Juanhong Yu

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The injection of emotional intelligence in human-computer interfaces is necessary for computer applications to appear intelligent when interacting with people. With the recent development of brain imaging techniques and brain-computer interfaces, computers can actually take a look inside users' head to observe their emotional states. This paper presents an(More)
—The use of motor imagery-based brain computer interface has recently been shown to have potential for rehabilitation. This paper proposes a novel scheme to detect motor imagery of swallow from electroencephalography (EEG) signals for dysphagia rehabilitation. The proposed scheme extracts features from the coefficients of dual-tree complex wavelet transform(More)
Near-infrared spectroscopy (NIRS)–based Brain-Computer Interface (BCI) was recently proposed to assess level of numerical cognition in subjects. However, existing feature extraction method was only proposed for low density 16 channels NIRS-based BCI. This study investigates the performance of a high density 348 channels NIRS-based BCI on 8 healthy subjects(More)
This study presents single-trial classification performance on high density Near Infrared Spectroscopy (NIRS) data collected from the prefrontal cortex of 11 healthy subjects while performing working memory tasks and idle condition. The NIRS data collected comprised a total of 40 trials of n-back tasks for 2 difficulty levels: n=1 for easy and n=3 for hard.(More)
We developed an EEG- and audio-based sleep sensing and enhancing system, called iSleep (interactive Sleep enhancement apparatus). The system adopts a closed-loop approach which optimizes the audio recording selection based on user's sleep status detected through our online EEG computing algorithm. The iSleep prototype comprises two major parts: 1) a(More)
Several functional neuroimaging studies had been performed to explore the sensorimotor function for motor imagery and passive movement, but there is scanty work that investigated the cortical activation pattern for passive movement using functional Near-Infrared Spectroscopy (fNIRS). This study investigated the cortical activation pattern from fNIRS data of(More)
Sleep has been shown to be imperative for the health and well-being of an individual. To design intelligent sleep management tools, such as the music-induce sleep-aid device, automatic detection of sleep onset is critical. In this work, we propose a simple yet accurate method for sleep onset prediction, which merely relies on Electroencephalogram (EEG)(More)
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