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Publications (33)
Electroencephalography (EEG)-based brain—computer interface (BCI) is a non-invasive technology with potential in various healthcare applications, including stroke rehabilitation and neuro-feedback training. These applications typically require multi-channel EEG. However, setting up a multi-channel EEG headset is time-consuming, potentially resultin...
This paper discusses a machine learning approach for detecting SSVEP at both ears with minimal channels. SSVEP is a robust EEG signal suitable for many BCI applications. It is strong at the visual cortex around the occipital area, but the SNR gets worse when detected from other areas of the head. To make use of SSVEP measured around the ears follow...
Speech discrimination is used by audiologists in diagnosing and determining treatment for hearing loss patients. Usually, assessing speech discrimination requires subjective responses. Using electroencephalography (EEG), a method that is based on event-related potentials (ERPs), could provide objective speech discrimination. In this work we propose...
Background
The aging population is one of the major challenges affecting societies worldwide. As the proportion of older people grows dramatically, so does the number of age-related illnesses such as dementia-related illnesses. Preventive care should be emphasized as an effective tool to combat and manage this situation.
Objective
The aim of this p...
BACKGROUND
The aging population is one of the major challenges affecting societies worldwide. As the proportion of older people grows dramatically, so does the number of age-related illnesses such as dementia-related illnesses. Preventive care should be emphasized as an effective tool to combat and manage this situation.
OBJECTIVE
The aim of this...
BACKGROUND
Electroencephalography (EEG) is a non-invasive Brain Computer Interface (BCI) technology that has shown potential in various healthcare applications such as epilepsy treatment, sleep disorder diagnosis, and stroke rehabilitation. Usually these applications require multi-channels EEG. However, multi-channel EEG headset setup process is ti...
For future healthcare applications, which are increasingly moving towards out-of-hospital or home-based caring models, the ability to remotely and continuously monitor patients' conditions effectively are imperative. Among others, emotional state is one of the conditions that could be of interest to doctors or caregivers. This paper discusses a pre...
Introduction
This study examines the clinical efficacy of a game-based neurofeedback training (NFT) system to enhance cognitive performance in patients with amnestic mild cognitive impairment (aMCI) and healthy elderly subjects. The NFT system includes five games designed to improve attention span and cognitive performance. The system estimates att...
Background:
One of the most promising applications for electroencephalogram (EEG)-based brain computer interface is for stroke rehabilitation. Implemented as a standalone motor imagery (MI) training system or as part of a rehabilitation robotic system, many studies have shown benefits of using them to restore motor control in stroke patients. Hand...
Our work is aimed to investigate the feasibility and suitability of subject-dependent and subject-independent emotion classification using unimodal and multimodal physiological signals. We propose to use EEG, ECG, and SC to classify valence and arousal emotion using SVM classifier. The emotions are elicited by pictures and classical music. In class...
Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. This study proposes the utilization of a deep learning network (DLN) to discover unknown feature correlation between input signals that is cru...
There is a strong relationship between sustained attention and cognitive performance. The ability to sustain attention potentially leads to enhance cognitive functions. Attention Training provides a promising alternative therapy to enhance cognitive ability and it can be efficiently implemented with Neurofeedback Training (NFT) system. The purpose...
Online EEG artifact suppression system is a crucial function of real-time Brain Computer Interface (BCI) applications. EEG artifacts significantly affect the accuracy of feature extraction and data classification for estimating cognitive states in Neurofeedback Training (NFT) systems. The EEG artifacts derived from ocular and muscular activities ar...
We propose to use real-time EEG signal to classify happy and unhappy emotions elicited by pictures and classical music. We use PSD as a feature and SVM as a classifier. The average accuracies of subject-dependent model and subject-independent model are approximately 75.62% and 65.12%, respectively. Considering each pair of channels, temporal pair o...
This paper describes the design, development, and tests of a low cost ALS. It was designed for hearing-impaired student classrooms. It utilised digital wireless technology and was aimed to be an alternative to a popular FM ALS. Key specifications include transmitting in 2.4 GHz ISM band with eight selectable transmission channels, battery operated...
In this research we propose to use EEG signal to classify two emotions (i.e., positive and negative) elicited by pictures. With power spectrum features, the accuracy rate of SVM classifier is about 85.41%. Considering each pair of channels and different frequency bands, it shows that frontal pairs of channels give a better result than the other are...
Abstract Providing effective travel time prediction is important part for Advanced Traveler
Information Systems (ATIS) and transportation management applications. The present paper
proposes a short-term prediction method travel time up to 30 minutes by Support Vector
Machine. The performance of the propose model is compared to historic approach....
This paper presents the methodology to find the appropriate locations on the scalp for detecting EEG signal for attention training. The aim was to use low cost commercial EEG sensing device to select four positions which provide strong attention related signals. We aim to use the results of this work to develop a low cost attention training set. Th...
The authors have studied and developed a proprietary digitally modulated Assistive Listening System (ALS)[1,2]. The system was designed to be used in a classroom for the hearing impaired students, as it was intended to be a low cost alternative to an existing FM system. It includes one transmitter and up to ten receivers, and operates in a broadcas...
This paper proposes new automated algorithm that can detect traffic patterns leading to congestion in microscopic traffic variables. The approach algorithm, namely Dynamic Time Warping, has many abilities to classify complex time series but requires much smaller training dataset than traditional Artificial Intelligent (AI) algorithms. The performan...
Electronic stethoscope is developed to improve the limitations and add functions to a conventional stethoscope. In electronic stethoscope, sound is transformed into electrical signal which offers various benefits including signal quality improvement, signal record and signal transfer via wireless. Electronic stethoscope in the market is expensive....
The objective of this study is to develop a new automated short-term traffic congestion detection algorithm that can detect traffic patterns leading to congestion in microscopic traffic variables. A new approach algorithm, namely Dynamic Time Warping, is different from traditional artificial intelligent algorithms that require a large training data...
We have developed a simple, low-cost digital wireless broadcasting system prototype, intended for a classroom of hearing impaired students. The system is designed to be a low-cost alternative to an existing FM system.
The system implemented is for short-range communication, with a one-transmitter, multiple-receiver configuration, which is typical f...
Due to the expansive use of GPS, GPS data can be used to provide valuable travel time and the travel speed data for the traffic information system. However, to access ID number for personal car would have problems with privacy. Thus, mean travel speed (MTS), which requires individual vehicle tracking, cannot be calculated directly. In this research...
As in many Asian cities, Bangkok motorcycle riders tend to ride along a traffic lane with a car or other motorcycles. They also meander through spaces between vehicles at intersections. These behaviors should have impact on the traffic throughputs and vehicle queuing times. Since motorcycles accounts for 20% of all Bangkok vehicles, this impact sho...
In this paper, we describe the development of a low cost wireless UHF broadcasting system prototype. It is designed for a short range application, with up to ten receivers, such as one used in a classroom for hearing impaired students. This system is intended to be a low cost alternative to an existing FM system, with additional capability in secur...
This paper discusses the design and implementation of an embedded digital wireless system for use in a classroom of hearing impaired children. This system is intended to be a low cost alternative to an existing FM system, with additional capability in security with an encryption function. The design discussed is an updated version of a one-to-one s...