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Related papers: Nigerian Schizophrenia EEG Dataset (NSzED) Towards…

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One notable method for recording brainwaves to identify neurological problems is electroencephalography (hereafter EEG). A trained neuro physician can learn more about how the brain functions through the use of EEGs. However conventionally,…

Neurons and Cognition · Quantitative Biology 2024-02-26 Hari Prasad SV

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.…

Signal Processing · Electrical Eng. & Systems 2018-01-18 Haichun Liu , TianHong Zhang , Yumeng Ye , Changchun Pan , Genke Yang , JiJun Wang , Robert C. Qiu

In the field of neuroscience, Brain activity analysis is always considered as an important area. Schizophrenia(Sz) is a brain disorder that severely affects the thinking, behaviour, and feelings of people all around the world.…

Signal Processing · Electrical Eng. & Systems 2021-11-23 Geetanjali Sharma , Amit M. Joshi

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…

Digital phenotyping in mental health often consists of collecting behavioral and experience-based information through sensory and self-reported data from devices such as smartphones. Such rich and comprehensive data could be used to develop…

Social and Information Networks · Computer Science 2023-12-05 Andy Davies , Eiko Fried , Hane Aung , Omar Costilla-Reyes

We describe a Magnetic Resonance Imaging (MRI) dataset from individuals from the African nation of Nigeria. The dataset contains pseudonymized structural MRI (T1w, T2w, FLAIR) data of clinical quality. The dataset contains data from 36…

Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional, and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of motivation, and difficulties in concentration. Diagnosing…

Epilepsy affects over 50 million people worldwide, and one-third of patients suffer drug-resistant seizures where surgery offers the best chance of seizure freedom. Accurate localization of the epileptogenic zone (EZ) relies on intracranial…

More than 50 million individuals are affected by epilepsy, a chronic neurological disorder characterized by unprovoked, recurring seizures and psychological symptoms. Researchers are working to automatically detect or predict epileptic…

Signal Processing · Electrical Eng. & Systems 2023-06-22 Palak Handa , Sakshi Tiwari , Nidhi Goel

Children with neurodevelopmental disorders require timely intervention to improve long-term outcomes, yet early screening remains inaccessible in many regions. A scalable solution integrating standardized assessments with physiological data…

Signal Processing · Electrical Eng. & Systems 2025-03-19 Andreas Bauer , William Bosl , Oliver Aalami , Paul Schmiedmayer

The research presents a machine learning (ML) classifier designed to differentiate between schizophrenia patients and healthy controls by utilising features extracted from electroencephalogram (EEG) data, specifically focusing on…

Machine Learning · Computer Science 2025-03-18 Sara Alkhalifa

Schizophrenia (SZ) is a mental disorder whereby due to the secretion of specific chemicals in the brain, the function of some brain regions is out of balance, leading to the lack of coordination between thoughts, actions, and emotions. This…

Timely identification of harmful brain activities via electroencephalography (EEG) is critical for brain disease diagnosis and treatment, which remains limited application due to inter-rater variability, resource constraints, and poor…

Neurological disorders pose major global health challenges, driving advances in brain signal analysis. Scalp electroencephalography (EEG) and intracranial EEG (iEEG) are widely used for diagnosis and monitoring. However, dataset…

Neurons and Cognition · Quantitative Biology 2025-10-24 Jiahe Li , Xin Chen , Fanqi Shen , Junru Chen , Yuxin Liu , Daoze Zhang , Zhizhang Yuan , Fang Zhao , Meng Li , Yang Yang

We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14…

This study investigates the potential of multimodal data integration, which combines electroencephalogram (EEG) data with sociodemographic characteristics like age, sex, education, and intelligence quotient (IQ), to diagnose mental diseases…

Machine Learning · Computer Science 2025-02-07 Himanshi Singh , Sadhana Tiwari , Sonali Agarwal , Ritesh Chandra , Sanjay Kumar Sonbhadra , Vrijendra Singh

Schizophrenia (SZ) is a serious mental disorder that could seriously affect the patient's quality of life. In recent years, detection of SZ based on deep learning (DL) using electroencephalogram (EEG) has received increasing attention. In…

Neurons and Cognition · Quantitative Biology 2022-07-12 Yihan Wu , Min Xia , Xiuzhu Wang , Yangsong Zhang

The Epilepsies are a common, chronic neurological disorder affecting more than 50 million individuals across the globe. It is characterized by unprovoked, recurring (similar or different type) seizures which are commonly diagnosed through…

Signal Processing · Electrical Eng. & Systems 2021-08-03 Palak Handa , Monika Mathur , Nidhi Goel

Clinical electroencephalography is routinely used to evaluate patients with diverse and often overlapping neurological conditions, yet interpretation remains manual, time-intensive, and variable across experts. While automated EEG analysis…

Human-Computer Interaction · Computer Science 2025-12-30 Argha Kamal Samanta , Deepak Mewada , Monalisa Sarma , Debasis Samanta

Patients with schizophrenia often display impairments in the expression of emotion and speech and those are observed in their facial behaviour. Automatic analysis of patients' facial expressions that is aimed at estimating symptoms of…

Computer Vision and Pattern Recognition · Computer Science 2018-08-09 Mina Bishay , Petar Palasek , Stefan Priebe , Ioannis Patras
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