Browsing Article by Title
Now showing items 1-20 of 31
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A 13µW 87dB dynamic range implantable ΔΣ modulator for full-spectrum neural recording
(IEEE, 2013-09-26)Experiment analysis on in-vivo data sequences suggests a wide system dynamic range (DR) is required to simultaneously record local field potentials (LFPs), extra-cellular spikes, and artifacts/interferences. In this paper, ... -
Application of Machine Learning on ECG Signal Classification Using Morphological Features
(IEEE, 2020-06)An electrocardiogram (ECG) is a simple test that is used to check one's heart's electrical activity. Sensors attached to the skin are used to detect the electrical signal produced by one's heart each time it beats. Many ... -
Artifact Characterization and Removal for In-Vivo Neural Recording
(Elsevier, 2014-04-15)Background: In vivo neural recordings are often corrupted by different artifacts, especially in a less-constrained recording environment. Due to limited understanding of the artifacts appeared in the in vivo neural data, ... -
Artifact Characterization, Detection and Removal from Neural Signals
(National University of Singapore, 2015-12)Artifact detection and removal are important preprocessing steps for neural recordings to decode the neural signals properly and currently an active research problem. In this thesis, for the first time, artifacts found in ... -
Classification of Emotions Induced by Horror and Relaxing Movies Using Single-Channel EEG Recordings
(Institute of Advanced Engineering and Science (IAES), 2020-08)It has been observed from recent studies that corticolimbic Theta rhythm from EEG recordings perceived as fear or threatening scene during neural processing of visual stimuli. In additions, neural oscillations’ patterns ... -
Design and Implementation of an EOG-based Mouse Cursor Control for Application in Human-Computer Interaction
(IOP, 2020-03-01)Human Computer Interaction (HCI) has turned into an emerging technology due to the advancement in the field artificial intelligence and biomedical engineering. Acquiring different bio-signals such as Electro-oculography ... -
Distance Dependent Service Differentiation of the IEEE 802.11e EDCA on Single Access Point Based WLAN Systems
(Journal of the Bangladesh Electronics Society, 2020-10-19)The IEEE 802.11e Enhanced Distributed Channel Access (EDCA) protocol allows class based differentiated Quality of service (QoS) in a wireless local area network (WLAN). Different fixed values of two certain parameters; ... -
Dual-Core Photonic Crystal Fiber-Based Plasmonic RI Sensor in the Visible to Near-IR Operating Band
(IEEE, 2020-10-04)In this paper, a dual-core photonic crystal fiber (DC-PCF) based surface plasmon resonance (SPR) bio-compatible sensor is proposed for various bio-organic molecules and biochemical analytes refractive index (RI) detection ... -
Editorial: Recent advances in EEG (non-invasive) based BCI applications
(Frontiers, 2023-03-02) -
EEG-based Mouse Cursor Control using Motor Imagery Brain-Computer Interface
(IEEE, 2024-05-03)Brain-computer interface (BCI) is a system that collects, analyzes, and transforms brain signals into commands. The brain experiences repetitive, oscillatory electrical changes caused by these activities that have a very ... -
EEG-Based Preference Classification for Neuromarketing Application
(Hindawi, 2023-03-01)Neuromarketing is a modern marketing research technique whereby consumers’ behavior is analyzed using neuroscientific approaches. In this work, an EEG database of consumers’ responses to image advertisements was created, ... -
Effect of artifact removal on EEG based motor imagery BCI applications
(SPIE Digital Library, 2024-01-29)Brain computer interface (BCI) is an emerging technology where the user can establish direct communication between the electrical device and himself without any physical exertion. The EEG signal is a noninvasive and low-cost ... -
Effect of varying the row and column size of periodic arrays of plasmonic nanoparticles on the energy conversion efficiency of thin-film solar cells
(2020-10-07)The use of plasmonic nanostructures in enhancing the energy conversion efficiency of solar cells has been of great interest in recent times. While much of this interest has resulted in research for analyzing the metals ... -
Emotion classification using single-channel scalp-EEG recording
(IEEE, 2016-10-18)Several studies have found evidence for corticolimbic Theta electroencephalographic (EEG) oscillation in the neural processing of visual stimuli perceived as fear or threatening scene. Recent studies showed that neural ... -
Frequency Estimation of Unbalanced Three-Phase Power Systems Using the Modified Adaptive Filtering
(Scientific & Academic Publishing, 2015-08)In this paper, the problem of frequency estimation using adaptive filters is addressed based on the augmented complex normalized least mean squares (ACNLMS) technique. In other words, motivated from ACLMS technique, a new ... -
A High Performance Delta-Sigma Modulator for Neurosensing
(Sensors, 2015-08-07)Recorded neural data are frequently corrupted by large amplitude artifacts that are triggered by a variety of sources, such as subject movements, organ motions, electromagnetic interferences and discharges at the electrode ... -
Influence of particle shape on the efficacy of plasmonic metal nanoparticles to enhance the energy conversion efficiency of thin-film solar cells
(IEEE, 2020-10-07)The energy conversion efficiency of solar cells can be enhanced significantly due to the effect of coupling the solar cells with plasmonic nanostructures. However, while the advantage of using plasmonic nanostructures has ... -
Intelligent fuzzy system for automatic artifact detection and removal from EEG signals
(Elsevier, 2022-10-05)The EEG signals were used in many medical and technological applications such as diagnosis of diseases, rehabilitation of disabled peoples, preventive healthcare, BCI (brain computer interface) systems. EEG signal is prone ... -
The Journey of Elastography: Background, Current Status and Future Possibilities in Breast Cancer Diagnosis
(Elsevier, 2015)Elastography is a promising way to assess tissue differences regarding stiffness or elasticity for what was historically assessed manually by palpation. Combined with conventional imaging modalities (eg, ultrasonography ... -
Machine Learning Model for Computer-Aided Depression Screening among Young Adults Using Wireless EEG Headset
(Hindawi, 2023-05-31)Depression is a disorder that if not treated can hamper the quality of life. EEG has shown great promise in detecting depressed individuals from depression control individuals. It overcomes the limitations of traditional ...
