Electroencephalogram (EEG) signals pose a challenge to emotion recognition (ER) tasks due to their complexity and individual differences. Conventional machine learning methods usually rely on handcrafted feature extraction and perform poorly in cross...
OBJECTIVES: Understanding drivers' cognitive load is essential for enhancing road safety, as cognitive demands fluctuate across different driving scenarios, potentially impacting performance, and safety, particularly for drivers with neurological dis...
We propose a deep learning approach for beat-wise atrial fibrillation (AF) detection in electrocardiogram (ECG) signals. AF, a major cardiac arrhythmia affecting millions globally, requires early detection for optimal treatment outcomes. Current rhyt...
International journal of neural systems
Jun 1, 2025
Extracellular recordings of neuronal spikes are crucial for studying brain activity. These signals are typically classified based on firing patterns and waveform shape, particularly trough-to-peak duration. While useful, this method oversimplifies th...
The accurate assessment of pain in clinical settings is challenging due to its subjective nature. In this study, we used functional near-infrared spectroscopy (fNIRS) to measure brain activity by detecting changes in blood oxygenation. Leveraging the...
Blood pressure is a critical risk factor for cardiovascular diseases (CVDs), yet most adults do not monitor it frequently enough to prevent serious complications. This is in part because the traditional cuff-based method is inconvenient, uncomfortabl...
BACKGROUND: Considering the prevalence of Alzheimer's Disease (AD) among the aging population and the limited means of treatment, early detection emerges as a crucial focus area whereas electroencephalography (EEG) provides a promising diagnostic too...
BACKGROUND: Treatment for essential tremor (ET) and cortical myoclonus (CM) differs. As their clinical distinction can be difficult, with large inter- and intra-observer variability, there is a need for additional diagnostic tools.
In this paper, a hybrid CNN-BiLSTM model for EEG-based emotion detection system is presented. The proposed technique is developed by extracting features using Power Spectral Density (PSD) signal. The proposed approach is carried out by combining CNN ...
In electrocardiography (ECG), measurement of QRS duration (QRSd) is crucial for diagnosing conditions such as left bundle branch block. To address the limited availability of ECG databases with QRS delineation labels, we present a method to use small...
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