular vision, according to the independence of imaging-model-parameters, a method of single-parameter analysis of positioning errors was proposed to facilitate the simulation. The simulation results and experiments show that among the intrinsic parameters, the calibration error of the principle point (u0, v0) has a significant influence on the positioning accuracy on the X and Y direction, and the calibration error of focus f u has an obvious influence on the positioning accuracy on the Z direction. On the other hand, among the extrinsic parameters, both the rotation angle β and the baseline t1 have a visible influence on the positioning accuracies accuracy on all the three directions. The conclusion can be taken as a reference for the design and calibration of binocular vision system.

A new targets matching method based on epipolar geometry

Abstract: In this paper, a multi-targets matching method to the epipolar line is proposed. The method, which is combined with a bundle of adjustment processes, is based on the epipolar plane, as opposed to method which is based on the 2D intersection of the epipolar line. During the procedure, the photogrammetric network is refined and strengthened as matching targets are gradually identified and introduced. An epipolar plane is defined such that the cause of such ambiguities can be eliminated by restricting the viewpoints used in the matching process. The new method has been found to be valid in the general case, and appears particularly suited to accurate industrial measurement.

Movement and deformation of virtual object based on argument passing method

Abstract: Force feedback is a good opportunity for virtual reality technology(VRT) into the field of engineering simulation. haptic device point (HIP) is the common tool used for interacting with the virtual objects, while the mass-spring model consistent with which does not have good scalability, and cannot guarantee the necessary accuracy. By substituting mass-spring model with finite element model (FEM) for contact problems, there will be a solution. This article has set up a system based on argument passing between virtual reality environment and FEM solver, and details the system working process and the challenge.

Near infrared spectroscopy signal processing for interfacing brain function

Abstract: Near-infrared spectroscopy (NIRS) which can detect rapid signals and slow signals has been widely used in the detection of brain function. However, due to the near-infrared spectroscopy signal contains some of the inevitable noisel, we need to pre-treat near-infrared spectroscopy signal. In this paper, interference suppression for data preprocessing on the premise in the original signal head movement, combined with the mobile standard deviation and wavelet singular value detection, to determine the exact location of the moving interference, the processed data can inhibit large fluctuations and pulse interferences. Motion artifacts can be suppressed automatically by combined with the mobile standard deviation and wavelet singular value detection to determine the exact location of the movement interferences, the method can restrain the large fluctuations and pulse interferences; Wavelet threshold denoising inhibit biological interferences and high- frequency noise, EMD threshold denoising can inhibit biological interferences, high-frequency interferences and baseline drift, independent component analysis also inhibited biological interferences, high-frequency interferences and baseline drift. The performance of EMD threshold denoising method is best with the highest signal noise ratio and the relative short processing time.

Using implicit features for enhancing the immersive object representation in multimodal virtual reality environments

Abstract: We introduce a new concept of so called implicit features used to enhance the immersive representation of objects in multimodal virtual reality environments. The implicit features represent hidden object properties (i.e. magnetization, radiation, humidity, toxicity, etc.) which normally are not part of the object model cannot be perceived by the observer through his/her senses without specialized equipment in order to expand the observer's sensory abilities. The proposed approach extends the underlying general scene graph structure of the Virtual Reality software system incorporating additional effects nodes for implicit features representation. It is flexible and can be easily implemented on different hardware configurations on a single computer or on a computer cluster for immersive presentation.