AIMC Topic: Electroencephalography
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Machine learning approaches for fine-grained symptom estimation in schizophrenia: A comprehensive review.
Artificial intelligence in medicine
Jul 1, 2025
Schizophrenia is a severe yet treatable mental disorder, and it is diagnosed using a multitude of primary and secondary symptoms. Diagnosis and treatment for each individual depends on the severity of the symptoms. Therefore, there is a need for accu...
Deep generative models for physiological signals: A systematic literature review.
Artificial intelligence in medicine
Jul 1, 2025
In this paper, we present a systematic literature review on deep generative models for physiological signals, particularly electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG) and electromyogram (EMG). Compared to the existin...
A neural approach to the Turing Test: The role of emotions.
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
As is well known, the Turing Test proposes the possibility of distinguishing the behavior of a machine from that of a human being through an experimental session. The Turing Test assesses whether a person asking questions to two different entities, c...
Self-training EEG discrimination model with weakly supervised sample construction: An age-based perspective on ASD evaluation.
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Deep learning for Electroencephalography (EEG) has become dominant in the tasks of discrimination and evaluation of brain disorders. However, despite its significant successes, this approach has long been facing challenges due to the limited availabi...
Ternary spike-based neuromorphic signal processing system.
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Deep Neural Networks (DNNs) have been successfully implemented across various signal processing fields, resulting in significant enhancements in performance. However, DNNs generally require substantial computational resources, leading to significant ...
Mobile Sleep Stage Analysis Using Multichannel Wearable Devices Integrated with Stretchable Transparent Electrodes.
ACS sensors
Jun 27, 2025
The prevalence of sleep disorders in the aging population and the importance of sleep quality for health have emphasized the need for accurate and accessible sleep monitoring solutions. Polysomnography (PSG) remains the clinical gold standard for dia...
[Study on speech imagery electroencephalography decoding of Chinese words based on the CAM-Net model].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Jun 25, 2025
Speech imagery is an emerging brain-computer interface (BCI) paradigm with potential to provide effective communication for individuals with speech impairments. This study designed a Chinese speech imagery paradigm using three clinically relevant wor...
Unraveling Parkinson's disease motor subtypes: A deep learning approach based on spatiotemporal dynamics of EEG microstates.
Neurobiology of disease
Jun 15, 2025
BACKGROUND: Despite prior studies on early-stage Parkinson's disease (PD) brain connectivity and temporal patterns, differences between tremor-dominant (TD) and postural instability/gait difficulty (PIGD) motor subtypes remain poorly understood. Our ...
SHAP-Driven Feature Analysis Approach for Epileptic Seizure Prediction.
Journal of medical systems
Jun 10, 2025
Predicting epileptic seizures presents a substantial difficulty in healthcare, with considerable implications for enhancing patient outcomes and quality of life. This paper presents an explainable artificial intelligence (AI) that integrates a one-di...
CNNs improve decoding of selective attention to speech in cochlear implant users.
Journal of neural engineering
Jun 10, 2025
. Understanding speech in the presence of background noise such as other speech streams is a difficult problem for people with hearing impairment, and in particular for users of cochlear implants (CIs). To improve their listening experience, auditory...
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