Many clinicians presume that a screening electroencephalogram (EEG) is useful in differentiating psychiatric from neurologic disorders. In a retrospective review of 698 charts of psychiatric inpatients, the authors assessed the usefulness of screening EEGs. Usefulness was defined as leading to a change in diagnosis or treatment. While 31% of screening EEGs were abnormal, only 1.7% of cases led to a change in diagnosis that might otherwise have been missed. It is unclear whether the EEG is a useful screening test on the basis of these results. Caution is warranted in interpreting these results because of the inaccuracies inherent in any retrospective review. Prospective studies are needed to better define EEG's usefulness in psychiatry.
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Annu Int Conf IEEE Eng Med Biol Soc
July 2024
Epilepsy, traditionally conceptualized as a neurological disorder characterized by a persistent inclination toward epileptic seizures, is commonly diagnosed and monitored through EEGs. However, manual analysis of EEG data can be exceedingly time-consuming. The integration of automated seizure classification methods represents a valuable resource for clinicians engaged in epilepsy analysis.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
Chronic pain often goes unrecognized and untreated in individuals with Alzheimer's disease and related dementias (ADRD), mainly due to limited capacity to verbalize pain. Addressing this issue requires the development of reliable objective biomarkers for pain. In the present pilot study, we explored the feasibility and acceptability of using a wearable electroencephalograph (EEG) and a screen-based eye tracker system to identify neural signatures of chronic pain in this population.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
Schizophrenia is a complex brain disorder that leads to an abnormal interpretation of reality. One of its reliable biological markers is the auditory evoked potential P300. The aim of the current paper is to classify healthy-control subjects from schizophrenic patients using EEG signals collected during an auditory oddball paradigm.
View Article and Find Full Text PDFNeurocrit Care
March 2025
Comprehensive Epilepsy Center, Department of Neurology, Yale New Haven Hospital, New Haven, CT, USA.
Background: Increasing use of continuous electroencephalography (cEEG) provides the opportunity to observe temporal trends in EEG patterns during the acute phase of brain injury. These trends have not been extensively documented.
Methods: We conducted a retrospective chart review of patients undergoing cEEG between January 1st and June 30th, 2019, at two academic medical centers.
IEEE J Biomed Health Inform
March 2025
The study introduces an innovative approach to efficient mental stress detection by combining electroencephalography (EEG) analysis with on-chip neural networks, taking advantage of EEG's temporal resolution and the computational capabilities of embedded neural networks. The proposed system utilizes behind-the-ear (BTE) EEG signals and on-chip neural networks for mental stress detection. A wearable custom-designed device captures EEG signals from a single BTE channel, performs on-chip signal-to-spectrogram conversion, and integrates a compact convolutional neural network (CNN) for stress classification.
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