Electroencephalography

Acoustic and Text Features Analysis for Adult ADHD Screening: A Data-Driven Approach Utilizing DIVA Interview
Acoustic and Text Features Analysis for Adult ADHD Screening: A Data-Driven Approach Utilizing DIVA Interview 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)
Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder commonly seen in childhood that leads to behavioural changes in social development and communication patterns, often continues into undiagnosed adulthood due… read more

Variation in the Photoplethysmogram Response to Arousal from Sleep Depending on the Cause of Arousal and the Presence of Desaturation
Variation in the Photoplethysmogram Response to Arousal from Sleep Depending on the Cause of Arousal and the Presence of Desaturation 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)
Objective: The aim of this study was to assess how the photoplethysmogram frequency and amplitude responses to arousals from sleep differ between arousals caused by apneas and hypopneas with and… read more

Impaired brain-heart relation in patients with methamphetamine use disorder during VR induction of drug cue reactivity
Impaired brain-heart relation in patients with methamphetamine use disorder during VR induction of drug cue reactivity 1978 2560 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)
Objective: Methamphetamine use disorder (MUD) is an illness associated with severe health consequences. Virtual reality (VR) is used to induce the drug-cue reactivity and significant EEG and ECG abnormalities were… read more

Classifying multi-level stress responses from brain cortical EEG in Nurses and Non-health professionals using Machine Learning Auto Encoder
Author(s)3: Ashlesha Akella, Avinash Kumar Singh, Daniel Leong, Sara Lal, Phillip Newton, Roderick Clifton-Bligh, Craig Steven McLachlan, Sylvia Maria Gustin, Shamona Maharaj, Ty Lees, Zehong Cao, Chin-Teng Lin
Classifying multi-level stress responses from brain cortical EEG in Nurses and Non-health professionals using Machine Learning Auto Encoder 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Objective: Mental stress is a major problem in our society and has become an area of interest for many psychiatric researchers. One primary research focus area is the identification of…

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Massage Therapy’s Effectiveness on the decoding EEG rhythms of Left/Right Motor Imagery and Motion Execution in Patients with Skeletal Muscle Pain
Author(s)3: Huihui Li, Kai Fan, Junsong Ma, Bo Wang, Xiaohao Qiao, Yan Yan, Wenjing Du, Lei Wanga
Massage Therapy’s Effectiveness on the decoding EEG rhythms of Left/Right Motor Imagery and Motion Execution in Patients with Skeletal Muscle Pain 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Objective: Most of effectiveness assessments of the widely-used Massage therapy were based on subjective routine clinical assessment tools, such as Visual Analogue Scale (VAS) score. However, few studies demonstrated the…

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A deep convolutional neural network method to detect seizures and characteristic frequencies using epileptic electroencephalogram (EEG) data
Author(s)3: Md. Rashed-Al-Mahfuz, Mohammad Ali Moni, Shahadat Uddin, Salem A. Alyami, Mattew A. Summers, Valsamma Eapen
A deep convolutional neural network method to detect seizures and characteristic frequencies using epileptic electroencephalogram (EEG) data 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Background: Diagnosing epileptic seizures using electroencephalogram (EEG) in combination with deep learning computational methods has received much attention in recent years. However, to date, deep learning techniques in seizure detection…

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Low-Power and Low-Cost Dedicated Bit-Serial Hardware Neural Network for Epileptic Seizure Prediction System

Low-Power and Low-Cost Dedicated Bit-Serial Hardware Neural Network for Epileptic Seizure Prediction System
Author(s)3: Si Mon Kueh, Tom J. Kazmierski
Low-Power and Low-Cost Dedicated Bit-Serial Hardware Neural Network for Epileptic Seizure Prediction System 780 547 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

  This paper presents results of using a simple bit-serial architecture as a method of designing an extremely low-power and low-cost neural network processor for epilepsy seizure prediction. The proposed…

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An Ultra Low Power Smart Headband for Real-time Epileptic Seizure Detection

An Ultra Low Power Smart Headband for Real-time Epileptic Seizure Detection
Author(s)3: Shih-Kai Lin, Istiqomah, Li-Chun Wang, Chin-Yew Lin, Herming Chiueh
An Ultra Low Power Smart Headband for Real-time Epileptic Seizure Detection 780 494 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

     Abstract In this paper, the design of a smart headband for epileptic seizure detection is presented. The proposed headband consists of four key components: 1) an analog front-end circuitry,…

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Panel B shows 12 minutes of bipolar EEG from Fp2-F4 (1-70 Hz, 200 S/s). Panel A is the corresponding spectrogram. Panel E shows 30 seconds of EEG from Panel B at the onset of the generalized seizure (dashed line). Panels C, D, and F are the corresponding tEEG signals from Fp2’ (1-100 Hz, 200 S/s). Note the high gamma-band burst HFOs just prior to the partial seizure (highlighted by ellipse in panel C).

High-Frequency Oscillations Recorded on the Scalp of Patients with Epilepsy Using Tripolar Concentric Ring Electrodes
High-Frequency Oscillations Recorded on the Scalp of Patients with Epilepsy Using Tripolar Concentric Ring Electrodes 540 508 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Panel B shows 12 minutes of bipolar EEG from Fp2-F4 (1-70 Hz, 200 S/s). Panel A is the corresponding spectrogram. Panel E shows 30 seconds of EEGfrom Panel B at…

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