AIMC Topic: Signal Processing, Computer-Assisted

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[A motor imagery decoding study integrating differential attention with a multi-scale adaptive temporal convolutional network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Motor imagery electroencephalogram (MI-EEG) decoding algorithms face multiple challenges. These include incomplete feature extraction, susceptibility of attention mechanisms to distraction under low signal-to-noise ratios, and limited capture of long...

Integrating Motor Unit Activity With Deep Learning for Real-Time, Simultaneous and Proportional Wrist Angle and Grasp Force Estimation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Myoelectric prostheses offer great promise in enabling amputees to perform daily activities independently. However, existing neural interfaces generally cannot simultaneously and proportionally decode kinematics and kinetics in real time, ...

Hierarchical Transformer Fusion of Gaze Attention and Muscle Activity for Forearm Movement Estimation.

IEEE transactions on bio-medical engineering
Tracking forearm movement via measured physiological signals is crucial for understanding human motor control mechanism. Current methods mainly use muscle-derived signals to predict arm movements while often overlooking the potential role of gaze att...

ECG-SMART-NET: A Deep Learning Architecture for Precise ECG Diagnosis of Occlusion Myocardial Infarction.

IEEE transactions on bio-medical engineering
OBJECTIVE: In this paper we develop and evaluate ECG-SMART-NET for occlusion myocardial infarction (OMI) identification. OMI is a severe form of heart attack characterized by complete blockage of one or more coronary arteries requiring immediate refe...

Deep Learning for EEG-Based Visual Classification and Reconstruction: Panorama, Trends, Challenges and Opportunities.

IEEE transactions on bio-medical engineering
Deep learning has significantly enhanced the research on the emerging issue of Electroencephalogram (EEG)-based visual classification and reconstruction, which has gained a growth of attention and concern recently. To promote the research progress, a...

Adaptive Cardiorespiratory Separation With Harmonic Models and Filters: The Case of Electrical Impedance Tomography.

IEEE transactions on bio-medical engineering
Cardiorespiratory monitoring methods are vital in clinical and personal healthcare contexts, continuously delivering comprehensive insights into patient health. Among them, electrical impedance tomography, a non-invasive imaging modality, uniquely en...

CLaI: Collaborative Learning and Inference for Low-Resolution Physiological Signals: Validation in Clinical Event Detection and Prediction.

IEEE transactions on bio-medical engineering
While machine learning (ML) techniques have been applied to detection and prediction tasks in clinical data, most methods rely on high-resolution data, which is not routinely available in most Intensive Care Units (ICUs), and perform poorly when face...

Deep Learning-Augmented Sleep Spindle Detection for Acute Disorders of Consciousness: Integrating CNN and Decision Tree Validation.

IEEE transactions on bio-medical engineering
Sleep spindles, which are key biomarkers of non-rapid eye movement stage 2 sleep, play a crucial role in predicting outcomes for patients with acute disorders of consciousness (ADOC). However, several critical challenges remain in spindle detection: ...

Multi-View Self-Supervised Learning Enhances Automatic Sleep Staging From EEG Signals.

IEEE transactions on bio-medical engineering
Deep learning-based methods for automatic sleep staging offer an efficient and objective alternative to costly manual scoring. However, their reliance on extensive labeled datasets and the challenge of generalization to new subjects and datasets limi...

[Cough frequency monitoring: current technologies and clinical research applications].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Cough is a common symptom of many respiratory diseases, and parameters such as frequency, intensity, type and duration play important roles in disease screening, diagnosis and prognosis. Among these, cough frequency is the most widely applied metric....