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Prefrontal Cortical Activation While Doing Mindfulness Task: a Pilot Functional Near-Infrared Spectroscopy Study
Juanhong Yu;Kai Keng Ang;Carol C. Choo;Cyrus SH Ho;Roger Ho;Rosa Q. So
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Year: 2020 | Conference Paper |
Cited by: Papers (5)
Mindfulness interventions are increasingly used in clinical settings. Neurophysiological mechanisms underlying mindfulness offer objective evidence that can help us evaluate the efficacy of mindfulness. Recent advances in technology have facilitated the use of functional Near-Infrared Spectroscopy (fNIRS) as a light weight, portable, and relatively lower cost neuroimaging device as compared to fun...Show More
Image-based Motor Imagery EEG Classification using Convolutional Neural Network
Tao Yang;Kok Soon Phua;Juanhong Yu;Thevapriya Selvaratnam;Valerie Toh;Wai Hoe Ng;Kai Keng Ang;Rosa Q. So
2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)
Year: 2019 | Conference Paper |
Cited by: Papers (9)
Motor Imagery (MI) based Brain Computer Interface (BCI) has clinical applications such as rehabilitation or communication for patients who have lost motor functions. Accurate classification of motor-imagery based electroencephalography (EEG) is important in developing such BCI applications. We propose an image-based approach to design a convolutional neural network (CNN) to classify EEG signals. I...Show More
EEG Channel Selection Based on Correlation Coefficient for Motor Imagery Classification: A Study on Healthy Subjects and ALS Patient
Tao Yang;Kai Keng Ang;Kok Soon Phua;Juanhong Yu;Valerie Toh;Wai Hoe Ng;Rosa Q. So
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2018 | Conference Paper |
Cited by: Papers (6)
Brain-Computer Interface (BCI) provides an alternate channel of interaction for people with severe motor disabilities. The Common Spatial Pattern (CSP) algorithm is effective in extracting discriminative features from EEG data for motor imagery-based Brain-Computer Interface (BCI). CSP yields signal from various locations for better performance. In this study, we selected a subset of EEG channels ...Show More
Prefrontal cortical activation while viewing urban and garden scenes: A pilot fNIRS study
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2017 | Conference Paper |
Cited by: Papers (8)
Recent studies have shown that pleasant and unpleasant emotions could be detected through functional Near-Infrared Spectroscopy (fNIRS). This study investigates the prefrontal cortical activation in human subjects while they were viewing urban and garden scenes. A multi-channel continuous wave fNIRS system was used to record the prefrontal cortical activations from seven subjects. During the data ...Show More
Reduction in time-to-sleep through EEG based brain state detection and audio stimulation
Zhuo Zhang;Cuntai Guan;Ti Eu Chan;Juanhong Yu;Aung Aung Phyo Wai;Chuanchu Wang;Haihong Zhang
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2015 | Conference Paper |
Cited by: Papers (4)
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 sleeping mask integrated with a single channel E...Show More
Single-trial classification of NIRS data from prefrontal cortex during working memory tasks
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2014 | Conference Paper |
Cited by: Papers (4)
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. The single-trial classification was perf...Show More
Automatic sleep onset detection using single EEG sensor
Zhuo Zhang;Cuntai Guan;Ti Eu Chan;Juanhong Yu;Andrew Keong Ng;Haihong Zhang;Chee Keong Kwoh
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2014 | Conference Paper |
Cited by: Papers (7)
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) signal acquired from a single frontal electro...Show More
Cortical activation of passive hand movement using Haptic Knob: A preliminary multi-channel fNIRS study
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2014 | Conference Paper |
Cited by: Papers (2)
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 8 healthy subjects performing motor imag...Show More
Brain-computer interface for neurorehabilitation: Looking beyond upper limbs
Cuntai Guan;Huijuan Yang;Kai Keng Ang;Kok Soon Phua;Juanhong Yu;Chuanchu Wang;Karen Chua;Effie Chew
2014 International Winter Workshop on Brain-Computer Interface (BCI)
Year: 2014 | Conference Paper |
With deeper understanding and appreciation of the roles of Brain-computer interface (BCI) in assisting stroke survivors to restore motor function by inducing activity-dependent brain plasticity through Hebbian learning, more and more studies in applying BCI for stroke rehabilitation have been conducted. Previous studies mainly focused on upper limb rehabilitation, typically by combining BCI with a...Show More
A multimodal fNIRS and EEG-based BCI study on motor imagery and passive movement
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)
Year: 2013 | Conference Paper |
Cited by: Papers (14)
In EEG-based motor imagery Brain-Computer interface (BCI), EEG data collected in the calibration phase is used as a subject-specific model to classify the EEG data in the evaluation phase. Previous study has shown the feasibility of calibrating EEG-based BCI from passive movement. This paper investigates the primary sensorimotor area activation from fNIRS on 4 subjects using multimodal NIRS and EE...Show More
Common frequency pattern for music preference identification using frontal EEG
Yaozhang Pan;Cuntai Guan;Juanhong Yu;Kai Keng Ang;Ti Eu Chan
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)
Year: 2013 | Conference Paper |
In this paper, we investigate the use of 2-channel frontal EEG signal to classify two music preferences: like and dislike. The hypothesis for this investigation is that the frontal EEG signal contains sufficient information on the mental state of a subject for discriminating the preference of music of the subject. An experiment is performed to collect 2-channel frontal EEG data from 12 subjects by...Show More
Prefrontal cortical activation during arithmetic processing differentiated by cultures: A preliminary fNIRS study
Juanghong Yu;Yaozhang Pan;Kai Keng Ang;Cuntai Guan;Darren J. Leamy
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2012 | Conference Paper |
Cited by: Papers (3)
Understanding the neural basis of arithmetic processes could play an important role in improving mathematical education. This study investigates the prefrontal cortical activation among subjects from different cultural backgrounds while performing two difficulty levels of mental arithmetic tasks. The prefrontal cortical activation is measured using a high density 206 channels fNIRS. 8 healthy subj...Show More
Extracting effective features from high density nirs-based BCI for assessing numerical cognition
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2012 | Conference Paper |
Cited by: Papers (11)
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 while they solve mental arithmetic proble...Show More
Fast emotion detection from EEG using asymmetric spatial filtering
Dong Huang;Haihong Zhang;Kaikeng Ang;Cuntai Guan;Yaozhang Pan;Chuanchu Wang;Juanhong Yu
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2012 | Conference Paper |
Cited by: Papers (12)
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 EEG-based emotion detection system which ...Show More
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