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Scalp EEG-Based Pain Detection Using Convolutional Neural Network
Duo Chen;Haihong Zhang;Perumpadappil Thomas Kavitha;Fong Ling Loy;Soon Huat Ng;Chuanchu Wang;Kok Soon Phua;Soon Yin Tjan;Su-Yin Yang;Cuntai Guan
Pain is an integrative phenomenon coupled with dynamic interactions between sensory and contextual processes in the brain, often associated with detectable neurophysiological changes. Recent advances in brain activity recording tools and machine learning technologies have intrigued research and development of neurocomputing techniques for objective and neurophysiology-based pain detection. This pa...Show More
Infant EEG Band Power Analysis at 6 Months and 18 Months
Haihong Zhang;Chuanchu Wang;Tao Yang;Kok Soon Phua;Valerie Shi Hui Ng;Evelyn Chung Ning Law
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
Neural development of infants has drawn increasing research interests from the community. In this paper, we investigated the frequency band power of 112 infants who participated in an auditory oddball experiment, and the visual expectation (VE) score of 177 infants who went through a visual expectation paradigm test. Analysis found that the frequency band power decreases in the delta and theta ban...Show More
Brain-Computer Interface-Based Soft Robotic Glove Rehabilitation for Stroke
Nicholas Cheng;Kok Soon Phua;Hwa Sen Lai;Pui Kit Tam;Ka Yin Tang;Kai Kei Cheng;Raye Chen-Hua Yeow;Kai Keng Ang;Cuntai Guan;Jeong Hoon Lim
Objective: This randomized controlled feasibility study investigates the ability for clinical application of the Brain-Computer Interface-based Soft Robotic Glove (BCI-SRG) incorporating activities of daily living (ADL)-oriented tasks for stroke rehabilitation. Methods: Eleven recruited chronic stroke patients were randomized into BCI-SRG or Soft Robotic Glove (SRG) group. Each group underwent 120...Show More
Assessment of the Efficacy of EEG-Based MI-BCI With Visual Feedback and EEG Correlates of Mental Fatigue for Upper-Limb Stroke Rehabilitation
Ruyi Foong;Kai Keng Ang;Chai Quek;Cuntai Guan;Kok Soon Phua;Christopher Wee Keong Kuah;Vishwanath Arun Deshmukh;Lester Hon Lum Yam;Deshan Kumar Rajeswaran;Ning Tang;Effie Chew;Karen Sui Geok Chua
Objective: This single-arm multisite trial investigates the efficacy of the neurostyle brain exercise therapy towards enhanced recovery (nBETTER) system, an electroencephalogram (EEG)-based motor imagery brain-computer interface (MI-BCI) employing visual feedback for upper-limb stroke rehabilitation, and the presence of EEG correlates of mental fatigue during BCI usage. Methods: A total of 13 recr...Show More
Assessment of the Efficacy of EEG-Based MI-BCI With Visual Feedback and EEG Correlates of Mental Fatigue for Upper-Limb Stroke Rehabilitation
Ruyi Foong;Kai Keng Ang;Chai Quek;Cuntai Guan;Kok Soon Phua;Christopher Wee Keong Kuah;Vishwanath Arun Deshmukh;Lester Hon Lum Yam;Deshan Kumar Rajeswaran;Ning Tang;Effie Chew;Karen Sui Geok Chua
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
Prognostic and Monitory EEG-Biomarkers for BCI Upper-Limb Stroke Rehabilitation
Ravikiran Mane;Effie Chew;Kok Soon Phua;Kai Keng Ang;Neethu Robinson;A. P. Vinod;Cuntai Guan
With the availability of multiple rehabilitative interventions, identifying the one that elicits the best motor outcome based on the unique neuro-clinical profile of the stroke survivor is a challenging task. Predicting the potential of recovery using biomarkers specific to an intervention hence becomes important. To address this, we investigate intervention-specific prognostic and monitory biomar...Show More
Differential Amplitude of Low-Frequency Fluctuations in brain networks after BCI Training with and without tDCS in Stroke
Mengjiao Hu;Fang Ji;Zhongkang Lu;Weimin Huang;Reza Khosrowabadi;Ling Zhao;Kai Keng Ang;Kok Soon Phua;Fatima Ali Nasrallah;Kai-Hsiang Chuang;Mary C Stephenson;John Totman;Xudong Jiang;Effie Chew;Cuntai Guan;Juan Zhou
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2018 | Conference Paper |
Cited by: Papers (4)
Mapping the brain alterations post stroke and post intervention is important for rehabilitation therapy development. Previous work has shown changes in functional connectivity based on resting-state fMRI, structural connectivity derived from diffusion MRI and perfusion as a result of brain-computer interface-assisted motor imagery (MI-BCI) and transcranial direct current stimulation (tDCS) in uppe...Show More
Differential Amplitude of Low-Frequency Fluctuations in brain networks after BCI Training with and without tDCS in Stroke
Mengjiao Hu;Fang Ji;Zhongkang Lu;Weimin Huang;Reza Khosrowabadi;Ling Zhao;Kai Keng Ang;Kok Soon Phua;Fatima Ali Nasrallah;Kai-Hsiang Chuang;Mary C Stephenson;John Totman;Xudong Jiang;Effie Chew;Cuntai Guan;Juan Zhou
Year: 2018 | Conference Paper |
Quantitative EEG as Biomarkers for the Monitoring of Post-Stroke Motor Recovery in BCI and tDCS Rehabilitation
Ravikiran Mane;Effie Chew;Kok Soon Phua;Kai Keng Ang;A. P. Vinod;Cuntai Guan
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2018 | Conference Paper |
Cited by: Papers (11)
This study investigates the neurological changes in the brain activity of chronic stroke patients undergoing different types of motor rehabilitative interventions and their relationship with the clinical recovery using the Quantitative Electroencephalography (QEEG) features. Over a period of two weeks, 19 hemiplegic chronic stroke patients underwent 10 sessions of upper extremity motor rehabilitat...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
Increased Theta Oscillations During Motor Imagery in a Subject with Late-stage ALS
Q. Rosa So;Tao Yang;Kok Soon Phua;Juanhong Yu;Valerie Toh;Wai Hoe Ng;Kai Keng Ang
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
Non-invasive brain computer interface (BCI) has been successfully used to control cursors, helicopters and robotic arms. However, this technology is not widely adopted by people with late-stage amyotrophic lateral sclerosis (ALS) due to poor effectiveness. In this study, we attempt to assess the cognitive state of a completely locked-in ALS subject, and her ability to use motor imagery-based BCI f...Show More
Modeling EEG-based Motor Imagery with Session to Session Online Adaptation
Zhuo Zhang;Ruyi Foong;Kok Soon Phua;Chuanchu Wang;Kai Keng Ang
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2018 | Conference Paper |
Cited by: Papers (9)
Subject-specific calibration plays an important role in electroencephalography (EEG)-based Brain-Computer Interface (BCI) for Motor Imagery (MI) detection. A calibration session is often introduced to build a subject specific model, which then can be deployed into BCI system for MI detection in the following rehabilitation sessions. The model is termed as a fixed calibration model. Progressive ada...Show More
A measurement of motor recovery for motor imagery-based BCI using EEG coherence analysis
Sau Wai Tung;Cuntai Guan;Kai Keng Ang;Kok Soon Phua;Chuanchu Wang;Christopher Wee Keong Kuah;Karen Sui Geok Chua;Yee Sien Ng;Ling Zhao;Effie Chew
2015 10th International Conference on Information, Communications and Signal Processing (ICICS)
Year: 2015 | Conference Paper |
Cited by: Papers (1)
Motor imagery-based BCI (MI-BCI) technology possesses the potential to be a post-stroke rehabilitation tool. To ensure the optimal use of the MI-BCI technology for stroke rehabilitation, the ability to measure the motor recovery patterns is important. In this study, the relationship between the EEG recorded during, and the changes in the recovery patterns before and after MI-BCI rehabilitation is ...Show More
Combining EPI and motion correction for fMRI human brain images with big motion
Zhongkang Lu;Kok Soon Phua;Weimin Huang;Xin Hong;Fatima Ali Nasrallah;Kai-Hsiang Chuang;Cuntai Guan
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2015 | Conference Paper |
Motion correction is an important component in fMRI brain image analysis. Linear registration technique is mostly used in the process based on the assumption that there is not any shape changes of human brain during imaging process. Echo planar imaging (EPI) technique has been widely adapted in fMRI imaging to shorten encoding duration and increase temporal resolution. However, due to the magnetic...Show More
Quality assessment of EEG signals based on statistics of signal fluctuations
Huijuan Yang;Cuntai Guan;Kai Keng Ang;Kok Soon Phua;Chuanchu Wang
2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
Year: 2014 | Conference Paper |
Cited by: Papers (2)
The quality of the non-invasive EEG signals was always affected by the changes in the contact impedances and the artifacts from eye blinking, eye movements and body movements. An effective quality assessment method is needed to assess the qualities of the EEG signals. This paper proposed a novel method to assess the signal quality of EEG signals based on block-based measurements of the fluctuation...Show More
Selection of effective EEG channels in brain computer interfaces based on inconsistencies of classifiers
Huijuan Yang;Cuntai Guan;Kai Keng Ang;Kok Soon Phua;Chuanchu Wang
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2014 | Conference Paper |
Cited by: Papers (5)
This paper proposed a novel method to select the effective Electroencephalography (EEG) channels for the motor imagery tasks based on the inconsistencies from multiple classifiers. The inconsistency criterion for channel selection was designed based on the fluctuation of the classification accuracies among different classifiers when the noisy channels were included. These noisy channels were then ...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 forearm pronation/supination assessment method integrated into Haptic Knob for stroke rehabilitation
Longjiang Zhou;Kai Keng Ang;Chuanchu Wang;Kok Soon Phua;Cuntai Guan
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)
Year: 2013 | Conference Paper |
The Haptic Knob (HK) is a robotic device that enables subjects to open or close their hands, or rotate their forearms for stroke rehabilitation. The present HK uses force sensors to measure the force applied by the subject, which provides an indirect force measurement with high development cost. In this paper, we propose a novel method to detect the grasping force applied directly on the haptic kn...Show More
A novel hand strength assessment method integrated into haptic knob for stroke rehabilitation
Longjiang Zhou;Kai Keng Ang;Chuanchu Wang;Kok Soon Phua;Cuntai Guan
2013 IEEE Symposium on Computational Intelligence in Rehabilitation and Assistive Technologies (CIRAT)
Year: 2013 | Conference Paper |
Cited by: Papers (3)
Haptic knob is a robotic assistive tool that allows subjects to open or close their hands, or rotate their arms so as to improve their motor functions after stroke. Current haptic knob uses force sensors to measure the force applied by the subject, which provides an indirect force with high development cost. This paper proposes a method to detect the force applied directly on the haptic knob by me...Show More
A clinical study of motor imagery BCI performance in stroke by including calibration data from passive movement
Kai Keng Ang;Cuntai Guan;Karen Sui Geok Chua;Kok Soon Phua;Chuanchu Wang;Zheng Yang Chin;Longjiang Zhou;Ka Yin Tang;Gopal Joseph Ephraim Joseph;Christopher Kuah
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2013 | Conference Paper |
Cited by: Papers (3)
Electroencephalogram (EEG) data from performing motor imagery are usually used to calibrate a subject-specific model in Motor Imagery Brain-Computer Interface (MI-BCI). However, the performance of MI is not directly observable by another person. Studies that attempted to address this issue in order to improve subjects with low MI performance had shown that it is feasible to use calibration data fr...Show More
A clinical study of motor imagery BCI performance in stroke by including calibration data from passive movement
Kai Keng Ang;Cuntai Guan;Karen Sui Geok Chua;Kok Soon Phua;Chuanchu Wang;Zheng Yang Chin;Longjiang Zhou;Ka Yin Tang;Gopal Joseph Ephraim Joseph;Christopher Kuah
Year: 2013 | Conference Paper |
Feature consistency-based model adaptation in session-to-session classification: A study using motor imagery of swallow EEG signals
Huijuan Yang;Cuntai Guan;Kai Keng Ang;Chuanchu Wang;Kok Soon Phua;Christina Tang Ka Yin;Longjiang Zhou
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2013 | Conference Paper |
Cited by: Papers (2)
The performance degradation for session to session classification in brain computer interface is a critical problem. This paper proposes a novel method for model adaptation based on motor imagery of swallow EEG signal for dysphagia rehabilitation. A small amount of calibration testing data is utilized to select the model catering for test data. The features of the training and calibration testing ...Show More
Motor imagery BCI for upper limb stroke rehabilitation: An evaluation of the EEG recordings using coherence analysis
Sau Wai Tung;Cuntai Guan;Kai Keng Ang;Kok Soon Phua;Chuanchu Wang;Ling Zhao;Wei Peng Teo;Effie Chew
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2013 | Conference Paper |
Cited by: Papers (11)
Brain-computer interface (BCI) technology has the potential as a post-stroke rehabilitation tool, and the efficacy of the technology is most often demonstrated through output peripherals such as robots, orthosis and computers. In this study, the EEG signals recorded during the course of upper limb stroke rehabilitaion using motor imagery BCI were analyzed to better understand the effect of BCI the...Show More
Transcranial direct current stimulation and EEG-based motor imagery BCI for upper limb stroke rehabilitation
Kai Keng Ang;Cuntai Guan;Kok Soon Phua;Chuanchu Wang;Irvin Teh;Chang Wu Chen;Effie Chew
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2012 | Conference Paper |
Cited by: Papers (17)
Clinical studies had shown that EEG-based motor imagery Brain-Computer Interface (MI-BCI) combined with robotic feedback is effective in upper limb stroke rehabilitation, and transcranial Direct Current Stimulation (tDCS) combined with other rehabilitation techniques further enhanced the facilitating effect of tDCS. This motivated the current clinical study to investigate the effects of combining ...Show More
Dynamic initiation and dual-tree complex wavelet feature-based classification of motor imagery of swallow EEG signals
Huijuan Yang;Cuntai Guan;Kai Keng Ang;Chuan Chu Wang;Kok Soon Phua;Juanhong Yu
The 2012 International Joint Conference on Neural Networks (IJCNN)
Year: 2012 | Conference Paper |
Cited by: Papers (11)
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 (DT-CWT). A novel sliding window-based pe...Show More
Calibrating EEG-based motor imagery brain-computer interface from passive movement
Kai Keng Ang;Cuntai Guan;Chuanchu Wang;Kok Soon Phua;Adrian Hock Guan Tan;Zheng Yang Chin
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2011 | Conference Paper |
Cited by: Papers (13)
EEG data from performing motor imagery are usually collected to calibrate a subject-specific model for classifying the EEG data during the evaluation phase of motor imagery Brain-Computer Interface (BCI). However, there is no direct objective measure to determine if a subject is performing motor imagery correctly for proper calibration. Studies have shown that passive movement, which is directly o...Show More
Clinical study of neurorehabilitation in stroke using EEG-based motor imagery brain-computer interface with robotic feedback
Kai Keng Ang;Cuntai Guan;Karen Sui Geok Chua;Beng Ti Ang;Christopher Kuah;Chuanchu Wang;Kok Soon Phua;Zheng Yang Chin;Haihong Zhang
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology
Year: 2010 | Conference Paper |
Cited by: Papers (60)
This clinical study investigates the ability of hemiparetic stroke patients in operating EEG-based motor imagery brain-computer interface (MI-BCI). It also assesses the efficacy in motor improvements on the stroke-affected upper limb using EEG-based MI-BCI with robotic feedback neurorehabilitation compared to robotic rehabilitation that delivers movement therapy. 54 hemiparetic stroke patients wit...Show More
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