1,143 research outputs found

    Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification

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    Objective. The main goal of this work is to develop a model for multi-sensor signals such as MEG or EEG signals, that accounts for the inter-trial variability, suitable for corresponding binary classification problems. An important constraint is that the model be simple enough to handle small size and unbalanced datasets, as often encountered in BCI type experiments. Approach. The method involves linear mixed effects statistical model, wavelet transform and spatial filtering, and aims at the characterization of localized discriminant features in multi-sensor signals. After discrete wavelet transform and spatial filtering, a projection onto the relevant wavelet and spatial channels subspaces is used for dimension reduction. The projected signals are then decomposed as the sum of a signal of interest (i.e. discriminant) and background noise, using a very simple Gaussian linear mixed model. Main results. Thanks to the simplicity of the model, the corresponding parameter estimation problem is simplified. Robust estimates of class-covariance matrices are obtained from small sample sizes and an effective Bayes plug-in classifier is derived. The approach is applied to the detection of error potentials in multichannel EEG data, in a very unbalanced situation (detection of rare events). Classification results prove the relevance of the proposed approach in such a context. Significance. The combination of linear mixed model, wavelet transform and spatial filtering for EEG classification is, to the best of our knowledge, an original approach, which is proven to be effective. This paper improves on earlier results on similar problems, and the three main ingredients all play an important role

    Analysis of worker performances using statistical process control in fish paste otak-otak food industries

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    This research focuses on the improvement of Small and Medium Enterprises through the used of Process Statistical Control (SPC). An industry that focuses on the fish paste (known as “otak-otak”) production was taken as the case study in this research and the problems analysed are based on the real industrial experiences. The data collection for control charts were recorded for two weeks consisting of working time for each operator. The data were collected in subgroup of 16 with sample size of 5. The collection of data for weight of product was recorded randomly for the whole production line, while data collection of working time of operation was taken randomly from each operator every 30 minutes of the working hour. From this study, there are several problems had been detected in the process that been categories in six element that is people, method, measurement, machine, environment and materials. There were lack of motivation, lack of skill, lack of supervision, manual operation, lack of standard of procedure, waiting time in process, weight-based operator, lack of quality check, not using weight scale, conveyer that sometimes got stuck, spoon for tools, no automation, poor layout arrangement, talking while working, small working space, lack of hygiene, waiting time for material and easily spoiled. The findings can be used as the guideline to the industries for future production improvement. The industries would focus on elimination or reduction of the problems through their innovative solution

    Data Analytics in Steady-State Visual Evoked Potential-based Brain-Computer Interface: A Review

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    Electroencephalograph (EEG) has been widely applied for brain-computer interface (BCI) which enables paralyzed people to directly communicate with and control of external devices, due to its portability, high temporal resolution, ease of use and low cost. Of various EEG paradigms, steady-state visual evoked potential (SSVEP)-based BCI system which uses multiple visual stimuli (such as LEDs or boxes on a computer screen) flickering at different frequencies has been widely explored in the past decades due to its fast communication rate and high signal-to-noise ratio. In this paper, we review the current research in SSVEP-based BCI, focusing on the data analytics that enables continuous, accurate detection of SSVEPs and thus high information transfer rate. The main technical challenges, including signal pre-processing, spectrum analysis, signal decomposition, spatial filtering in particular canonical correlation analysis and its variations, and classification techniques are described in this paper. Research challenges and opportunities in spontaneous brain activities, mental fatigue, transfer learning as well as hybrid BCI are also discussed

    Adaptive Filtering Techniques for the Detection of User - Independent Single Trial ERPs in Brain Computer Interfaces

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    El trabajo desarrollado es una presentación de los sistemas Brain Computer Interface (BCI) e involucra el entendimiento tanto de su funcionamiento como de las señales cerebrales en las que este está basado. Para este proyecto, cada una de las partes que forman uno de los tipos de sistema BCI más ampliamente usado serán desarrolladas. Se estudiarán diversas técnicas de procesado de señal para ser aplicadas en varias partes del sistema. Además, una interfaz adecuada será creada para validar los métodos implementados y evaluar el rendimiento del sistema. El resultado final del trabajo será un sistema BCI completo

    The effect of internal through coolant on grinding performance on AISI1020 mildsteel

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    This paper presents the experimental result of grinding performance with an internal through coolant supply. Using this method, the coolant is delivered through the grinding wheel and this concept will allowed the coolant supplied directly to the contact zone. The experiment has been conducted on thin plate of AISI1020 mild steel, to ensure the effectiveness when using internal through coolant supply and the grinding result using internal through. The result of internal through coolant supply was compared with an external coolant supply. It was revealed that the temperature was lower and surface roughness was smaller when the proposed coolant supply concept used

    Classification of electroencephalography for pain and pharmaco-EEG studies

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    Human Computer Interactions for Amyotrophic Lateral Sclerosis Patients

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