A P300-speller based on event-related spectral perturbation (ERSP)

A brain-computer interface (BCI) P300 speller is a novel technique that helps people spell words using the electroencephalography (EEG) without the involvement of muscle activities. However, only time domain ERP features (P300) are used for controlling of the BCI speller. In this paper, we investigated the time-frequency EEG features for the P300-based brain-computer interface speller. A signal preprocessing method integrated ensemble average, principal component analysis, and independent component analysis to remove noise and artifacts in the EEG data. A time-frequency analysis based on wavelet transform was carried out to extract event-related spectral perturbation (ERSP) and inter-trial coherence (ITC) features. Results showed that the proposed signal processing method can effectively extract EEG time-frequency features in the P300 speller, suggesting that ERSP and ITC may be useful for improving the performance of BCI P300 speller. © 2012 IEEE.published_or_final_versio

Immunotherapy for Glioblastomas

Glioblastoma (GBM), a WHO grade IV brain tumor, is an aggressive tumor with poor prognosis; even with current standard care of triple therapy, consisting of surgical resection, chemo and radiation therapy, the patients’ median survival time is only approximately 15 months. Recent practice shows that immunotherapy made some progress in some other solid tumors, like melanoma or non-small cell lung cancer. This chapter is going to review some advances in immunotherapy for GBM

Upper extremity kinetics during walker-assisted gait of knee joint stiffness simulation

Because of various inflammations and fractures of low limbs, the number of patients with knee joint stiffness is increasing. Walkers are commonly prescribed to improve these patients' stability and ambulatory ability. The evaluation on the assisted walking effect has become a hot problem, whose prerequisite is a comprehensive mechanical understanding of the upper extremity force. In order to study the upper extremity kinetics during walker-assisted gait of knee joint stiffness, this paper developed a new method to collect upper extremity kinetics data based on a special-designed walker dynamometer system. Handle reaction vector (HRV) data were collected from 15 healthy right-handed young subjects by simulation experiments for four knee joint stiffness modes. T test and support vector machine (SVM) were used to analyze these HRV data. The results indicated that knee joint stiffness had a great influence on the upper extremity force during the walker-assisted walking. The proposed method is hoped to beneficially influence walker-assisted gait retraining strategies for knee joint stiffness. © 2010 IEEE.published_or_final_versionThe 2010 IEEE International Conference on Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS), Taranto, Apulia, Italy, 6-8 September 2010. In Proceedings of the IEEE-VECIMS, 2010, p. 1-

Brain-computer interface technique for electro-acupuncture stimulation control

Electro-acupuncture stimulation (EAS) technique applies the electrical nerve stimulation therapy on traditional acupuncture points to restore the muscle tension. The rapid rise and development of brain-computer interface (BCI) technology makes the thought-control of EAS possible. This paper designed a new BCI-controls-EAS (BCICEAS) system by using event related desynchronization (ERD) of EEG signal evoked by imaginary movement. The Fisher parameters were extracted from feature frequency bands of EEG and classified into EAS control commands by Mahalanobis Classifier. A feedback training technique was introduced to enhance the signal feature through a visual feedback interface with a virtual liquid column, which height varied along with EEG power spectral feature. Experimental results demonstrated the validity of the proposed method, including the effective improvement of feedback training on signal feature and reliable control of EAS. It is hoped the BCICEAS can explore a new way for EAS system design and help people who sufferers with severe movement dysfunction. © 2010 IEEE.published_or_final_versionThe 2010 IEEE International Conference on Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS), Taranto, Apulia, Italy, 6-8 September 2010. In Proceedings of the IEEE-VECIMS, , 2010, p. 33-3

A hybrid brain-computer interface combining the EEG and NIRS

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 75.04% and the highest rate 91.11%, 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. © 2012 IEEE.published_or_final_versio

ICA-SVM combination algorithm for identification of motor imagery potentials

Mental tasks such as motor imagery in synchronization with a cue which result event related desynchronization (ERD) and event related synchronization (ERS) are usually studied in brain-computer interface (BCI) system. In this paper we analyze and classify the ERD/ERS response evoked by the motor imagery of left hand, right hand, foot and tongue. The signals were spatially filtered by Independent Component Analysis (ICA) before calculating the power spectral density (PSD) for related electrodes, and then the Support Vector Machine (SVM) was adopted to recognise the different imagery pattern according to ERD/ERS feature for the signals. The results showed that the combination of ICA-based signal extraction algorithm and SVM-based classification method was an effective tool for the identification of motor imagery potentials, with the highest accuracy rate of 91.4% and 77.6% for the lowest. © 2010 IEEE.published_or_final_versionThe 2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA), Taranto, Apulia, Italy, 6-8 September 2010. In Proceedings of IEEE-CIMSA, 2010, p. 92-9

Decreased Blood Levels of Oxytocin in Ketamine-Dependent Patients During Early Abstinence

Background: Ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist, is a common drug of abuse worldwide. Existing evidence suggest a disruption of oxytocin system involves in the development of addiction. In this study, we aimed to investigate the role of oxytocin in ketamine addiction by measuring the blood oxytocin levels in ketamine-dependent (KD) patients.Methods: Sixty-five KD patients and 65 controls were enrolled. Fasting plasma levels of oxytocin were determined at baseline and 1 and 2 weeks after ketamine withdrawal. Ketamine use variables, Beck Depression Inventory, Beck Anxiety Inventory (BAI), Visual Analog Scale for craving, and Childhood Trauma Questionnaire-short form were assessed in KD patients.Results: KD patients had significantly lower levels of oxytocin at baseline compared to controls (5.89 ± 2.13 vs. 9.53 ± 4.17 ng/mL, P < 0.001). Oxytocin levels increased after one (6.74 ± 2.63, P < 0.002) and 2 weeks (6.89 ± 2.69, P = 0.01) of withdrawal in KD patient despite the levels were still lower than controls (P = 0.001 and 0.002, respectively). The clinical variables did not correlate with baseline oxytocin levels except BAI scores, which showed a negative correlation with the levels (r = −0.263; P = 0.039).Conclusion: We found a distinctively reduced oxytocin level in KD patients and the level did not normalize after early abstinence. Lower oxytocin might be associated with anxious phenotype of ketamine dependence. These results suggest that oxytocin system dysregulated following chronic ketamine abuse and might provide insight in evaluating the potential therapeutic use of oxytocin for treating ketamine dependence

Direct synthesis of ultrafine tetragonal BaTiO3 nanoparticles at room temperature

A large quantity of ultrafine tetragonal barium titanate (BaTiO3) nanoparticles is directly synthesized at room temperature. The crystalline form and grain size are checked by both X-ray diffraction and transmission electron microscopy. The results revealed that the perovskite nanoparticles as fine as 7 nm have been synthesized. The phase transition of the as-prepared nanoparticles is investigated by the temperature-dependent Raman spectrum and shows the similar tendency to that of bulk BaTiO3 materials. It is confirmed that the nanoparticles have tetragonal phase at room temperature