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Electroencephalography (EEG) serves as an effective diagnostic tool for mental disorders and neurological abnormalities. Enhanced analysis and classification of EEG signals can help improve detection performance. A new approach is examined…

信号处理 · 电气工程与系统科学 2020-02-11 Lubna Shibly Mokatren , Rashid Ansari , Ahmet Enis Cetin , Alex D Leow , Heide Klumpp , Olusola Ajilore , Fatos Yarman Vural

Resting state electroencephalogram (EEG) abnormalities in clinically high-risk individuals (CHR), clinically stable first-episode patients with schizophrenia (FES), healthy controls (HC) suggest alterations in neural oscillatory activity.…

信号处理 · 电气工程与系统科学 2018-01-18 Haichun Liu , TianHong Zhang , Yumeng Ye , Changchun Pan , Genke Yang , JiJun Wang , Robert C. Qiu

Electroencephalography (EEG) is a widely used technique for measuring brain activity. EEG-based signals can reveal a persons emotional state, as they directly reflect activity in different brain regions. Emotion-aware systems and EEG-based…

机器学习 · 计算机科学 2026-02-03 Ashna Purwar , Gaurav Simkar , Madhumita , Sachin Kadam

This paper proposes a new approach to identifying patients with insomnia using a single EEG channel, without the need for sleep stage annotation. Data preprocessing, feature extraction, feature selection, and classification techniques are…

计算机视觉与模式识别 · 计算机科学 2024-12-16 Chan-Yun Yang , Nilantha Premakumara , Hooman Samani , Chinthaka Premachandra

Depression is a common psychiatric disorder, which causes significant patient distress. Bipolar disorder is characterized by mood fluctuations between depression and mania. Unipolar and bipolar depression can be easily confused because of…

图像与视频处理 · 电气工程与系统科学 2019-09-02 Marie Zelenina , Diana Prata

Parkinson's disease (PD), a severe and progressive neurological illness, affects millions of individuals worldwide. For effective treatment and management of PD, an accurate and early diagnosis is crucial. This study presents a deep…

信号处理 · 电气工程与系统科学 2023-08-16 Niloufar Delfan , Mohammadreza Shahsavari , Sadiq Hussain , Robertas Damaševičius , U. Rajendra Acharya

In this study we focus on the diagnosis of Parkinson's Disease (PD) based on electroencephalogram (EEG) signals. We propose a new approach inspired by the functioning of the brain that uses the dynamics, frequency and temporal content of…

系统与控制 · 电气工程与系统科学 2023-03-31 Houssem Meghnoudj , Bogdan Robu , Mazen Alamir

Electroencephalogram (EEG) provides noninvasive measures of brain activity and is found to be valuable for diagnosis of some chronic disorders. Specifically, pre-treatment EEG signals in alpha and theta frequency bands have demonstrated…

应用统计 · 统计学 2023-05-24 Bin Yang , Xingche Guo , Ji Meng Loh , Qinxia Wang , Yuanjia Wang

Biomedical signals aid in the diagnosis of different disorders and abnormalities. When targeting lossy compression of such signals, the medically relevant information that lies within the data should maintain its accuracy and thus its…

信息论 · 计算机科学 2024-10-30 Hoda Daou , Fabrice Labeau

Resting-state EEG (rs-EEG) has been demonstrated to aid in Parkinson's disease (PD) diagnosis. In particular, the power spectral density (PSD) of low-frequency bands ({\delta} and {\theta}) and high-frequency bands ({\alpha} and \b{eta})…

The Guided Imagery technique is reported to be used by therapists all over the world in order to increase the comfort of patients suffering from a variety of disorders from mental to oncology ones and proved to be successful in numerous of…

With more than 300 million people depressed worldwide, depression is a global problem. Due to access barriers such as social stigma, cost, and treatment availability, 60% of mentally-ill adults do not receive any mental health services.…

计算机视觉与模式识别 · 计算机科学 2018-11-28 Albert Haque , Michelle Guo , Adam S Miner , Li Fei-Fei

Emerging evidence showed that major depressive disorder (MDD) is associated with disruptions of brain structural and functional networks, rather than impairment of isolated brain region. Thus, connectome-based models capable of predicting…

神经元与认知 · 定量生物学 2021-10-18 Aya Kabbara , Gabriel Robert , Mohamad Khalil , Marc Verin , Pascal Benquet , Mahmoud Hassan

In the status quo, dementia is yet to be cured. Precise diagnosis prior to the onset of the symptoms can prevent the rapid progression of the emerging cognitive impairment. Recent progress has shown that Electroencephalography (EEG) is the…

According to the World Health Organization, the number of mental disorder patients, especially depression patients, has grown rapidly and become a leading contributor to the global burden of disease. However, the present common practice of…

Representation and classification of Electroencephalography (EEG) brain signals are critical processes for their analysis in cognitive tasks. Particularly, extraction of discriminative features from raw EEG signals, without any…

机器学习 · 计算机科学 2019-05-01 Emad-ul-Haq Qazi , Muhammad Hussain , Hatim Aboalsamh

While EEG features differentiate Major Depressive Disorder (MDD) from healthy controls (HC), their clinical utility as biomarkers depends on a monotonic trajectory across the disease spectrum, from the acute (AC) phase to the maintenance…

神经元与认知 · 定量生物学 2026-03-05 Feng Yan , Xuteng Wang , Shuyu Yang , Yue Zhao , Xiaobin Wong , Zhiren Wang

Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations in high-frequency waves associated with psychotic disorders during…

神经元与认知 · 定量生物学 2023-01-05 Sadi Md. Redwan , Md Palash Uddin , Anwaar Ulhaq , Muhammad Imran Sharif

There is mounting evidence of a link between the properties of electroencephalograms (EEGs) of depressive patients and the outcome of pharmacotherapy. The goal of this study was to develop an EEG biomarker of antidepressant treatment…

神经元与认知 · 定量生物学 2017-02-17 Wojciech Jernajczyk , Pawel Gosek , Miroslaw Latka , Klaudia Kozlowska , Lukasz Swiecicki , Bruce J. West

The problem of detecting the presence of Social Anxiety Disorder (SAD) using Electroencephalography (EEG) for classification has seen limited study and is addressed with a new approach that seeks to exploit the knowledge of EEG sensor…