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Hybrid EEG-fNIRS brain-computer interface based on the non-linear features extraction and stacking ensemble learning

Maher Asmaa, Mian Qaisar Saeed, Salankar N., Jiang Feng, Tadeusiewicz Ryszard, Pławiak Paweł, Abd El-Latif Ahmed A., Hammad Mohamed

Biocybernetics and Biomedical Engineering

2023

Vol. 43, no. 2

463--475

The Brain-computer interface (BCI) is used to enhance the human capabilities. The hybridBCI (hBCI) is a novel concept for subtly hybridizing multiple monitoring schemes to maximize the advantages of each while minimizing the drawbacks of individual methods. Recently, researchers have started focusing on the Electroencephalogram (EEG) and ‘‘Functional Near-Infrared Spectroscopy” (fNIRS) based hBCI. The main reason is due to the development of artificial intelligence (AI) algorithms such as machine learning approaches to better process the brain signals. An original EEG-fNIRS based hBCI system is devised by using the non-linear features mining and ensemble learning (EL) approach. We first diminish the noise and artifacts from the input EEG-fNIRS signals using digital filtering. After that, we use the signals for non-linear features mining. These features are ‘‘Fractal Dimension” (FD), ‘‘Higher Order Spectra” (HOS), ‘‘Recurrence Quantification Analysis” (RQA) features, and Entropy features. Onward, the Genetic Algorithm (GA) is employed for Features Selection (FS). Lastly, we employ a novel Machine Learning (ML) technique using several algorithms namely, the ‘‘Naïve Bayes” (NB), ‘‘Support Vector Machine” (SVM), ‘‘Random Forest” (RF), and ‘‘K-Nearest Neighbor” (KNN). These classifiers are combined as an ensemble for recognizing the intended brain activities. The applicability is tested by using a publicly available multi-subject and multiclass EEG-fNIRS dataset. Our method has reached the highest accuracy, F1-score, and sensitivity of 95.48%, 97.67% and 97.83% respectively.

Research on visible light indoor positioning algorithm based on fire safety

Li Mao, Jiang Feng, Pei Cong

Optica Applicata

2020

Vol. 50, nr 2

209--222

From the perspective of ensuring life safety, combined with the advantages of high-speed time response and energy conservation of white light emitting diodes (LEDs), the visible light indoor positioning algorithm based on fire safety is proposed in the paper. First, the model is designed which needs three LED lights arranged in a straight line and positioned in the geographically north direction on the top of the model. Then, the proposed algorithm is discussed and analyzed when the camera is located at the center of the model and facing north, when the camera is located at the center of the model and the angle is rotated, and when the camera is located at any position of the model, respectively. It can accurately calculate the current position of the camera, its response speed is fast and the positioning accuracy is high. Furthermore, this paper also verifies the practicability and reliability of the algorithm by designing the visible light indoor positioning system based on fire safety rescue in natural environment and smoke environment. The experimental results show that the positioning error does not exceed 0.70 cm in smoke environment.

Low temperature preparation of stabilized aluminium titanate ultrafine powder assisted by the solvothermal treatment process

Zhang Quan, Liu Jianmin, Jiang Wei-Hui, Feng Guo, Jiang Feng, Wang Tao

Materiały Ceramiczne

2019

T. 71, nr 4

362--367

Stabilized aluminium titanate (AT) ultrafine powder with the average particle size of 150 nm was prepared at 1000 °C assisted by the solvothermal process, using aluminium nitrate (Al(NO3)3•9H2O) and titanium tetrachloride (TiCl4) as precursor materials, ethanol as solvent, manganese(II) or iron(III) as stabilizer and PEG1000 as additive. The phase transition process of AT dry gel powder and the influence of technological parameters on the synthesis of stable AT superfine powder were studied by DTA-TG, XRD and TEM. The results showed that the amorphous dry gel formed anatase phase first, and then transformed into Al2(1-x)MgxTi1+xO5 solid solution. Magnesium acetate shows better stabilization effect compared with ferric chloride and ferric sulfate. Optimized dosages of magnesium acetate and PEG1000 are 10 mol% and 3 wt%, respectively.

Stabilizowany, bardzo drobny proszek tytanianu glinu (AT) o średniej wielkości cząstek 150 nm został przygotowany w 1000 ° C przy pomocy procesu solwotermalnego, przy użyciu azotanu glinu (Al(NO3)3•9H2O) i czterochlorku tytanu (TiCl4) jako materiałów prekursorowych, etanolu jako rozpuszczalnika, mangan(II) lub żelazo(III) jako stabilizatorów i PEG1000 jako dodatku. Proces przemiany fazowej suchego proszku żelu AT i wpływ parametrów technologicznych na syntezę stabilnego super drobnego proszku AT zbadano za pomocą DTA-TG, XRD i TEM. Wyniki wykazały, że amorficzny suchy żel najpierw utworzył fazę anatazową, a następnie przekształcił się w stały roztwór Al2(1-x)MgxTi1+xO5. Octan magnezu wykazuje lepszy efekt stabilizujący w porównaniu z chlorkiem żelazowym i siarczanem żelazowym. Zoptymalizowane dawki octanu magnezu i PEG1000 wynoszą odpowiednio 10% mol. i 3% wag.